20 jobs found

The National Radio Astronomy Observatory (NRAO) seeks a Software Engineer Group Lead to guide development of online systems supporting world-class radio telescopes. You will lead a small team building scalable, reliable web and backend services for proposal submission, data access, and observing tools. Responsibilities include technical leadership, architecture decisions, code reviews, and mentoring engineers while remaining hands-on. Collaborate closely with scientists, data engineers, and IT to deliver secure, high-performance software that enables groundbreaking astronomical research and global scientific collaboration. Responsibilities Lead design and development of online web and backend services for telescope user workflows Provide technical direction, architecture decisions, and code reviews Mentor and coach software engineers, fostering best engineering practices Collaborate with scientists and stakeholders to translate research needs into software Ensure performance, reliability, security, and scalability of production systems Oversee agile planning, task prioritization, and delivery of releases Maintain hands-on involvement in coding, testing, and troubleshooting Integrate applications with scientific data pipelines and observatory systems Required Skills Software architecture Web application development Backend APIs (REST/Graph QL) Python or Java Java Script/Type Script Cloud or virtualized environments Relational/No SQL databases Linux systems Agile/Scrum leadership CI/CD pipelines

What Makes a Honda, is Who makes a Honda Honda has a clear vision for the future, and it's a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of "power" that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize "the joy and freedom of mobility" by developing new technologies and an innovative approach to achieve a "zero environmental footprint." We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team. If your goals and values align with Honda's, we want you to join our team to Bring the Future! Job Purpose The Data and Solution Architect is responsible for defining, governing, and advancing the enterprise data architecture required to enable scalable, trusted, and responsible AI solutions in the AI Hub. This role ensures that data platforms, models, standards, and semantic structures are designed to support AI/ML, Generative AI, Agentic AI, experimentation (POCs), and production deployment, while aligning with enterprise data governance, security, and compliance requirements. Key Accountabilities AI Ready Data Architecture & Design Lead the design of logical, physical, and semantic data architectures to support AI, advanced analytics, GenAI and Agentic AI use cases Define AI ready data models, feature oriented structures, and analytics ready data assets aligned to enterprise data platforms Ensure architectural alignment between data platforms, AI tooling, and MLOps pipelines Support design and governance of the Foundry Ontology layer as the enterprise semantic backbone for AI use cases Data Standards, Governance & Semantics Work closely with Data Architecture and Governance teams, define and enforce data standards, metadata practices, naming conventions, and master/reference data patterns for AI use cases Establish and maintain semantic consistency (business definitions, critical data elements, feature definitions) to enable explainable and reusable AI Partner with Data Governance, Legal, and Compliance teams to ensure responsible and compliant AI data usage AI Use Case Enablement & POC Support Architect data flows and patterns supporting AI POCs, experimentation environments, and sandbox platforms Guide data sourcing, profiling, and readiness activities for AI Data Scientists, Data and AI Engineers Own the data architecture stage-gate process across POC, expanded pilot, and production phases; define and maintain AI-readiness scorecards to assess data asset maturity at each stage Data Platform, Integration and Solution Architecture Architect integrations across source systems, data platforms, analytics tools, and AI services Evaluate and onboard new data sources and technologies to meet evolving AI requirements Define reference architecture and architectural guardrails for cloud, hybrid, and global deployments Lead/support solution architecture development for projects/products, where necessary Collaboration, Review & Enablement Serve as a data and solution architecture authority for AI related initiatives and design reviews Mentor junior architects, data engineers and provide architectural guidance to delivery teams Contribute to AI Hub (COE), communities of practice, standards bodies, and architecture review forums Qualifications, Experience, and Skills Bachelor's degree in Computer Science, Information Systems, Data Engineering/ Data Science, or related field 8+ years of experience in data architecture, solution architecture, enterprise data platforms, or analytics architecture Demonstrated experience supporting AI/ML, advanced analytics, or data driven product initiatives Experience operating in federated governance or hub and spoke operating models Experience with data profiling and data quality management Workstyle This is an onsite job. One remote workday per week, may be possible with prior departmental approval. Visa sponsorship issues This position is not eligible for work visa sponsorship What differentiates Honda and makes us an employer of choice? Total Rewards: Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.) Regional Bonus (when applicable) Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included) Industry-leading Benefit Plans (Medical, Dental, Vision, Rx) Paid time off, including vacation, holidays, shutdown Company Paid Short-Term and Long-Term Disability 401K Plan with company match + additional contribution Relocation assistance (if eligible) Career Growth: Advancement Opportunities Career Mobility Education Reimbursement for Continued learning Training and Development Programs Additional Offerings: Lifestyle Account Childcare Reimbursement Account Elder Care Support Tuition Assistance & Student Loan Repayment Wellbeing Program Community Service and Engagement Programs Product Programs Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

Job Description Job Description THAAD System Operator OverviewSimTech, Inc., recognized as one of the 2026 Best Places for Working Parents, is seeking a THAAD System Operator to join our dynamic and diverse corporate team in Huntsville, AL. SimTech offers a market leading compensation package with excellent benefits, work/life balance, outstanding retirement plan, career advancement and much more. The THAAD System Operator will support test events by collaborating with team members, operating assigned systems and simulation workstations, and applying component-specific setup and testing procedures. Responsibilities Collaboration within a team environment while emphasizing individual contributions to effectively complete a test event, which can span from a few weeks to several months. Ability to operate one of many workstations, on an as needed basis, to include, but not limited to: THAAD Fire Control and Communications (TFCC), THAAD Radar (AN/TPY-2 TM), Simulation-Over-Live-Driver (SOLD), Common Data Link Interface-Module (CDLI-M) and the Network Systems Integration and Test Environment (NSITE) workstation. Will be required to learn individual component specifics as required to conduct tests, such as component initialization parameters and specific test operating procedures. Perform data collection and post-test processing of data. Off-hours and travel may be required. Other responsibilities as assigned. Minimum Qualifications & Education RequirementsBachelor 's degree from an accredited university, with 3 years of relevant experience; or may substitute with High school diploma and 6 years of relevant work experience. Excellent troubleshooting, analytical, and problem-solving skills. Good verbal and written communications skills. Some Unix/Linux experience and knowledge of Missile Defense Systems is a plus. U.S. Citizenship with an Active Secret security clearance or ability to obtain/maintain security clearance required. Physical DescriptionEmployees in these positions will function in a general office/cubicle setting environment, and laboratory/testing setting using standard office equipment and various electronic testing equipment, including a computer, telephone, printers, video equipment, computer software and testing equipment. Will interact in a general office setting environment with various personnel; participate in meetings and contribute to team success; deliver timely results and produce reports; receive and communicate information; may include telework. May function in a specialized laboratory/testing environment using electronic testing equipment, computer software and complex systems. May move and test equipment of various weights. Laboratory environment may require use of protective equipment (PPE) including but not limited to safety glasses and protective hearing and footwear. May be expected to work varying shifts and hours to ensure successful operation of activities in the organization due to business demands; travel occasionally for assigned work. About SimTech, Inc.SimTech's mission is to be the most reliable and cost-effective provider of Signature Models, Simulations, Hardware, Software, Cyber solutions, and Test & Evaluation services. Established in 1983 by a team of experienced scientists and engineers, SimTech has a long history of delivering high-technology defense-oriented solutions. The company has been recognized as a "Best Place to Work" in 2020 and 2021, and as a "Best Place for Working Parents" in by the Huntsville/Madison County Chamber of Commerce. SimTech offers an industry-leading comprehensive compensation and benefits package. Be a part of over 43+ years of excellence-join our team today! To learn more about our exceptional team and employee benefits, contact SimTech HR or visit for more information. Equal Employment Opportunity and Affirmative Action EmployerSimTech, Inc. is an Equal Opportunity/Affirmative Action Employer. SimTech, Inc. is a committed EOE/Vet/Disabled employer. Simulation Technologies, Inc. (SimTech) is an Equal Employment Opportunity employer and provides reasonable accommodation for qualified individuals with disabilities and disabled veterans in its job application procedures. If you have any difficulty using our online system and you need an accommodation due to a disability, you may use the following email address, and/or phone number ) to contact us about your interest in employment with SimTech. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, citizenship, ancestry, marital status, protected veteran status, disability status or any other status protected by federal, state, or local law. SimTech participates in E-Verify. Job Posted by ApplicantPro

Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance

Job Description Job Description Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Robotics AI Engineer - Calibration, Localization, and Mapping About Field AI Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact. Learn more at . About the Job Field AI is seeking passionate scientists and engineers to play a vital role in the development of advanced geometric robot perception algorithms. As a member of our Calibration, Localization, and Mapping (CLAM) team, you will work with a team of high-focused individuals in a fast-paced environment to deliver production-quality code within our calibration, localization, and mapping subsystems. You will work with a variety of different sensing modalities and help streamline our calibration pipeline and/or develop environment-agnostic localization and mapping algorithms for our downstream autonomy modules. The specific project and work that you will be doing will depend on your specific skill set and area of interest. The ideal candidate will not only have a deep theoretical understanding of modern calibration, localization, and mapping algorithms, but also the practical skills to deliver high-quality and maintainable code on a small, focused team in a fast-paced environment. What You'll Get To Do Design and implement state-of-the-art calibration, localization, and mapping algorithms for our autonomous quadrupeds and humanoids Develop various tools and metrics to continuously validate and benchmark the performance of our various subsystems Write clean, efficient, and maintainable code in C++ and Python Collaborate with cross-functional teams to integrate and deploy your algorithms into real-world systems What You Have Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field, with expertise in calibration, localization, and/or 3D mapping Strong mathematical foundation in linear algebra, probability theory, numerical optimization, 3D geometry, Lie theory, and 3D kinematics Strong theoretical understanding and practical experience with different linear and non-linear state estimation frameworks for sensor fusion Familiarity with state-of-the-art LiDAR-inertial odometry and SLAM algorithms Familiarity with state-of-the-art visual-inertial odometry and SLAM algorithms Experience with sensor calibration (intrinsics and extrinsics) and time synchronization Strong proficiency in C++ and Python and modern best practices, with the ability to write maintainable and efficient code Strong understanding how ROS works and experience with designing, building, and deploying your own nodes into a complex robotic system Strong problem-solving skills, attention to detail, and being able to work independently while managing multiple priorities Strong work ethic, highly self-motivated, and excellent written and verbal communication skills The Extras That Set You Apart Publications and/or patents in calibration, state estimation, odometry, and/or SLAM Experience working with noisy sensor measurements and designing outlier-resilient algorithms Experience working with computationally constrained platforms and designing efficient, real-time algorithms with low computational complexity Experience with other sensing modalities (e.g., radar, doppler-LiDAR, GPS, etc.) Experience with modern version control and project management tools Field AI Onsite Work Philosophy: Field AI believes in-person collaboration is essential for tackling complex challenges. This is a fully onsite role based in our Irvine, CA office, with flexible hours to support work-life balance. We are committed to fostering a diverse and inclusive workplace and encourage candidates from all backgrounds to apply. Compensation and Benefits Our salary range is between ($70,000 - $300,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option. Why Join Field AI? We are solving one of the world's most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment. You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals. Be Part of the Next Robotics Revolution To tackle such ambitious challenges, we need a team as unique as our vision - innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We're seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators. We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates. Join us, shape the future, and be part of a fun, close-knit team on an exciting journey! We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status. 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 About Medical Guardian: Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. Mission: This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian. The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption. Role Summary: We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness. This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications. This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership. Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured. A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes. Key Responsibilities: Hands-On Data Engineering and Platform Development Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture. Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data. Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams. Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems. Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning. Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline. Real-Time Streaming, IoT Telemetry, and Operational Data Services Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds. Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns. Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads. Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases. Define reliability, latency, quality, observability, and supportability expectations for production streaming systems. Databricks, Lakehouse, and Data Platform Architecture Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design. Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design. Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership. Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture. Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact. Stakeholder Shaping and Cross-Functional Partnership Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like. Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans. Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value? Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests. Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders. Team Management and Principal-Level Technical Leadership Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability. Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making. Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives. Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security. Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed. Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions. ML/AI, Analytics, and GenAI Enablement Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops. Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation. Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases. Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on. Governance, Data Quality, Security, and Production Operations Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data. Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring. Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs. Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation. Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness. Required Qualifications: 10+ years of professional experience in data engineering . click apply for full job details

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 HRL Laboratories, an IBM company, pioneers the next frontiers of physical and information science. Delivering transformative technologies in automotive, aerospace and defense, HRL advances the critical missions of its customers to help them remove limitations and create competitive advantage. HRL then transitions the work back to customers - ready for real-world application. For more than 70 years, HRL's rich portfolio of scientific discoveries and engineering innovations continues to build on each other - often in unexpected, profound and far-reaching ways. As a private company owned by IBM, HRL prioritizes purpose over profit, significantly advancing the state of the art. HRL Laboratories advances critical structural and functional materials and semiconductor devices that enable precision navigation, quantum technologies and extreme-environment performance. With expertise from design through deployment, we deliver scalable, high-performance solutions that transform our customers' missions. Our work leverages digital manufacturing and scalable microfabrication techniques to meet tomorrow's toughest challenges. Position Summary: • Design, build, test, and analyze optical, optoelectronic, and photonic experiments for quantum communications systems and platforms • Collaborate with multidisciplinary R&D teams to advance quantum communications technologies Key Responsibilities: • Perform critical engineering and R&D under the supervision of staff scientists for next generation quantum photonic/electronic devices and deployable optical payloads • Design, model, setup, and test of free-space and/fiber optic experiments and design and fabrication of state-of-the-art semiconductor devices • Improve processes, perform measurements, collect, summarize, and analyze data, present and discuss data with other scientists • Work with mechanical and electrical teams to troubleshoot complex systems Required Qualifications: • Bachelor's or master's in physics, Electrical Engineering, Optical Engineering, or related discipline • Some prior experience working with any of microfabrication, free-space/fiber optics, electronics, computer-controlled experiments obtain through coursework, independent study, or other internships • Strong desire to learn and be trained in scientific laboratory techniques and experimental procedures • Must be able to work well in a dynamic team environment and possess excellent communication skills • Working knowledge of free space optics, fiber optics, mechanical CAD software, and rf-test equipment (spectrum analyzers, power meters, oscilloscopes) Physical Requirements: • Must be able to work safely in an optical testing laboratory • Excellent verbal and written communication skills and organization skills are required • Must be proficient in use of computers, engineering workstations, and complex electronic equipment Special Requirements: • US Citizenship with the ability to obtain and maintain a US Government security clearance Compensation and Benefits: Pay Range : $81,800- 98,900 Our salary ranges are determined by role, level, and location (California). The range displayed on each job posting reflects the target range for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process. Benefits: HRL offers a generous and very competitive total compensation and benefits package. Our Regular/Full Time benefits include medical, dental, vision, life insurance, 401K match, gym facilities, PTO, Sick time, upward mobility, and an exciting and challenging work environment. For more information about our company benefit offerings please visit: Non-Discrimination and Equal Employment Opportunities (U.S.) Don't meet every single requirement? Studies have shown that some people are less likely to apply to jobs unless they meet every single desired qualification. At HRL, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. We are proud to be an EEO/AA employer M/F/D/V. We maintain a drug-free workplace and perform pre-employment substance abuse testing. If you would like more information about Equal Employment Opportunity as an applicant under the law, please go to Employees & Job Applicants u007C U.S. Equal Employment Opportunity Commission For our privacy policy please visit: 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.

Senior. Distinguished 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. In this role, you will: 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree 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, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished 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 . click apply for full job details

Req Id: 206 Job Title: Program Chief Engineer Location: Herndon, VA - Herndon, VA 20171 US (Primary) Job Description: Fibertek seeks a Program Chief Engineer to provide technical leadership for one or more programs in Fibertek's diverse technology portfolio of laser systems & technologies, lidar sensors, and laser communications systems. Fibertek is a recognized industry leader in delivering critical laser-based technologies that enable next generation missions for military and space applications. As a Program Chief Engineer you will provide technical leadership to advanced development programs through systematic engineering and delivery of first-of-kind systems for initial demonstration or qualification on operational airborne or space missions. This role will be the last line of authority for major program-level technical decisions and the first line of communication to customers and mission partners regarding Fibertek's technical approach and progress toward delivery. Fibertek plans to hire multiple engineers for this position to lead programs across a rapidly growing portfolio, including fast-paced developments of spaceflight technologies and instruments. Program opportunities include: Space LADAR: 2-year development and delivery of multiple compact space situational awareness LADAR instruments, with expected production transition to follow Earth-sensing LIDAR Technologies: 2-year development and delivery of laser and beam control subsystems for NASA spaceflight missions Space LADAR: Leadership of 2-year Assembly Integration and Test (AI&T) for the second-unit delivery of an existing proven LADAR transceiver design Fiber Laser Systems and Technologies: multiple fiber laser and amplifier programs for space and airborne systems Essential Job Duties: The Program Chief Engineer will have high-impact responsibilities that include: Technical leadership of select programs resulting in the successful delivery of laser-based systems and technologies that demonstrate new operational capabilities critical to national interests in defense and space exploration Responsibility for verified compliance with all technical performance, environmental, and functional requirements Support the Program Manager and company leadership to develop execution plans that are achievable, measurable, and reflect company and mission priorities Representation of Fibertek serving as the main point of contact to customers and mission partners on system design and technical progress Leadership and mentoring of a diverse and extremely talented program team of engineers and scientists with expertise across related disciplines including laser physics, electro-optics, systems engineering, electronics, signal processing, and others Leadership of teams through major technical decisions and analyses that have a high impact on program success, including architecture development, design trades, anomaly resolution & troubleshooting, and system verification methods Guidance and review of teams preparing for program milestone reviews including Preliminary and Critical Design Reviews, Test Readiness Reviews, Delivery and Acceptance Reviews, and/or other technical milestones Provide input on the development and adoption of engineering tools and best-practices that enhance the efficiency and operational success of engineering development programs and incorporate design features that enable predictable manufacturing following initial development and demonstration Job Requirements: Experience and Expertise Required: Master's or PhD degree in a relevant engineering or applied-science field Specific experience engineering, qualifying, and delivering electro-optical systems for US space and/or military applications Technical expertise in one or more of the following skill areas: laser systems, LIDAR sensors, optical communication systems, optical systems engineering, and/or qualification of systems and technologies for aerospace and defense Familiarity with industry-standard engineering tools in one or more disciplines: requirements tracking and verification, model-based systems engineering, circuit design and simulation, thermal and structural analysis, optical design and tolerance analysis, and/or others Exceptional written and verbal communication skills with the ability to concisely articulate how technical solutions and maturation plans are innovative, technically credible, and responsive to current and emerging mission needs US Citizenship and eligibility to obtain a US Security Clearance Salary Range: The annual base salary range for this position is $200,000-$250,000. This range reflects the compensation Fibertek reasonably expects to offer for this role. Placement within the range will depend on factors such as the scope and responsibilities of the position, the candidate's experience, education and training, key skills, and relevant market and business considerations. PI7dd8bc9c530e-3214

Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.

Senior. Distinguished 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. In this role, you will: 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. 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 enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree 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, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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. Distinguished AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished 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 . click apply for full job details

Distinguished 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. Why this Role Matters: We are building an enterprise Generative AI Platform that lets dozens of product teams compose powerful, safe and explainable AI capabilities - without wrestling with model minutiae or infra plumbing. You will design the agentic workflow framework, shared services such as memory, guardrails, vector search, SDKs and blueprints that translate foundation model power into production grade applications used by millions of users across multiple lines of businesses. In this role, you will: 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns Experience as a Staff-plus or Distinguished IC engineer influencing 50+ engineers and C-suite stakeholders K8s mastery (multi-region clusters, sericie mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished 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. . click apply for full job details

Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.

The National Radio Astronomy Observatory seeks a Systems Engineer to support world-class radio telescopes in a mission-driven, research-focused environment. You will design, integrate, and maintain complex systems connecting instrumentation, control, and data networks for astronomy and astrophysics. Responsibilities include requirements analysis, system design, implementation, testing, and troubleshooting. You will collaborate with scientists and engineers worldwide, contribute to high-reliability operations, create thorough documentation, and continuously improve performance, scalability, and security of observatory systems. Responsibilities Design, implement, and maintain radio telescope control and monitoring systems Integrate hardware, software, and networking components for observatory operations Troubleshoot and resolve complex systems and performance issues Collaborate with astronomers and engineers to translate scientific needs into technical solutions Develop and maintain system documentation, procedures, and configuration records Support reliability, security, and scalability of mission-critical infrastructure Participate in on-call or scheduled maintenance windows for system upgrades Required Skills Systems engineering Linux administration Network engineering Scripting (Python/Bash) Systems integration Requirements analysis Systems architecture design Monitoring and observability tools Configuration management Cybersecurity fundamentals

GXM Technologies LLC seeks a Senior Digital Engineer specializing in MBSE and Data Science to support mission-critical defense and intelligence programs. In this role, you will architect and maintain SysML-based models, integrate geospatial, C4ISR, AI/ML, and cyber capabilities, and build advanced analytics to inform complex system decisions. You will collaborate with cross-functional teams, drive digital engineering best practices, mentor junior staff, and contribute to R&D efforts, delivering secure, scalable solutions that directly support U.S. national security objectives. Responsibilities Lead development of MBSE models to support complex defense and intelligence systems Design and implement data science and analytics solutions for mission-focused applications Integrate geospatial, C4 ISR, AI/ML, and cyber capabilities into digital engineering workflows Collaborate with cross-functional teams to define system architecture and requirements Develop prototypes and tools to support advanced R&D and systems integration Ensure model traceability, verification, and validation across the system lifecycle Optimize data pipelines, feature engineering, and model performance for production use Document designs, analyses, and technical decisions for stakeholders and customers Mentor junior engineers and data scientists in MBSE and analytics best practices Support proposal efforts and technical presentations to government clients Required Skills Model-Based Systems Engineering (MBSE) Sys ML or similar modeling languages Systems architecture and requirements engineering Data science and statistical analysis Python or similar programming languages Machine learning frameworks (e.g., Tensor Flow, Py Torch, scikit-learn) Geospatial data and tools (e.g., GIS, geospatial libraries) C4 ISR or defense/intelligence systems domain knowledge Data pipeline and ETL development Cloud or containerized environments for analytics