City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
04/08/2026
Full time
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
04/08/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
04/05/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
