81 jobs found

Job Description Job Description Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together. Principal Applied AI Engineer Location: Remote (US) Lead the engineering of software that matters - driving AI automation for the world's largest enterprises. ABOUT THE TEAM Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. THE OPPORTUNITY As a Principal Applied AI Engineer, you will serve as the technical linchpin for applied AI on the team, bringing deep hands-on expertise in designing and operating production LLM systems and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity AI systems - spanning code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability - set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. WHAT YOU'LL DO Develop Clean Software: Architect, build, and optimize high-performance production LLM systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase - and the AI systems built on it - cutting-edge, modern, and performant. Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness. Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier and AI-powered application layers - from feature scoping through implementation. Build prototypes to de-risk novel AI approaches and establish the standards others build on. Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning. Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence. Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you. Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering's permanent documentation site. REQUIRED QUALIFICATIONS Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree). Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field). Production LLM Systems: Deep hands-on experience designing and operating production LLM systems. AI Systems Expertise: Demonstrated expertise across code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability. AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context. Domain Expertise: Strong distributed-systems, API, security, and reliability foundations, with the ability to contribute meaningfully at a senior individual contributor level within that space. Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope. Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment. Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences. PREFERRED QUALIFICATIONS Compilers & Program Analysis: Experience with compilers, program analysis, formal or executable specifications, or legacy modernization is strongly preferred. We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment. The base salary range represents a good faith and reasonable estimate of the range at the time of posting. Actual compensation will be dependent on a number of factors including, but not limited to, the candidate's relevant work experience, qualifications, internal peer equity, and market and business conditions that exist when extending an offer. A discretionary bonus may be awarded in recognition of individual and company performance. In addition, Appian provides generous benefits offerings that include a 401(k) plan with company match, flexible time off, paid parental leave, medical, dental, and vision plans, life insurance, disability insurance, wellness programs, flexible spending accounts, health savings account contributions, an employee referral bonus program, and learning and development resources. Certain positions may be eligible for equity awards. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation, commission, bonus, or benefit plans. Base Salary Range $200,000-$350,000 USD Tools and Resources Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires. Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities. Community: We'll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company. Benefits Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to. About Appian Appian provides AI automation for mission-critical work. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We've been automating processes for more than 25 years and understand enterprise operations like no one else. For more information, visit Nasdaq: APPN Follow Appian: LinkedIn, Youtube, Instagram, Facebook Appian is an equal opportunity employer that strives to attract and retain the best talent. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law. Appian provides reasonable accommodations to applicants in accordance with all applicable laws. If you need a reasonable accommodation for any part of the employment process, please contact us by email at . Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address. Appian's Applicant & Candidate Privacy Notice

Job Description Job Description Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together. Principal ML Platform Engineer Location: Remote (US) Lead the engineering of software that matters - driving AI automation for the world's largest enterprises. About the Team Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. The Opportunity As a Principal Software Engineer, you will serve as a technical linchpin for the team, bringing deep expertise in cloud-native architecture and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity engineering solutions, set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. What You'll Do Develop Clean Software: Architect, build, and optimize high-performance software systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase cutting-edge, modern, and performant. Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness. Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier application layers - from feature scoping through implementation. Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning. Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence. Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you. Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering's permanent documentation site. Required Qualifications Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree). Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field). Technical Mastery: Expert coding, scripting, and debugging proficiency in one or more core enterprise programming languages, specifically Java, Python, or Go. Domain Expertise: Deep working knowledge of distributed systems, cloud infrastructure, and the ability to contribute meaningfully at a senior individual contributor level within that space. Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope. AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context. Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment. Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences. Preferred Qualifications Cloud Architecture: Strong experience designing microservices, working with containerization (Docker, Kubernetes), and implementing modern CI/CD pipelines. Cloud Platforms: Deep experience developing and operating infrastructure across public cloud ecosystems, specifically AWS, Azure, and/or GCP. We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment. What We Equip You With High-Impact Autonomy: A leadership environment where you will have real ownership over your team's direction, the latitude to make meaningful decisions, and participation in broader Engineering discussions. New Hire Orientation: A robust onboarding experience designed to integrate you smoothly into our technology, culture, and leadership model so you can show up for your team from day one. Continuous Enablement: Access to premier learning resources and dedicated learning time focused on both your continued technical growth and your evolution as an engineering leader. Sponsored Certifications: Full corporate sponsorship for professional technical certifications to advance your engineering credentials. The base salary range represents a good faith and reasonable estimate of the range at the time of posting. Actual compensation will be dependent on a number of factors including, but not limited to, the candidate's relevant work experience, qualifications, internal peer equity, and market and business conditions that exist when extending an offer. A discretionary bonus may be awarded in recognition of individual and company performance. In addition, Appian provides generous benefits offerings that include a 401(k) plan with company match, flexible time off, paid parental leave, medical, dental, and vision plans, life insurance, disability insurance, wellness programs, flexible spending accounts, health savings account contributions, an employee referral bonus program, and learning and development resources. Certain positions may be eligible for equity awards. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation, commission, bonus, or benefit plans. Base Salary Range $175,000-$325,000 USD Tools and Resources Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires. Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities. Community: We'll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company. Benefits Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to. About Appian Appian provides AI automation for mission-critical work. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We've been automating processes for more than 25 years and understand enterprise operations like no one else. For more information, visit Nasdaq: APPN Follow Appian: LinkedIn, Youtube, Instagram, Facebook Appian is an equal opportunity employer that strives to attract and retain the best talent . click apply for full job details

Job Description Job Description Millennium NYC 5 days a week in office 200-225K Base plus bonus (total comp-400-500K) Technical Lead Market Data The SPEED Market Data team seeks a hands-on Technical Lead who will own and drive a critical workstream focused on architecting, implementing, monitoring, and supporting low-latency C++ systems that are robust, resilient, accurate, stable, and blindingly fast. By leading the design and evolution of this high-performance infrastructure, you will help position MLP as a leader in quantitative trading. You will shape the future of this industry while working alongside other exceptional engineers and strategists to solve some of the most significant engineering problems in the world. We are looking for a strong technical leader with financial markets technology experience and real-time market data expertise to design, build, and support our global real-time (both low-latency and non-latency-sensitive) market data platform. This role emphasizes technical leadership, architectural ownership, and cross-team coordination rather than people management. The successful candidate will be comfortable owning a workstream end-to-end-covering design, implementation, monitoring, support, and stakeholder management-while ensuring stability of the existing environment and driving platform improvements. Principal Responsibilities Act as the technical owner for a major market data workstream, setting technical direction, defining architecture, and driving execution across the full lifecycle. Collaborate with hardware and software teams across divisions to design and build real-time market data processing and distribution systems. Lead and drive new technical initiatives for the team, including evaluating technologies, defining standards, and establishing best practices. Design and develop systems, interfaces, and tools for historical market data and trading simulations that increase research productivity. Architect and implement components of an enterprise market data platform, including components for caching, aggregation, conflation and value-added data enrichment. Optimize platform performance using network and systems programming, and advanced low-latency techniques (CPU, NIC, kernel, and application-level tuning). Lead the design and maintenance of automated test and benchmark frameworks, and tools for risk management, performance tracking, and system validation. Provide technical leadership for the support and operation of both enterprise real-time market data environments, including coordinating internal, vendor, and exchange-driven changes. Design and engineer components to automate support and management of the market data platform, including monitoring, real-time and historical metrics collection/visualization, and self-service administrative/user tools. Serve as a primary technical liaison for users of the market data environment (Portfolio Managers, trading desks, and core technology teams), translating requirements into robust technical solutions. Lead the enhancement of processes and workflows for operating the market data platform (release/deployment, incident management and remediation, exchange notification handling, defining and enforcing SLAs). Mentor and influence other engineers through code reviews, design reviews, and hands-on guidance, fostering a culture of technical excellence and accountability. Qualifications / Skills Required Degree in Computer Science or a related field with a strong background in data structures, algorithms, and object-oriented programming in modern C++. Deep understanding of Linux system internals and networking, especially in low-latency and high-throughput environments. Strong knowledge of CPU architecture and the ability to leverage CPU capabilities for performance optimization. Demonstrated experience acting as a technical lead or senior engineer owning complex systems or workstreams end-to-end (design, delivery, and operations). Able to prioritize and make trade-offs in a fast-moving, high-pressure, constantly changing environment; strong sense of urgency, ownership, and follow-through. Strong belief in and practice of extreme ownership, with a track record of taking accountability for systems in production. Effective communication and stakeholder management skills: able to work closely with business and technology users, understand their needs, and drive appropriate technical solutions. Experience building solutions on cloud environments such as GCP and AWS. Knowledge of additional programming languages such as Java, Python, or scripting (Perl, shell). Technical background in application development on complex market data systems (e.g., Bloomberg, Thomson Reuters, etc.). Experience supporting market data environments within a global organization, including internally developed DMA feed handlers and distribution infrastructure. Strong understanding of market data concepts and functionality, including data models (fields/messages), protocols (e.g., snapshot + delta), order book representations (L1/L2/L3), recovery, and reliability. Hands-on Site Reliability Engineering or DevOps experience, including system administration, automation, measurement, and release/deployment management. Experience with monitoring, metrics, and command/control tooling for distributed market data platforms, with the ability to evaluate existing solutions and drive enhancements across development and operations. Ability to operate with a high level of thoroughness and attention to detail, demonstrating strong ownership of deliverables and production systems.

Job Description Job Description About Medical Guardian: Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. Mission: This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian. The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption. Role Summary: We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness. This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications. This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership. Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured. A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes. Key Responsibilities: Hands-On Data Engineering and Platform Development Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture. Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data. Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams. Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems. Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning. Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline. Real-Time Streaming, IoT Telemetry, and Operational Data Services Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds. Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns. Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads. Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases. Define reliability, latency, quality, observability, and supportability expectations for production streaming systems. Databricks, Lakehouse, and Data Platform Architecture Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design. Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design. Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership. Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture. Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact. Stakeholder Shaping and Cross-Functional Partnership Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like. Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans. Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value? Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests. Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders. Team Management and Principal-Level Technical Leadership Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability. Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making. Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives. Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security. Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed. Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions. ML/AI, Analytics, and GenAI Enablement Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops. Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation. Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases. Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on. Governance, Data Quality, Security, and Production Operations Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data. Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring. Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs. Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation. Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness. Required Qualifications: 10+ years of professional experience in data engineering . click apply for full job details

AI Engineer 5 (MLXT) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details

AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (MLXT) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details

AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

About Zaden Technologies, Inc. Join Zaden Technologies on our mission to simplify the delivery and improve the utility of software products for our customers. At Zaden, we believe that our employees are our greatest assets. We hire the right candidates with the right skill sets who fit our culture of customer obsession, innovation, and continuous learning. We are our customer's biggest advocate and we are looking for like-minded individuals who encompass these same ideals. It is important to us to offer you competitive pay and comprehensive benefits with opportunities that match your life and propel your career! Zaden Technologies is seeking an experienced Principal Windows Systems Administrator to lead the design, implementation, and management of enterprise Windows infrastructure and Azure Virtual Desktop environments. This role will be critical in supporting our DevSecOps initiatives and ensuring secure, scalable, and efficient system operations for defense and space systems. The ideal candidate will bring deep expertise in Windows system administration, Azure cloud infrastructure, and security hardening while working in a fast-paced environment supporting mission-critical applications. Role Responsibilities: Design, deploy, and manage Azure Virtual Desktop (AVD) environments including host pools, session hosts, and user profiles to support distributed workforce requirements Administer and optimize Group Policy Objects (GPOs) across enterprise domains to enforce security policies, user configurations, and system settings Conduct comprehensive security and vulnerability scanning using industry-standard tools, and remediate identified vulnerabilities in accordance with compliance requirements Manage Windows Update deployment strategies, including WSUS administration, patch testing, and enterprise-wide update rollouts with minimal operational disruption Oversee some Linux virtual machine environments within hybrid infrastructure, ensuring proper integration with Windows systems and maintaining cross-platform operational excellence Design and troubleshoot complex networking configurations including VPNs, subnets, routing, firewalls, and load balancers in both on-premises and Azure environments Architect and maintain Azure infrastructure components including virtual networks, storage accounts, resource groups, and identity management solutions Lead Security Technical Implementation Guide (STIG) compliance efforts by implementing and validating security baselines across a mixed fleet Provide technical leadership and mentorship to junior system administrators and contribute to the development of best practices and standard operating procedures Collaborate with DevSecOps teams to integrate infrastructure-as-code practices and automation workflows for system provisioning and configuration management Required Qualifications: U.S. Citizenship and active secret security clearance Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent practical experience 7+ years of hands-on experience in Windows system administration in enterprise environments Advanced expertise in Azure Virtual Desktop deployment, management, and optimization Demonstrated proficiency in Group Policy creation, management, and troubleshooting across complex Active Directory environments Strong experience with security and vulnerability scanning tools (e.g., Nessus, Qualys, Rapid7) and remediation workflows Proven track record managing Windows Server Update Services (WSUS) or equivalent patch management solutions In-depth knowledge of networking protocols, architectures, and troubleshooting methodologies (TCP/IP, DNS, DHCP, VPN) Solid understanding of Azure cloud services, Azure networking (VNets, NSGs, Application Gateway), and infrastructure management Hands-on experience implementing and validating STIG compliance on Windows and Linux systems Preferred Qualifications: Active Top Secret clearance with ability to obtain TS/SCI Microsoft certifications such as Azure Administrator Associate, Azure Solutions Architect Expert, or Windows Server Hybrid Administrator Associate Proficiency in basic Linux system administration tasks. Experience with Infrastructure-as-Code tools (Terraform, ARM templates, Bicep) Knowledge of containerization technologies (Docker, Kubernetes) and their integration with Windows infrastructure Familiarity with DevSecOps practices, CI/CD pipelines, and automation frameworks Experience with PowerShell scripting and automation for system administration tasks Background supporting Department of Defense (DoD) or federal government IT environments Experience with monitoring and observability tools (Azure Monitor, Log Analytics, Prometheus, Grafana) Knowledge of identity and access management solutions (Azure AD, ADFS, MFA implementation) Experience with disaster recovery planning and implementation in cloud environments What we offer: Robust startup environment with a variety of projects to work on Growth paths and endless opportunities to learn and develop Paid holidays Employer contributions toward 401k Performance-based bonus and profit-sharing 50% coverage of health insurance for employees and their dependents The pay range for this role is: 130,000 - 170,000 USD per year(Huntsville, AL) Compensation details: 00 Yearly Salary PIda68e5b312f7-2570

Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science

Job Description Job Description The future of aerospace and defense starts here. Ursa Major was founded to revolutionize how America and its allies access and apply high-performance propulsion, from hypersonics to solid rocket motors, satellite maneuvering and launch. We design and deliver propulsion and defense systems that solve the most urgent and critical national security demands. Ursa Major is bringing a new model to propulsion and defense technology: one where performance and access are no longer constrained by legacy systems. We design, build, and deploy advanced propulsion systems that power national security missions, hypersonic capabilities, and the future of space access. Our mission requires an extraordinary team-one that will mold tomorrow's critical technologies while deploying today's best. We are an intrinsically motivated team with a passion for solving complex technical problems and empowering each other every day, knowing that there is always room for growth. As a Principal DevOps Engineer within our Digital Operations team, you won't just be managing servers or responding to deployment tickets. You will be a principal technical leader and system architect responsible for owning and shaping Ursa Major's platform engineering, infrastructure automation, and software deployment strategies across cloud, on-premise, and manufacturing environments. Sitting at the vital intersection of Software Engineering, IT, Zero-Trust Networking, Digital Manufacturing, and Cybersecurity, you will build the foundational platforms that empower our engineering and manufacturing teams to design, test, and deliver mission-critical systems faster and more reliably. As Ursa Major expands, you will decompose complex technical challenges, author clear architecture designs, and drive pragmatic, high-impact solutions that connect our cloud environments directly to physical manufacturing and test-bench hardware. Responsibilities: Platform Architecture & Developer Experience Lead the research, design, and continuous improvement of platform infrastructure, software deployment, and Developer Experience (DX) across the enterprise. Decompose complex infrastructure problems into maintainable systems; author clear technical design documents and lead cross-functional teams through execution. Act as a strategic connector between Software Engineering, IT, and Networking to unify tooling, share infrastructure patterns, and eliminate operational silos. Infrastructure-as-Code (IaC), GitOps & High Availability (HA) Advance our declarative Infrastructure-as-Code (IaC) and GitOps practices (using Terraform, Helm, and ArgoCD/Flux) to deliver fully automated, drift-free application lifecycles across Azure GovCloud and AWS GovCloud. Extend containerization and orchestration (Kubernetes, Docker) beyond cloud environments into on-premise test benches, shop-floor PCs, and edge manufacturing hardware in alignment with our CMMC Level 2 hybrid strategy. Own Disaster Recovery (DR) and Business Continuity (BC) architecture-maintaining automated backup and failover capabilities that keep critical system recovery times measured in minutes, not days. DevSecOps & AI Pipeline Integration Partner with Cybersecurity and Zero-Trust teams to integrate automated vulnerability scanning, secrets management, and policy-as-code guardrails directly into CI/CD workflows without introducing developer friction. Architect and support automated pipelines for hosted and private AI models, enabling software and engineering teams to leverage high-throughput AI capabilities safely within our secure compliance boundary. Maintain continuous telemetry, metrics, and alerting frameworks (Prometheus, Grafana) to give engineers real-time visibility into application performance and pipeline health. Leadership, Mentorship & Impact Frame all technical initiatives in terms of maximum impact on overall business health, execution speed, and system reliability. Mentor and elevate engineers across the software and IT organizations, fostering a culture of analytical, value-driven problem-solving. Function as a top-level technical decision-maker, managing high-ambiguity challenges with high autonomy while maintaining psychological safety and clear standards of excellence Minimum Qualifications: 8+ years of professional DevOps, SRE, or Infrastructure/Platform Engineering experience, with a proven track record of principal-level technical leadership and system architecture. Hands-on mastery of Azure GovCloud and/or AWS GovCloud environments, with deep expertise in VPC networking, IAM, and cloud-native security controls. Advanced proficiency in Terraform, Docker, Kubernetes, Helm, and continuous delivery via GitOps patterns (ArgoCD, GitHub Actions, or Flux). Direct experience architecting high-availability systems, automated DR solutions, and telemetry suites (Prometheus, Grafana). Practical experience configuring automated container/code and centralized secrets management (AWS/Azure Key Vaults, HashiCorp Vault). Experience automating, deploying, or supporting hosted AI model integrations within production CI/CD pipelines. A proactive problem solver who builds trust across teams, rejects black-and-white thinking, and focuses on enabling business outcomes. Preferred Qualifications: Familiarity with NIST SP 800-171 / CMMC Level 2 compliance standards and securing CUI data flows. Experience with Artifactory, SonarQube, Open Policy Agent (OPA), Kyverno, or automated Software Bill of Materials (SBOM) tooling. Experience automating physical hardware, edge nodes, or shop-floor environments using Packer, Ansible, K3s, or Rancher. Experience orchestrating self-hosted or private AI model execution frameworks. Ability to obtain and maintain a U.S. Government Security Clearance. Colorado law requires us to tell you the base compensation range of this role, which is $175,000 - $215,000, determined by your education, experience, knowledge, skills, and abilities. The salary range for this role is intentionally wide as we are evaluating individuals based on their unique experience and abilities to fit our needs. Most importantly, we are excited to meet you and see if you are a great fit for our team. What we can't quantify for you are the exciting challenges, supportive team, and amazing culture we enjoy. Classification: Full-Time, Exempt Benefits Include: (Please note, Interns are not eligible for benefits) Unlimited PTO - Vacation, Sick, Personal, and Bereavement Paid Parental and Adoptive Leave Medical, Dental and Vision Insurance Tax Advantage Accounts (HSA/FSA) Employer Paid Short and Long Term Disability, Basic Life, AD&D Additional Benefit Options Including Voluntary Life and Emergency Medical Transport EAP Program Retirement Savings Plan - 401k with Company Match Equity Grants in the Company How To Apply: Interested candidates are encouraged to apply by filling out the application below and clicking "Submit Application". This position will be posted for a minimum of 3 days and will remain open until filled or adjusted based on the volume of applicants. NOTE: Research suggests that women and BIPOC individuals may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage anyone who believes they have the skills and the drive necessary to succeed here to apply for this role. Must be a U.S. Person (this includes U.S. Citizens and Permanent Residents). Eligibility to obtain and maintain a U.S. Security Clearance. We're an equal-opportunity employer. You will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. No outside recruiters, please.

Job Description Job Description Essential Responsibilities Define enterprise-wide platform strategy, vision, and target-state architectures for platforms such as Microsoft Fabric, Foundry/OpenAI, Databricks, and Synapse. Own the end-to-end lifecycle of cloud platforms. Establish standards and guardrails across all platform engineering domains. Drive innovation in cloud, data, and AI platforms (Fabric, OpenAI/Foundry, etc.). Lead large-scale transformation initiatives (e.g., platform modernization, DC exit, AI adoption). Act as the highest-level escalation point for technical decisions and complex issues. Influence enterprise architecture boards, governance, and regulatory alignment. Drive cost optimization strategies and large-scale efficiency improvements. Foster platform product mindset across the organization (self-service, reuse, enablement). Mentor senior and lead engineers; shape engineering culture and technical direction. Partner with executives and business leaders to translate strategy into platform capabilities. Education & Years of Experience Minimum - 4 Year Bachelors Degree in Computer Science, Engineering or related Minimum - 10 Years of Platform engineering, cloud infrastructure, SRE roles or related In Lieu of Education 12 Years of Supporting enterprise-level environments in platform engineering, cloud infrastructure or SRE roles or related License/Certifications/Training Preferred - Azure DevOps Engineer Expert (or equivalent DevOps focused certification) Preferred - Fabric Analytics Engineer Associate (or equivalent data platform focused certification) Preferred - Azure AI Engineer Associate (or equivalent AI focused certification) Preferred - HashiCorp Certified: Terraform Professional (or equivalent IaC focused certification) Preferred - Azure Solutions Architect Expert (or equivalent Cloud focused certification) Compensation & Benefits: Typical hiring range: $119,400.00 to $204,600.00 Annually. Actual compensation will be determined using factors such as experience, skills & knowledge. Benefits: Alliant provides a benefits package including health care, vision, dental, and 401k with employer match including: Annual performance bonus Work from home up to 3 days a week Paid parental leave Employee discount programs Time off including paid personal and sick days 11 paid holidays Education reimbursement Note that eligibility and cost of benefits can vary depending on the number of regularly scheduled hours, and job status such as regular full-time, regular part-time, or temporary employment. Adhere to and ensure compliance of all business transactions with policy and process of the Bank Secrecy Act. Ensures compliance with all applicable state and federal laws, company procedures and policies. Maintains integrity and ethics in all actions and conversations with or regarding credit union members and their accounts; complies with Privacy Act directives. The responsibilities listed do not contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this position. Duties, responsibilities and activities may change at any time with or without notice.

Job Description Job Description Company Description IFS is a billion-dollar revenue company with 7000+ employees on all continents. We deliver award-winning enterprise software solutions through the use of embedded digital innovation and a single cloud-based platform to help businesses be their best when it really matters-at the Moment of Service . At IFS, we're flexible, we're innovative, and we're focused not only on how we can engage with our customers, but on how we can make a real change and have a worldwide impact. We help solve some of society's greatest challenges, fostering a better future through our agility, collaboration, and trust. We celebrate diversity and accept that there are so many different perspectives in this world. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view. By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world. We're looking for innovative and original thinkers to work in an environment where you can so that we can help others make theirs. If you want to change the status quo, we'll help you make your moment. Join Team Purple. Join IFS. Job Description Our Aerospace & Defense business helps the world's leading airlines, MROs, OEMs and defense operators keep complex fleets and platforms mission-ready - managing the full maintenance, asset and service lifecycle at scale. We are reimagining how that software is built and delivered around AI, and we are investing in engineers who can put AI to work both inside our products and in how we build them. You operate forward deployed - working shoulder-to-shoulder with A&D customers in their own environments - to ship AI-powered mobile capabilities that connect IFS to the systems that run their operations. This is a Principal-level role: you are the person others build toward, setting technical direction across product groups, carrying deep expertise in Applied AI and Forward Deployed Engineering, and taking end-to-end ownership with a you-build-it, you-run-it mindset - from design and development through testing, deployment and operational reliability in the field. What you'll do • Shape our next-generation mobility solution. Help define and deliver the next-generation mobile experience for aviation maintenance - a fast, reliable, field-ready product that engineers trust to do their most critical work, including where connectivity is constrained. • Build AI into the product. Design and ship AI-powered product capabilities - model integration, prompt engineering, retrieval-augmented generation (RAG), agentic architectures and the evaluation harnesses and MLOps that keep them reliable in production. You build AI systems, not just use them. • Use AI to build the product. Treat AI-assisted development and agentic tooling as core engineering capability. You raise the bar for how the team builds - measurably faster and better - and set the standard others adopt. • Deploy forward. Embed with Aerospace & Defense customers to deploy, integrate and harden solutions in their environment. You connect IFS to the systems that run their business - ERP, CRM, IoT, telemetry, and legacy and mission systems - and own the solution architecture in real customer context, under real-world constraints. • Own delivery end to end. Design, develop, test, deploy and operate across the full stack in modern general-purpose languages. You own quality through automated testing, manage delivery through CI/CD, and ensure operational reliability in cloud, edge and mobile environments. • Lead as a Principal. Drive technical strategy across product groups, make the architecture and shipping-quality calls others defer, mentor engineers, and lift the AI and forward-deployment practice of the wider organisation. Represent IFS credibly in front of customers and partners. • Anchor to the customer. Ground technical decisions in direct customer evidence and business value. You understand the A&D domain deeply enough to know which problems are worth solving and how AI changes the answer. Qualifications Essential • Demonstrated, hands-on experience leveraging AI for building products - using AI-assisted and agentic development tooling as a core part of your workflow - and for building AI within products - shipping production AI capabilities using ML integration, prompt engineering, RAG, agentic architectures, evaluation and testing, and MLOps. • Mobile engineering: a proven track record building and shipping production mobile applications, with the depth to set the technical direction for a mobile product. Native iOS development experience is strongly preferred given this role's focus on our next-generation aviation-maintenance mobility solution. • Principal-level impact: a proven track record as a recognised technical authority who drives strategy and delivery across multiple teams or product groups, with the depth to operate as a role model in the most complex, large-scope work. • Forward-deployed strength: substantial experience deploying, integrating and operating enterprise software directly in customer environments, including integration with ERP, CRM, IoT and legacy systems, and owning solution architecture in customer context. • Full-lifecycle engineering: strong foundations across the delivery lifecycle - design and development, quality and testing, cloud and DevOps, and security - with proficiency in modern general-purpose programming languages beyond any single domain framework. • Leadership and ownership: end-to-end ownership with a you-build-it, you-run-it mindset, excellent communication with technical and non-technical audiences, and a track record of growing the capability of the engineers and teams around you. Nice to have • Experience working in or with Aerospace & Defense organisations, or on solutions for asset, maintenance, MRO or fleet-readiness management. • Experience with other enterprise asset management (EAM), field service or maintenance-management solutions. • Degree in Computer Science, Software Engineering or a related field, or equivalent practical experience. • Experience of agile delivery and of working with globally distributed teams. Additional Information Flexible paid time off, including sick and holiday Medical, dental, & vision insurance 401K with Company contribution Flexible spending accounts Life insurance and disability benefits Tuition assistance Community involvement and volunteering events We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. VEVRAA Federal Contractor, Equal Opportunity Employer

Job Description Job Description We are a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions. As a leader in SaaS technology for healthcare, we offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With our expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace. Position Summary The Principal Platform Engineer owns the core engineering platform that every product team at RxSense builds on. As a direct report to the VP, Infrastructure Engineering, this role is accountable for the cloud infrastructure, CI/CD systems, developer tooling, and reliability practices that determine how confidently and how fast RxSense engineering can ship. This is a hands-on-keyboard, architect-level role, partnering with software engineers, AI engineers, security, and finance to build a platform that teams choose to build on rather than one they are required to use. Essential Duties and Responsibilities Design, build, and operate the core cloud infrastructure that supports RxSense engineering, including compute, networking, identity and access management, and container orchestration on AWS. Own the CI/CD platform used across engineering teams, including build pipelines, artifact management, environment promotion, progressive rollout, and rollback. Build and maintain the observability stack across the organization, including logging, metrics, distributed tracing, alerting, and the SLIs and SLOs that define reliable service. Drive infrastructure as code practices across the organization and manage the Kubernetes clusters, custom controllers, and operators that back production workloads. Partner with security and compliance to manage secrets, network policy, and access controls appropriate to a regulated healthcare and pharmacy benefits environment. Design self-service developer tooling and platform APIs and set the abstractions that let product and AI engineering teams' provision, deploy, and operate services without handholding. Own incident response tooling, on-call practices, and reliability engineering standards, and lead or support major incident response across the platform. Partner with engineering leadership and finance on infrastructure cost visibility, capacity planning, and cost optimization. Write documentation, runbooks, and clear interfaces so the platform is adoptable by other engineering teams without handholding. Participate in code review and promote collaboration and best practices, including simplicity, automation, sound design patterns, test coverage, and reusability. Work normal day business hours in the Eastern US time zone Education, Experience, and Competencies BS (or higher, e.g., MS or Ph.D.) in Computer Science or a related technical field involving coding, or equivalent technical experience. 8+ years of platform, infrastructure, or site reliability engineering experience, with demonstrated Staff, Principal, or Architect-level scope, such as owning platform architecture end to end or being accountable for critical production systems. We evaluate candidates on the scope and impact of their work rather than years of experience alone. Deep, hands-on experience designing and operating CI/CD pipelines for high-velocity engineering organizations, including artifact management, environment promotion, and progressive rollout. Strong AWS background, comfortable down to the IAM, networking, and container orchestration layers, including production Kubernetes experience. Experience with GitHub and GitHub actions. Proven track record building internal developer platforms or tools that other engineering teams adopted by choice, not by mandate. Hands-on coding fluency in Python, Go, or TypeScript. This is a keyboard role, not an architecture-only role. Comfortable operating in a polyglot environment. The RxSense engineering stack spans Python, .NET, and TypeScript, and you will support services across all three. Practical experience with infrastructure as code (such as Terraform, CloudFormation, or Pulumi) and modern observability tooling (such as Prometheus, New Relic, Grafana, Datadog, or Open Telemetry). Comfortable owning the cost and reliability conversation with both engineering leadership and finance partners. Strong written communication and a bias toward documentation, runbooks, and clear interfaces. Proven analytical thinking and problem-solving skills. Excellent communication skills, both verbal and written. Bonus Qualifications Experience supporting infrastructure for AI or LLM-powered workloads, including GPU provisioning, model serving, or agent runtime infrastructure. Background in healthcare, PBM, pharmacy, or another regulated data environment. Kubernetes operator experience or comfort building custom controllers. FinOps experience, particularly attributing infrastructure spend to features, teams, or business units. Familiarity with distributed systems tooling such as Kafka, gRPC, or Dragonfly and Redis. Experience with Agile development methodologies, preferably both Scrum and Kanban. Experience with code scanning, security, and quality checks as part of the CICD. Salary Range: $190,000 - $235,000 RxSense believes that a diverse workforce is a more talented and productive workforce. As such, we are an Equal Opportunity and Affirmative Action employer. Our recruitment process is free from discriminatory hiring practices and all qualified applicants are considered for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin. Neither will qualified applicants be discriminated against on the basis of disability or protected veteran status. We believe in the strength of the collaboration, creativity and sense of community a diverse workforce brings.

Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.

Job Description Job Description About the Company : Sungrow North America is a leading provider of renewable energy solutions, specializing in the development and manufacturing of photovoltaic inverters and energy storage systems. The company offers a comprehensive range of products and services designed to optimize the performance and efficiency of solar power installations. Sungrow North America aims to provide sustainable and reliable energy solutions to meet the growing demand for clean power and is known for its commitment to innovation, high-quality standards, and exceptional customer service. Security Engineer - Network & Identity: The Security Engineer (Network & Identity) is a hands-on engineering role within the IT team responsible for designing, implementing, securing, and automating Sungrow USA's network security, PKI and certificate management, and identity & access infrastructure across on-premises, cloud, and SaaS environments. This role serves as the technical owner for network security architecture, cryptographic services, certificate lifecycle management, authentication, and access controls. The position focuses on Zero Trust security, network segmentation, certificate-based authentication, and identity protection to reduce organizational risk and enable secure business operations and platform ownership rather than SOC operations, threat monitoring, or incident response. Essential Duties and Responsibilities: Network Security Design, implement, and maintain secure enterprise network architectures across corporate offices, data centers, cloud platforms, and remote workforce environments. Architect network segmentation, Zero Trust access controls, and secure connectivity standards using Fortinet and Zscaler security solutions. Develop and maintain Zero Trust architectures across network, identity, endpoint, application, and cloud environments. Design and administer secure remote access using Zscaler Private Access, VPN technologies, and identity-aware access controls. Manage firewall policies, network security controls, routing security, DNS security, and hybrid-cloud connectivity. Design and support Network Access Control architectures using IEEE 802.1X, RADIUS, and certificate-based authentication. Assess network security posture, develop remediation plans, and drive continuous security improvements. Cryptography, PKI & Certificate Management Own the enterprise PKI, cryptography, and certificate lifecycle management architecture, standards, and governance program. Design and manage certificate-based authentication and machine identity solutions for users, devices, servers, applications, cloud workloads, and network infrastructure across Azure, AWS, and hybrid environments. Implement and maintain certificate lifecycle automation using Microsoft Cloud PKI, Keyfactor, CyberArk Certificate Manager, EJBCA, DigiCert, AppViewX, or comparable platforms. Manage certificate issuance, enrollment, discovery, deployment, monitoring, renewal, revocation, auditing, and compliance across the enterprise. Design and support cryptographic services and certificate-based security controls, including TLS/mTLS, code signing, PKI trust hierarchies, certificate-based authentication, SCEP, PKCS, and machine identities. Establish PKI and cryptographic standards, key management practices, and security controls to support Zero Trust, regulatory compliance, and enterprise security requirements. Troubleshoot and resolve complex certificate, cryptographic, trust chain, authentication, and secure communications issues across enterprise systems and applications. Identity & Access Define authentication and authorization standards for workforce, partner, application, service, and machine identities. Design, implement, and maintain Microsoft Entra ID architecture, tenant governance, and identity security controls. Develop, test, and enforce Conditional Access policies and Zero Trust access controls. Implement and maintain MFA, passwordless authentication, phishing-resistant authentication, and Microsoft Entra ID Protection capabilities. Design and support enterprise SSO and federation integrations using SAML, OAuth 2.0, OpenID Connect, and SCIM. Implement least-privilege and risk-based access models across enterprise platforms. Administer RBAC, administrative separation, Microsoft Entra Privileged Identity Management, and least-privilege access controls. Govern application registrations, service principals, enterprise applications, API permissions, and managed identities. Support B2B collaboration, guest-user governance, external workforce access, and third-party identity integrations. Design and implement security controls across Microsoft Azure and AWS environments. Apply least privilege, RBAC, encryption, secrets management, and secure configuration standards to on-prem and cloud resources. Automate identity provisioning and deprovisioning, access governance, certificate management, configuration validation, and security operations. Create reusable secure-by-default templates and reduce manual administration through automation and orchestration Conduct access reviews, entitlement certifications, and identity governance activities. Education or Desired License and Certificates: Bachelor's degree in Computer Science, Information Technology, Cybersecurity, Engineering, or a related field, or equivalent professional experience. Microsoft Certified: Identity and Access Administrator Associate (SC-300) preferred. Microsoft Certified: Azure Security Engineer Associate (AZ-500) preferred. CCNA, Fortinet, Zscaler, AWS Security, CISSP, CISM, Terraform, or relevant PKI certification preferred Preferred Experience & Qualifications: 5+ years of experience in security engineering, identity & access management (IAM), network security, cloud security, or a related enterprise IT discipline. Hands-on experience with Microsoft Entra ID, including Conditional Access, MFA, SSO, Identity Protection, PIM, RBAC, identity governance, and modern authentication protocols (SAML, OAuth, OpenID Connect, SCIM). Experience designing, implementing, and securing enterprise identity, privileged access, and machine identity solutions across hybrid and multi-cloud environments. Hands-on experience with Fortinet, Zscaler (ZIA/ZPA), Zero Trust architectures, least-privilege access models, and network security controls. Experience designing and operating enterprise PKI, certificate lifecycle management, certificate-based authentication, and machine identity platforms such as Keyfactor, DigiCert, EJBCA, AppViewX, CyberArk Certificate Manager, or similar solutions. Experience securing Azure and AWS environments, including identity, networking, encryption, secrets management, logging, and security monitoring. Experience with PAM and IGA platforms such as CyberArk, Delinea, BeyondTrust, SailPoint, Saviynt, or similar technologies. Experience integrating identity, network, cloud, and security telemetry with SIEM and security operations platforms. Strong automation and Infrastructure as Code skills using PowerShell, Python, Microsoft Graph API, REST APIs, Terraform, or similar technologies. Strong troubleshooting skills across authentication, federation, certificates, PKI, network security, cloud access, application integrations, and enterprise identity services. Knowledge of cybersecurity and compliance frameworks including SOC 2, ISO/IEC 27001, NIST CSF, NIST 800-63, CIS Controls, Zero Trust, and NERC CIP. Competencies: Mandarin fluency preferred but not required. Strong analytical, troubleshooting, and problem-solving skills. Ability to work independently and collaboratively in a fast-paced environment. Excellent communication, stakeholder management, and technical documentation skills. Strong organization, attention to detail, initiative, and ownership. Ability to balance security, reliability, usability, scalability, and business requirements. Proactive approach to automation, standardization, and continuous improvement. Travel 5%-20% Work Location and Status: Full time, Hybrid at any Sungrow USA office in Phoenix, Costa Mesa, or Houston No visa sponsorship Compensation: Compensation commensurate with experience Competitive salary and annual bonus eligibility Comprehensive benefits package including health, dental, vision, and retirement plans Strong personal and company growth opportunities Sungrow is an equal opportunity employer. Due to strong interest in this position, Sungrow will only reach out to those candidates who best meet the requirements. Thank you for your interest in Sungrow.

Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.

Job Description Job Description An active or rein-statable TS/SCI with Polygraph security clearance is REQUIRED. Please do not apply if you currently do not possess this level of clearance. Are you an Principal AI/ML Engineer who is ready for a new challenge that will launch your career to the next level? Tired of being treated like a company drone? Tired of promised adventures during the hiring phase, then dropped off on a remote contract and never seen or heard from the mothership again? Our engineers were certainly tired of the same. At GliaCell our slogan is "We make It happen". We will immerse you in the latest technologies. We will develop and support your own personalized training program to continue your individual growth. We will provide you with work that matters with our mission focused customers, and surround you with a family of brilliant engineers. Culture isn't something you need to talk about if it just exists. If this sounds interesting to you, then we'd like to have a discussion regarding your next adventure! If you want to be a drone, this isn't the place for you. We Make It Happen! GliaCell Technologies focuses on Software & System Engineering in Enterprise and Cyber Security solution spaces. We excel at delivering stable and reliable software solutions using Agile Software Development principles. These provide us the capability to deliver a quick turn-around using interactive applications and the integration of industry standard software stacks. GliaCell's Enterprise capabilities include Full-Stack Application Development, Big Data, Cloud Technologies, Analytics, Machine Learning, AI, and DevOps Containerization. We also provide customer solutions in the areas of CND, CNE, and CNO by providing our customers with assessments and solutions in Threat Mitigation, Vulnerability Exposure, Penetration Testing, Threat Hunting, and Preventing Advanced Persistent Threat. We Offer: Long term job security Competitive salaries & bonus opportunities Challenging work you are passionate about Ability to work with some amazingly talented people Job Description: GliaCell is seeking a Principal AI/ML Engineer on one of our subcontracts. This is a full-time position offering the opportunity to support a U.S. Government customer. The mission is to provide technical expertise that assists in sustaining critical mission-related software and systems to a large government contract. Key Requirements: To be considered for this position you must have the following: U.S. Citizenship 10+ years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required. A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university. 7 additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree. Demonstrated abilities in software engineering and AI/ML model test and evaluation. Works well independently as well as on a team. Strong communication skills. Key Skills: You will design, create, test, and productize AI/ML algorithms to solve business challenges. The AI/ML models you create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. Should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. Needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Need an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. You may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills. Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus. Location: Annapolis Junction, MD / Partial Telework (up to 16 hours per week) may be available for this position based on mission needs/available tasking at the discretion of leadership, after the individual has become fully acclimated to the duties and responsibilities of the position and has completed the necessary telework training. Salary Range: The salary range for this full-time position is $200,000 to $280,000. Our salary ranges are determined by position, level, skills, professional experience, relevant education and certifications. Your recruiter can share more about the specific salary range for your preferred position during the hiring process. Benefits: CareFirst Medical Coverage for Employee and Dependents Guardian Dental and Vision Coverage for Employee and Dependents Up to 25 Days of Paid Time Off Up to 40 hours of PTO Carryover 11 Federal Government Holidays Work From Home Opportunities 401K Company Contribution, Fully Vested Day 1 Discretionary, Certification, and Sign-On Bonus Potential Employee Referral Bonus Program Annual Professional Development 100% Premium Covered for Life & Disability Insurances Additional Voluntary Life Insurance Coverage Available Employee Assistance Program Travel Protection Program Financial Planning Assistance Bereavement and Jury Duty Leave Monthly Team and Family Events Technology Budget Global Entry Annual Swag Budget Learn more about GliaCell Technologies: To apply for this position, respond to this job posting and attach an updated resume for us to review. GliaCell Technologies, LLC is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status. Powered by JazzHR cDeBOm5dlB

Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html

About Zaden Technologies, Inc. Join Zaden Technologies on our mission to simplify the delivery and improve the utility of software products for our customers. At Zaden, we believe that our employees are our greatest assets. We hire the right candidates with the right skill sets who fit our culture of customer obsession, innovation, and continuous learning. We are our customer's biggest advocate and we are looking for like-minded individuals who encompass these same ideals. It is important to us to offer you competitive pay and comprehensive benefits with opportunities that match your life and propel your career! Zaden Technologies is seeking an experienced Principal Windows Systems Administrator to lead the design, implementation, and management of enterprise Windows infrastructure and Azure Virtual Desktop environments. This role will be critical in supporting our DevSecOps initiatives and ensuring secure, scalable, and efficient system operations for defense and space systems. The ideal candidate will bring deep expertise in Windows system administration, Azure cloud infrastructure, and security hardening while working in a fast-paced environment supporting mission-critical applications. Role Responsibilities: Design, deploy, and manage Azure Virtual Desktop (AVD) environments including host pools, session hosts, and user profiles to support distributed workforce requirements Administer and optimize Group Policy Objects (GPOs) across enterprise domains to enforce security policies, user configurations, and system settings Conduct comprehensive security and vulnerability scanning using industry-standard tools, and remediate identified vulnerabilities in accordance with compliance requirements Manage Windows Update deployment strategies, including WSUS administration, patch testing, and enterprise-wide update rollouts with minimal operational disruption Oversee some Linux virtual machine environments within hybrid infrastructure, ensuring proper integration with Windows systems and maintaining cross-platform operational excellence Design and troubleshoot complex networking configurations including VPNs, subnets, routing, firewalls, and load balancers in both on-premises and Azure environments Architect and maintain Azure infrastructure components including virtual networks, storage accounts, resource groups, and identity management solutions Lead Security Technical Implementation Guide (STIG) compliance efforts by implementing and validating security baselines across a mixed fleet Provide technical leadership and mentorship to junior system administrators and contribute to the development of best practices and standard operating procedures Collaborate with DevSecOps teams to integrate infrastructure-as-code practices and automation workflows for system provisioning and configuration management Required Qualifications: U.S. Citizenship and active secret security clearance Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent practical experience 7+ years of hands-on experience in Windows system administration in enterprise environments Advanced expertise in Azure Virtual Desktop deployment, management, and optimization Demonstrated proficiency in Group Policy creation, management, and troubleshooting across complex Active Directory environments Strong experience with security and vulnerability scanning tools (e.g., Nessus, Qualys, Rapid7) and remediation workflows Proven track record managing Windows Server Update Services (WSUS) or equivalent patch management solutions In-depth knowledge of networking protocols, architectures, and troubleshooting methodologies (TCP/IP, DNS, DHCP, VPN) Solid understanding of Azure cloud services, Azure networking (VNets, NSGs, Application Gateway), and infrastructure management Hands-on experience implementing and validating STIG compliance on Windows and Linux systems Preferred Qualifications: Active Top Secret clearance with ability to obtain TS/SCI Microsoft certifications such as Azure Administrator Associate, Azure Solutions Architect Expert, or Windows Server Hybrid Administrator Associate Proficiency in basic Linux system administration tasks. Experience with Infrastructure-as-Code tools (Terraform, ARM templates, Bicep) Knowledge of containerization technologies (Docker, Kubernetes) and their integration with Windows infrastructure Familiarity with DevSecOps practices, CI/CD pipelines, and automation frameworks Experience with PowerShell scripting and automation for system administration tasks Background supporting Department of Defense (DoD) or federal government IT environments Experience with monitoring and observability tools (Azure Monitor, Log Analytics, Prometheus, Grafana) Knowledge of identity and access management solutions (Azure AD, ADFS, MFA implementation) Experience with disaster recovery planning and implementation in cloud environments What we offer: Robust startup environment with a variety of projects to work on Growth paths and endless opportunities to learn and develop Paid holidays Employer contributions toward 401k Performance-based bonus and profit-sharing 50% coverage of health insurance for employees and their dependents The pay range for this role is: 130,000 - 170,000 USD per year(Huntsville, AL) Compensation details: 00 Yearly Salary PIda68e5b312f7-2570