58 jobs found

Job Description Job Description Description: Company Description: ASG is a Minority- and Woman-Owned, Physician-Owned small business with over 15 years of experience in federal government contracting. We deliver a wide range of technology services, including software development, mobile apps, AI/ML, analytics, data science, big data, DevSecOps, digital transformation, cloud, and cybersecurity. ASG is CMMI Level 3 certified and holds ISO 9001:2015, 20000-1:2018, and 27001:2022 certifications . Job Description: ASG is seeking an experienced Security Lead to own the Program security posture, compliance artifacts, and coordination with Program Security Oversight leadership. This role shares leadership of the security team with a Co-Lead and directs the work of the Information Security Specialist team, ensuring compliance documentation, vulnerability management, and ATO artifacts are complete, current, and defensible in a complex federal healthcare IT environment. The ideal candidate brings deep federal cybersecurity experience, a track record of leading security teams, and the judgment to represent the program's security posture to executive and government stakeholders. What You Will Do: Own Task 3 security management deliverables, including compliance documentation, risk register maintenance, and coordination with the Program Security Oversight Leader. Direct and coordinate the Information Security Specialist team, including workload distribution and quality oversight of security deliverables, alongside the Sr. Information Security Specialist (Co-Lead). Support Authorization to Operate (ATO) maintenance, continuous Assessment & Authorization (A&A) activities, and FISMA/FedRAMP compliance documentation for Client-managed systems. Author and review security documentation, including System Security Plans (SSPs), Risk Assessments, and Security Impact Analyses (SIA), prior to submission to Program Security Oversight leadership. Oversee vulnerability scanning, remediation tracking, and security findings reporting across enterprise tools; review results and recommended corrective actions from the Information Security Specialist team. Serve as the primary security point of contact with Program Security Oversight Leadership, and maintain collaborative relationships with federal ISSOs, CSPs (e.g., AWS, Azure), system owners, and vendors. Coordinate with the Tools Management team through the combined Security/Tools scrum cadence. Track and maintain the centralized Security Risk Register, map vulnerabilities to POA&Ms, and support FISMA/FedRAMP compliance efforts across the program. Provide guidance and privacy/security insight to Agile teams across projects, and support Privacy and Security Compliance through all stages of the systems development lifecycle (SDLC). Work within Client system repositories such as CFACTS and BOX. Oversee declared game day events, ensuring after-action reports and other required game day artifacts are completed by the security team. Develop and maintain standard operating procedures (SOPs) for repeatable security processes across the team. Perform additional duties as assigned by the Program Security Oversight Leader. Perform additional duties assigned. Requirements: What We Need : Bachelor's degree or higher in Computer Science, Information Technology, Cybersecurity, Systems Engineering, or a related field (or equivalent professional experience). 8+ years of information security experience in a federal or enterprise environment, including team leadership. Experience with FISMA compliance, ATO processes, and continuous Assessment & Authorization (A working understanding of NIST 800-53/37. Experience co-leading or managing a multi-person security team, including workload distribution and quality oversight of deliverables. Working knowledge of vulnerability scanning and compliance/POA&M platforms, Jira, Confluence, and FISMA/ATO documentation standards and processes. Ability to obtain and maintain Program EUA access and required Public Trust clearance. Strong communication skills and ability to coordinate across multi-disciplinary teams and government stakeholders. Even Better: Prior Program or HHS security program experience strongly preferred. Relevant security certification (CISSP, CISM, CEH, CCNA Security, or Security+). Familiarity with federal control tracking systems (e.g., CFACTS and BOX). Working knowledge of cloud environments (AWS, Azure) and associated security controls. Exposure to pen testing, application security, and CDN security services (e.g., Akamai). Experience providing security and privacy input within Agile development environments. Knowledge about emerging industry or technology trends such as Artificial Intelligence (AI) frameworks. Clearance Requirement: Ability to obtain and maintain public trust background investigation/clearance per client requirements. Additional Information: At ASG, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or status as a protected veteran. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to . We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible. Perks: At ASG, we want you to be well and thrive. Our benefits package includes: Healthcare Benefits Life Disability Paid Time Off 401k Matching Employee Referral Bonus Education Assistance Learning and Development resources EOE, including Disability/Veterans

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 Description: AI/ML Technical Lead CASCOM ESD Enterprise Analytics/AI Program Schedule: Full-Time / 1.0 FTE Work Arrangement: Primarily Remote with Required Travel to Fort Lee, VA Clearance: Active Final Secret Required The Opportunity We're looking for an AI/ML Technical Lead who still builds. This position requires hands-on technical leadership across AI/ML solutions using CASCOM, GCSS-Army, SAP, and other Army data. The successful candidate must be capable of personally coding, evaluating, deploying, and sustaining models-not simply directing an AI strategy or managing data science teams. Potential use cases include GenAI/OpenAI, RAG, Copilot, document extraction, anomaly detection, equipment-readiness and maintenance forecasting, fleet automation, recommendation capabilities, and supply forecasting. What You'll Do Lead selection and technical refinement of three baseline AI/ML use cases. Define mission questions, data requirements, technical baselines, performance metrics, and acceptance criteria. Perform hands-on data exploration and feature engineering. Develop, train, validate, and comparatively evaluate machine-learning models. Conduct error analysis and document model limitations. Develop selected GenAI, RAG, forecasting, anomaly-detection, or recommendation capabilities. Work with GCSS-Army SMEs to validate business rules and interpret model results. Partner with Azure Data/MLOps engineering resources to package, deploy, version, monitor, and sustain models. Establish appropriate human-review processes for model outputs affecting operational decisions. Develop model cards, evaluation results, release documentation, known limitations, and retraining criteria. Integrate analytical outputs into dashboards, Power Apps, APIs, or other operational solutions. Participate in demonstrations and production-readiness reviews. .Requirements: Must-Have Qualifications Active final Secret clearance. 7+ years of data science, machine learning, advanced analytics, or applied AI experience. 4+ years developing machine-learning solutions. Hands-on production AI/ML development experience. Strong Python and SQL skills. Experience delivering at least three substantive models or AI capabilities. At least one model personally taken from requirements through production or operational deployment. Experience with Azure AI/ML services or a comparable cloud environment. Ability to explain model evaluation, deployment, monitoring, and retraining. Strong experience with pandas, NumPy, scikit-learn, and at least one major ML/deep-learning framework. Experience with at least two of the following: Forecasting Anomaly detection Classification Recommendation engines Optimization Document extraction NLP, RAG, or GenAI Experience establishing measurable model-performance criteria. Experience with feature engineering, training, validation/test data, error analysis, explainability, and model documentation. Bachelor's degree in computer science, data science, statistics, mathematics, operations research, engineering, or related discipline, or equivalent specialized experience. Strongly Preferred Azure Machine Learning, Azure OpenAI, Azure AI Search, Microsoft Copilot, or comparable Azure AI services. Defense logistics, maintenance, readiness, fleet, supply-chain, acquisition, property, or financial analytics. GCSS-Army, SAP ECC, ERP, or maintenance-system data. Government-cloud or classified deployment experience. Model monitoring, drift detection, bias testing, red teaming, or human-in-the-loop validation. Integration of model outputs with Power BI, Power Apps, APIs, or operational applications. Experience presenting technical findings to operational users and senior leadership. About Xtreme Solutions XSI is a leading provider of information technology and professional services known for outstanding service delivery in a wide range of professional services engagements around the country. Team XSI continually meets and exceeds customer expectations. We are passionate about our work and making a difference. Our vision is to be the best professional services management company for both our customers and our employees. We need employees that share this vision. Our remarkable employees are the key to our company's incredible success. XSI promotes a work environment of trust, integrity, respect, continual improvement, customer satisfaction, and business success. We strive to provide a competitive salary and benefits, an engaging and rewarding work environment, and training and development opportunities. Equal Employment Opportunity Xtreme Solutions, Inc. is an Equal Opportunity Employer and federal contractor. All qualified applicants will receive consideration for employment without discrimination based on any status protected by applicable federal, state, or local law.As a federal contractor, Xtreme Solutions, Inc. takes affirmative action to employ and advance in employment qualified individuals with disabilities and protected veterans. We are committed to providing equal employment opportunities throughout all aspects of employment, including recruitment, hiring, promotion, compensation, training, and other terms and conditions of employment. Equal Opportunity Employer Individuals with Disabilities Protected Veterans

Job Description Job Description What Impact You'll Have GRVTY is seeking a motivated and experienced Data Manager to provide technical and managerial leadership over our overhead satellite imagery preprocessing operations. The ideal candidate is an experienced data operations leader with a passion for solving complex pipeline challenges, ensuring data integrity, and delivering mission-critical results in support of the DoW and Intelligence Community. This role serves as the primary communication interface between the customer and the team, translating requirements into successful execution across the full data operations lifecycle. What You'll be Owning Oversee and manage data, databases, and pipelines across the full data acquisition, curation, and preprocessing lifecycle, ensuring compliance with specified requirements and priorities Conduct regular Quality Control (QC) of data holdings to: Manage the data operations pipeline to include: Apply engineering best practices to optimize data pipeline efficiency and performance across all sensor modalities including: EO, FMV, HMI, and SAR Lead and manage team members by providing: Ensure data dictionaries, Entity Relationship Diagrams (ERDs), software comments, and documentation are regularly maintained and updated Serve as the primary customer communication interface to relay tasks and requirements and ensure successful work execution What You Must Have Active TS/SCI Clearance with the ability to obtain a CI/Poly People management experience, including: Team lead or project lead roles Independently initiating and driving projects to completion Strategic problem solver with excellent communication skills Experience in quantitative analysis and data operations, to include: Developing visualizations and processing complex data to create data-driven insights Data manipulation and ETL procedures Working knowledge of SQL and NoSQL database technologies Demonstrated experience managing databases and data pipelines Experience working with cloud architectures Experience working with large, complex geospatial data files and formats What Would be Nice to Have Experience using Agile/SAFe methodologies Experience with NGA enterprise technology systems such as NGA CORE and MLOps GEOINT Professional Certification - Fundamentals (F) Experience working with AI/ML technologies applied to geospatial data Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. The pay range for this position is: $160,000 - $190,000 Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. Virginia Pay Range $160,000-$190,000 USD Why Choose GRVTY The toughest national security challenges demand vision and ingenuity, not just resources. We deliver mission and technical expertise to outpace our adversaries. We're purpose-built to tackle the most entrenched, systemic national security issues around the world. We partner with our customers to help them overcome challenges in every corner of technology and defense-including the ones still being explored. Our growing capabilities create complementary advantages, giving on-the-ground operations the edge they need to succeed. We muster everything we have to answer every challenge presented, every day of our lives. At GRVTY, we believe that when our employees thrive, our company thrives. That's why we offer a comprehensive and competitive benefits package designed to support your well-being, growth, and work-life balance. • Robust health plan including medical, dental, and vision • Health Savings Account with company contribution • Annual Paid Time Off and Paid Holidays • Paid Parental Leave • 401k with generous company match • Training and Development Opportunities • Award Programs • Variety of Company Sponsored Events EEO Statement GRVTY, is an Equal Opportunity Employer. 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 and will not be discriminated against on the basis of disability. Anyone requiring reasonable accommodations should email or call with requested details. A member of the HR team will respond to your request within 2 business days. Know Your Rights: Workplace Discrimination is Illegal (eeoc.gov) Please review our current job openings and apply for the positions you believe may be a fit. If you are not an immediate fit, we will also keep your resume in our database for future opportunities.

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).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences 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 Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning 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, 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).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences 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 Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning 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, 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 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).

Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) 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. Capital One is open to hiring a Remote Employee for this opportunity 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 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 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact 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. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer 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).

Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) 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. Capital One is open to hiring a Remote Employee for this opportunity 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 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 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact 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. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer 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).

Job Description Job Description Job description At , we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve. We hold ourselves accountable by providing space for authenticity, growth, and equity for everyone. has embraced a hybrid work model to provide flexibility and support work-life integration. Travel is part of this position, but frequency may vary based on client, team, and individual circumstances. Relocation assistance is not available for this position. About the Role The Principal AI Engineer sits at the intersection of software engineering, data science, platform architecture, and AI governance. You will be the technical owner of how AI/ML engineering is designed, built, governed, and shipped across a portfolio of products serving all of domains. This is a hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, building internal developer tooling, leading security and governance design, and mentoring engineering teams. Your success is measured by team-level outcomes - scalable patterns that outlast your direct involvement. What You'll Do AI Productization & Platform Engineering Design and own the firm's AI productization & governance playbook, covering service patterns, security/compliance standards, model evaluation rubrics, and production-readiness criteria. Build and maintain reusable internal tooling, including AI service scaffolding, evaluation and monitoring tooling, and data infrastructure - designed for team adoption without ongoing hand-holding. Establish AI agent governance policies covering agent permissions, code execution controls, access to internal systems, and human-in-the-loop enforcement. Partner with Security, Legal, and Compliance to define SOC2/ISO-aligned AI controls, vendor DPA requirements, and prompt data classification policies. Establish standardized deployment patterns using containerization, infrastructure-as-code, and CI/CD pipeline templates reusable across teams. Developer Experience & Engineering Excellence Champion AI-assisted development practices across the engineering org, including LLM-integrated development workflows, test-driven development patterns, and reusable tooling standards that scale across teams. Codify modern software development standards (CI/CD, DevOps, testing, delivery quality) referenced by multiple teams as a baseline for new or re-platformed products. Mentor engineers and tech leads with observable improvement in delivery consistency, design quality, and production readiness rigor. Cross-Functional Leadership & Stakeholder Influence Serve as the go-to technical authority on AI/ML, platform architecture, and engineering practices - regularly consulted by senior stakeholders at the design and strategy stages. Bridge technical and non-technical stakeholders, translating complex architectural decisions, AI risk topics, and platform tradeoffs into clear, actionable guidance. What You'll Need Required 15+ years in software engineering, data science, or a closely related technical field. Bachelor's degree or higher in Computer Science, Engineering, or a related field. Deep expertise in AI/ML frameworks and the Python ecosystem, with hands-on experience deploying models to public cloud infrastructure. Demonstrated experience designing and operating multi-tenant AI services and LLM integrations in production. Proven track record leading microservices architecture - decomposing monoliths, defining service contracts, and operationalizing CI/CD for distributed systems. Strong hands-on command of containerization (Docker), infrastructure-as-code (Terraform), and modern DevOps practices. Substantive experience with AI/LLM security - including prompt injection, data boundary enforcement, model supply chain risk, and AI-specific threat modeling. Strong problem-solving skills, especially in building governance frameworks, evaluation rubrics, and reusable platform patterns at scale. Excellent written and verbal communication skills in English; ability to translate complex technical topics to diverse audiences, including executive stakeholders. Experience with Agile methodologies and cross-functional product team collaboration. Preferred / Additional Qualifications Experience applying AI/ML in business consulting, advisory, or professional services contexts. Familiarity with AI service interface and gateway design patterns, including emerging AI integration protocols. Contributions to open-source AI/ML projects, publications, or active involvement in technical communities. Advanced certifications in AI, deep learning, cloud architecture, or security (e.g., AWS/GCP/Azure ML, CISSP). Experience defining AI compliance controls for SOC2, ISO 27001, or TISAX frameworks. Demonstrated enthusiasm for developer education - writing internal guides, running workshops, or building internal tooling communities. Proficiency in additional languages is a plus (Go, Typescript) Demonstrated ability and enthusiasm to mentor and uplift junior team members or peers Willingness to work outside of normal business hours, and in particular as unique projects/needs arise. Ability to work full time in an office and remote environment; physically able to sit/stand at a computer and work in front of a computer screen for significant portions of the workday Must become familiar with, and promote and abide by, our Core Values as defined by the and foster an inclusive environment with people at all levels of an organization

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 We are building a team that develops AI agents to solve hard security problems and you will be tackling the hardest ones. This is a hands-on, senior IC role. You will architect, build, and ship agentic AI systems that operate autonomously within security environments, while also driving the technical direction and standards for how these systems are built, tested, and secured. This is not a management role and not a pure research role. You will write code, ship systems, and get your hands dirty but you will be working on problems where there is no playbook yet. You will define the approach, build the proof of concept, harden it for production, and write the technical guidance others follow. Responsibilities: Architect and build AI agent systems for security operations autonomous detection, investigation, response, threat hunting, vulnerability analysis, and risk assessment Tackle the novel, high-complexity problems: adversarial robustness of agent systems, secure agent-to-agent communication, guardrails for autonomous decision-making in high-stakes security contexts Develop frameworks, tooling, and patterns for building secure and reliable agentic AI systems then use them yourself Conduct original research and experimentation on agentic AI applied to offensive and defensive security, translating findings into working code Build proof-of-concept exploits and adversarial tests against agentic AI systems to identify failure modes and inform defensive design Develop and publish technical guidance and policy for agentic AI security grounded in systems you have built and broken Independently author security position papers on emerging technologies strategic, high-level documents that frame organizational thinking on new threat domains and drive downstream policy and technical guidance Serve as a subject matter expert and key driver of the AI Cybersecurity Maturity program, spanning application security, training, AI controls and infrastructure, AI discovery and inventory, operations and incident response, and policy and procedure development Integrate LLMs, custom models, and security tooling (SIEM, EDR, SOAR, cloud platforms, vulnerability scanners) into agent architectures Evaluate and adopt emerging AI capabilities (new models, frameworks, techniques) and determine their applicability to security problems Set technical direction for agent development practices, including evaluation frameworks, testing methodologies, and deployment patterns Mentor and elevate other engineers on the team through code review, design guidance, and technical leadership Qualifications Required: Bachelor's Degree with 9 years' experience; Master's Degree with 8 years' experience; PhD with 4 years' experience. Respective years of experience in cybersecurity, security engineering, or security research with substantial hands-on technical depth Strong software engineering skills you ship production systems, not just prototypes. Python required; additional languages a plus Deep expertise in at least two of: security operations, application security, threat intelligence, vulnerability research, detection engineering, offensive security, cloud security Demonstrated experience building AI agents and AI/ML-powered security tools or automation that operated at scale Hands-on experience with agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot, Aider, or similar) as part of your daily development workflow you build with agents, not just build agents Track record of original technical work published research, open-source tooling, conference presentations, or equivalent evidence of independent technical contribution Ability to work at the intersection of security and AI: you understand both the security implications of AI systems and how to apply AI to security problems Experience developing technical standards, frameworks, or guidance that others adopted Strong written and verbal communication you can explain complex technical concepts to both engineers and senior leadership, and you can write strategically about emerging technology risks at a level that shapes organizational direction Preferred: Experience with agent orchestration and autonomous systems (custom frameworks, LangChain, AutoGen, MCP, or similar) Background in adversarial ML, AI red teaming, or AI safety Familiarity with security compliance frameworks (NIST, ISO 27001, SOX) and how they apply to AI systems Published work (Black Hat, DEF CON, OWASP, academic journals, or equivalent venues) Experience in regulated industries (financial services, healthcare, critical infrastructure, government/defense) Contributions to open-source security projects OWASP, MITRE ATT&CK, or similar framework expertise applied in production environments Security clearance eligibility (not required) 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

Job Description Job Description Overview We're looking for a Senior Principal AI Engineer to provide hands-on technical leadership across complex, production-grade AI systems. This role is for a builder-architect-someone who has repeatedly taken AI systems from idea to production, understands where they fail at scale, and knows how to unblock teams to move faster without sacrificing outcomes. This is not a pure strategy or people-management role. It is a deeply technical builder role with organizational impact. You will define technical direction by writing code, designing systems, and helping the organization stay in builder mode as complexity and scale increase. What You'll Do Architect and build end-to-end AI systems including LLM orchestration, retrieval layers, agentic workflows, and structured reasoning systems Lead the design of multi-agent and tool-calling systems that operate reliably in production Establish and evolve architecture patterns for scalable, cost-aware, and observable AI applications Drive technical decisions across data modeling, AI pipelines, infrastructure, and APIs Define best practices for evaluation, monitoring, and governance of AI systems in production Mentor senior engineers through design reviews, code reviews, and system-level debugging Translate ambiguous business and domain problems into clear technical strategies Stay ahead of emerging AI techniques and integrate what matters-without chasing hype Core Skills & Experience 12+ years of software engineering experience, with deep hands-on experience building AI/ML systems in production Strong proficiency in TypeScript, React, Go, Python and modern AI frameworks Extensive experience with LLMs, including RAG, tool use, prompt systems, and agentic architectures Proven ability to design and ship large-scale AI systems that run reliably in real-world environments Strong architectural judgment across data systems, AI models, infrastructure, and application layers Deep understanding of AI failure modes: hallucination, drift, brittleness, latency, and cost blowups Excellent communication skills-able to explain technical tradeoffs to both technical and non-technical audiences Track record of shipping systems end-to-end, not just prototypes or research work Builder Mentality (This Is Core to the Role) We are explicitly looking for builders. By " builder, " we mean an operating mode, not a title. Builders: Bias toward systems that solve user needs, not perfect abstractions Move comfortably from ambiguity first draft iteration production Optimize for learning velocity and customer impact, not theoretical completeness Are willing to build the entire arc of a system to surface real constraints early Treat quality as something you earn through iteration, not something you gate progress with Understand that the last 10-20% of a system-integration, edge cases, UX, usability, reliability-is where real work happens At the Principal level, being a builder also means: Helping the organization stay in builder mode as it grows Collapsing unnecessary complexity rather than introducing more process Knowing when architectural rigor matters, and when it is premature Pulling promising work across the finish line instead of waiting for "perfect readiness" Modeling speed, ownership, and clarity for other senior engineers Your impact is measured not only by what you build, but by how much faster and more effectively others can build because of you. Preferred Experience (Domain-Flexible Specialties) Knowledge graph architecture, ontology design, or semantic modeling in complex domains Graph databases, graph query languages, or graph ML techniques Hybrid systems combining structured reasoning with LLM-based approaches Entity resolution, schema alignment, or knowledge fusion at scale AI systems requiring explainability, auditability, or lineage tracking Experience building AI systems in regulated or high-stakes domains (finance, healthcare, legal, government) MLOps, evaluation infrastructure, or long-running AI services operating at scale What You'll Love Owning the technical direction of real AI systems that make it into production Solving hard, ambiguous problems where architecture and execution matter equally Leading through hands-on building, not layers of process Working in an environment that values shipping, learning, and iteration over perfection Having the latitude to shape both systems and how teams build them About Us We are an AI-first company, and we mean that literally. AI is not a feature we bolt on. It's not a marketing layer. It's not a roadmap experiment. It is the foundation of how we design, build, and operate. We are building systems where machines do what machines do best: pattern recognition, synthesis, analysis at scale. As well as what humans do what humans do best: judgment, context, trust, and accountability. That means rethinking workflows from the ground up. Not "how do we add AI to this process?" but "how should this process exist in a machine-augmented world?" We care deeply about shipping real systems that work in production. In regulated environments. With real customers. At scale. If you're excited to help invent the next way software is built and deployed, and to do it alongside a team of deeply pragmatic, AI-obsessed builders, we'd love to talk. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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 Agile Defense At Agile Defense we know that action defines the outcome and new challenges require new solutions. That's why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next. Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility-leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation's vital interests. Requisition #: 1853 Job Title: Network Security Engineer Location: Suitland, MD Clearance Level: Public Trust Job Description Agile Defense is seeking a Senior Network Security Engineer to support the agency as it moves away from its legacy ForeScout CounterACT NAC/NAM system and adopts Cisco Identity Services Engine (ISE) as the new access control platform. The engineer will help configure and manage Cisco ISE across the environment, handling AAA services, wired and wireless 802.1X authentication, device administration, and posture checks for users and devices. This role also supports the agency's modernization work by improving authentication processes, updating ISE policies, and strengthening identity-based access controls. The engineer will troubleshoot access issues, refine policy designs, and help ensure users and devices can connect securely and reliably as the organization completes its transition from ForeScout to Cisco ISE. Troubleshoot and resolve Cisco ISE issues across RADIUS, TACACS+, 802.1X, device administration, and endpoint authentication. Deploy, configure, and maintain Cisco ISE running on two clustered Cisco SNS 3715 appliances, ensuring high availability and consistent policy enforcement. Support the agency's migration from ForeScout CounterACT to Cisco ISE, including reviewing legacy ForeScout policies, device groups, and access rules and mapping them into ISE policy sets. Provide general wireless support, including basic troubleshooting, wireless access workflows, and coordination with wireless infrastructure teams. Configure and support Cisco ISE integrations with Cisco 9800 WLCs, including guest/registration portals, wireless onboarding, and policy driven access control. Integrate and maintain Cisco ISE with Active Directory (AD) and LDAP, including identity lookups, group based authorization, and directory based authentication workflows. Deploy, configure, and maintain Cisco ISE components, including: o Policy Sets, Authorization Profiles, and Authentication Rules o TACACS+ device administration o 802.1X for wired and wireless networks o Profiling, posture, and compliance policies o Certificate based authentication and PKI integrations Monitor security events using ISE logs, syslog, and performing root cause analysis for authentication and access issues. Manage identity integrations, enforce security policies, and tune configurations to support Zero Trust and improve user experience. Perform routine health checks, upgrades, migrations, and document changes through SOPs, engineering designs, and implementation procedures. Work closely with engineering, operations, and compliance teams while mentoring junior staff and contributing to knowledge sharing efforts. Education and Background Bachelor's degree in Information Technology, Cybersecurity, or a related field. Years of Experience Eight (8) years of experience in a large government organization with five (5) years in technical leadership, including four (4) years implementing and troubleshooting Cisco ISE. Four (4) years of experience supporting identity centric or Zero Trust architectures with strong knowledge of segmentation, certificate management, and endpoint posture controls. Required Skills Senior Network Security Engineer responsible for designing, configuring, monitoring, and troubleshooting Cisco ISE as a NAC/NAM platform, including TACACS+/RADIUS services, device administration policies, and wired/wireless 802.1X authentication. Eight (8) years of experience in a large government organization with five (5) years in technical leadership, including four (4) years implementing and troubleshooting Cisco ISE with expertise in: o Authentication and authorization policies (RADIUS/TACACS+) o 802.1X/EAP methods for wireless and wired access o Device profiling, posture checks, and endpoint compliance o Certificate based authentication (EAP TLS) and PKI integration o AAA integrations for switches, appliances, firewalls, and wireless controllers Experience working with Cisco ISE deployed on Cisco SNS 3715 appliances, preferably in a two node clustered, high availability setup. Understanding of ForeScout CounterACT, including legacy NAC/NAM policies, device classification, and access workflows, to support the migration to Cisco ISE Experience providing general wireless network support, including basic troubleshooting, controller interactions, and wireless access workflows. Hands on experience integrating Cisco ISE with Active Directory (AD) and LDAP, including identity lookups, group based policy decisions, and directory based authentication. Experience supporting Cisco ISE integrations with Cisco 9800 Wireless LAN Controllers, including guest/registration page redirection and wireless onboarding. Experience migrating legacy NAC, RADIUS, or device authentication systems into Cisco ISE while aligning with Zero Trust principles. Solid understanding of telecommunications, network security, and Zero Trust best practices. Strong communication skills with the ability to explain Cisco ISE, NAC/NAM, and AAA concepts to both technical and non technical audiences. Preferred Skills Preferred certifications: Cisco CCNP Security, Cisco ISE Specialist, or similar identity/security certifications. Working Conditions On-site 5 days a week in Suitland, Maryland In addition, Agile Defense invests in its employees beyond just compensation. Agile's benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, short-term and long-term Disability, Retirement and Learning and Development opportunities as well as other optional benefit elections. Our Core Values Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together. What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are. Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do. Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated. Honest - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support. Humble - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task. Hungry - Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges. Hustle - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success. Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Head of Product Design will define and lead the user experience vision for Hivemind, Shield AI's autonomy development platform. This role is responsible for transforming complex autonomy, robotics, AI, and developer workflows into intuitive experiences that enable engineers, operators, and organizations to develop and deploy resilient autonomy at scale. A major focus of this role will be shaping the next generation of AI-native and agent-driven workflows across the autonomy lifecycle. As Hivemind evolves from traditional software tooling toward AI-assisted autonomy development, simulation, evaluation, deployment, and operations, this leader will help invent entirely new ways for users to collaborate with AI systems, agents, and foundation-model-powered tools. The ideal candidate has deep experience designing AI products, developer platforms, or complex technical systems and can translate emerging AI capabilities into workflows that dramatically improve user productivity and outcomes. This is a highly hands-on role as this leader will manage a team of elite designers. During the first 6-12 months, most of the time will be spent conducting user research, designing experiences, prototyping concepts, facilitating product discovery, and partnering directly with Product and Engineering teams to define the future of autonomy development. What you'll do:User Research & Product Discovery Lead customer research efforts across product development, customer engagement, and solutions teams to identify pain points, workflows, unmet needs, and product opportunities. Establish scalable mechanisms for gathering, synthesizing, and communicating user insights throughout the product development lifecycle. Translate customer and operational feedback into actionable product recommendations, requirements, and design initiatives. Product Design & User Experience Design end-to-end workflows across autonomy development, simulation, testing, analysis, deployment, and operations. Create intuitive experiences for highly technical users including autonomy engineers, software developers, operators, and mission planners. Simplify complex system architectures, data flows, infrastructure tooling, and AI workflows into understandable user experiences. Own the end-to-end experience of the product including training, documentation, tutorials, and overall workflows - help our users get the most of the product. Strategic Product Leadership Partner closely with Product Managers to shape product vision, roadmap priorities, and go-to-market strategies. Drive alignment across Product, Engineering, Design, and Executive Leadership through compelling narratives, prototypes, and visual storytelling. Advocate for user-centered decision making in a highly technical and engineering-driven environment. Design Practice, Systems & Organizational Scale Establish and evolve design standards, design systems, UX principles, and product design best practices across Shield AI. Raise the quality bar for product design, usability, consistency, and customer experience. Grow the product design function by mentoring a small team of designers, shaping design culture, and staying actively involved in critical design work. Champion design wins and impact across the organization, highlighting the important role design plays in delivering successful products. AI-Native Product Design & Agentic Workflows Define the future user experience for AI-assisted autonomy development, simulation, testing, deployment, and operational workflows. Design human-AI collaboration models that enable users to effectively leverage AI agents, copilots, and foundation-model-powered systems. Partner with Product, AI Research, and Engineering teams to create new interaction patterns for agent orchestration, autonomy generation, scenario creation, test generation, and mission planning. Develop frameworks for trust, transparency, explainability, and human oversight within AI-assisted workflows. Help establish industry-leading design patterns for Physical AI development platforms and agent-driven software systems. Required qualifications: 10+ years of experience in Product Design, UX Design, Human Factors, or related fields. Proven track record designing and shipping complex technical products, developer tools, platforms, infrastructure software, data-dense applications, or enterprise systems. Deep technical fluency and ability to effectively collaborate with senior engineering leaders on architecture, technical constraints, and software development workflows. Strong experience conducting user research and translating insights into product strategy and design solutions. Proven ability to influence product direction and organizational decisions without direct authority. Strong understanding of AI-powered product experiences, including conversational interfaces, human-in-the-loop workflows, AI-assisted decision making, and agent-based systems. Experience defining new user experiences in ambiguous technology spaces where industry standards and workflows are still emerging. Experience building and retaining high-performing design teams. Strong portfolio showcasing both strategic thinking and hands-on design execution. Preferred qualifications: Background designing developer platforms, SDKs, cloud infrastructure products, DevOps tooling, or engineering productivity tools. Direct work on AI/ML platforms, MLOps workflows, foundation-model-enabled products, copilots, or agentic systems. Familiarity with autonomy, robotics, simulation, digital twins, mission systems, physical AI, or related development workflows including testing, evaluation, deployment, and operations. Portfolio examples involving command-and-control systems, mission-planning interfaces, operational dashboards, or real-time decision-support tools. Ability to design across integrated hardware/software systems. Domain exposure to defense technology, aerospace, robotics, or other regulated, mission-critical, or high-consequence operational environments. San Diego, CA and Washington, D.C. pay range: $230,000 - $350,000 San Mateo, CA pay range: $280,000 - $420,000 Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Head of Product Design will define and lead the user experience vision for Hivemind, Shield AI's autonomy development platform. This role is responsible for transforming complex autonomy, robotics, AI, and developer workflows into intuitive experiences that enable engineers, operators, and organizations to develop and deploy resilient autonomy at scale. A major focus of this role will be shaping the next generation of AI-native and agent-driven workflows across the autonomy lifecycle. As Hivemind evolves from traditional software tooling toward AI-assisted autonomy development, simulation, evaluation, deployment, and operations, this leader will help invent entirely new ways for users to collaborate with AI systems, agents, and foundation-model-powered tools. The ideal candidate has deep experience designing AI products, developer platforms, or complex technical systems and can translate emerging AI capabilities into workflows that dramatically improve user productivity and outcomes. This is a highly hands-on role as this leader will manage a team of elite designers. During the first 6-12 months, most of the time will be spent conducting user research, designing experiences, prototyping concepts, facilitating product discovery, and partnering directly with Product and Engineering teams to define the future of autonomy development. What you'll do:User Research & Product Discovery Lead customer research efforts across product development, customer engagement, and solutions teams to identify pain points, workflows, unmet needs, and product opportunities. Establish scalable mechanisms for gathering, synthesizing, and communicating user insights throughout the product development lifecycle. Translate customer and operational feedback into actionable product recommendations, requirements, and design initiatives. Product Design & User Experience Design end-to-end workflows across autonomy development, simulation, testing, analysis, deployment, and operations. Create intuitive experiences for highly technical users including autonomy engineers, software developers, operators, and mission planners. Simplify complex system architectures, data flows, infrastructure tooling, and AI workflows into understandable user experiences. Own the end-to-end experience of the product including training, documentation, tutorials, and overall workflows - help our users get the most of the product. Strategic Product Leadership Partner closely with Product Managers to shape product vision, roadmap priorities, and go-to-market strategies. Drive alignment across Product, Engineering, Design, and Executive Leadership through compelling narratives, prototypes, and visual storytelling. Advocate for user-centered decision making in a highly technical and engineering-driven environment. Design Practice, Systems & Organizational Scale Establish and evolve design standards, design systems, UX principles, and product design best practices across Shield AI. Raise the quality bar for product design, usability, consistency, and customer experience. Grow the product design function by mentoring a small team of designers, shaping design culture, and staying actively involved in critical design work. Champion design wins and impact across the organization, highlighting the important role design plays in delivering successful products. AI-Native Product Design & Agentic Workflows Define the future user experience for AI-assisted autonomy development, simulation, testing, deployment, and operational workflows. Design human-AI collaboration models that enable users to effectively leverage AI agents, copilots, and foundation-model-powered systems. Partner with Product, AI Research, and Engineering teams to create new interaction patterns for agent orchestration, autonomy generation, scenario creation, test generation, and mission planning. Develop frameworks for trust, transparency, explainability, and human oversight within AI-assisted workflows. Help establish industry-leading design patterns for Physical AI development platforms and agent-driven software systems. Required qualifications: 10+ years of experience in Product Design, UX Design, Human Factors, or related fields. Proven track record designing and shipping complex technical products, developer tools, platforms, infrastructure software, data-dense applications, or enterprise systems. Deep technical fluency and ability to effectively collaborate with senior engineering leaders on architecture, technical constraints, and software development workflows. Strong experience conducting user research and translating insights into product strategy and design solutions. Proven ability to influence product direction and organizational decisions without direct authority. Strong understanding of AI-powered product experiences, including conversational interfaces, human-in-the-loop workflows, AI-assisted decision making, and agent-based systems. Experience defining new user experiences in ambiguous technology spaces where industry standards and workflows are still emerging. Experience building and retaining high-performing design teams. Strong portfolio showcasing both strategic thinking and hands-on design execution. Preferred qualifications: Background designing developer platforms, SDKs, cloud infrastructure products, DevOps tooling, or engineering productivity tools. Direct work on AI/ML platforms, MLOps workflows, foundation-model-enabled products, copilots, or agentic systems. Familiarity with autonomy, robotics, simulation, digital twins, mission systems, physical AI, or related development workflows including testing, evaluation, deployment, and operations. Portfolio examples involving command-and-control systems, mission-planning interfaces, operational dashboards, or real-time decision-support tools. Ability to design across integrated hardware/software systems. Domain exposure to defense technology, aerospace, robotics, or other regulated, mission-critical, or high-consequence operational environments. San Diego, CA and Washington, D.C. pay range: $230,000 - $350,000 San Mateo, CA pay range: $280,000 - $420,000 Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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 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