Senior AI/ML Data Engineer

Boeing Intelligence & Analytics is building enterprise-scale capabilities for modern AI use cases, and this role supports that work in a hybrid environment based in Washington, DC (or Reston, VA). If you enjoy leading technical direction, improving reliability through governance and observability, and translating complex AI concepts into operational outcomes for leadership, this Senior AI/ML Data Engineer position is designed for you.

This position focuses on designing and implementing data platforms that enable vector search, Retrieval-Augmented Generation (RAG), LLM applications, and emerging Agentic AI capabilities. You will set architectural direction for AI-supporting infrastructure while partnering across engineering, security, and AI teams to deliver production-grade systems.

Responsibilities

• Architect, build, and maintain enterprise-scale data platforms for vector databases, semantic search, RAG, Agentic AI systems, and large language model applications.
• Define and implement controls for data quality, data lineage, source attribution, and prompt and context traceability, including explainability and evaluation of AI outputs.
• Lead architectural decision-making to balance performance, scalability, security, reliability, maintainability, and cost for AI-supporting data infrastructure.
• Collaborate with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity, and Software Engineers to convert AI requirements into production capabilities.
• Communicate technical AI, machine learning, and data architecture concepts as clear operational impacts, risks, opportunities, and implementation considerations for senior leadership.
• Coordinate across multiple organizations to align AI initiatives, maximize reuse of enterprise capabilities, and reduce duplication of effort.
• Implement monitoring, observability, and alerting to support reliability, performance, and continuous platform improvement.
• Provide technical leadership and mentorship, promoting engineering best practices and innovation.
• Evaluate emerging AI technologies, including vector database platforms, retrieval frameworks, and engineering approaches to strengthen organizational AI capabilities.

Requirements

• 20 years of experience in AI/ML, Data, or Software Engineering roles, or a highly related field, with similar scope and responsibilities.
• A Bachelor’s degree may substitute for 4 years of experience, and a Master’s degree may substitute for 6 years of experience.
• Active TS/SCI with CI Polygraph.
• Expert proficiency in Python and SQL, plus modern software engineering practices.
• Deep experience with Azure, AWS, or Google Cloud data and AI platforms.
• Strong understanding of distributed systems, cloud-native architectures, MLOps, and AI platform engineering.
• Experience implementing vector databases, embedding pipelines, retrieval systems, and Retrieval-Augmented Generation (RAG) architectures.
• Experience with CI/CD pipelines, orchestration platforms, infrastructure automation, and observability tooling.

Desired Qualifications

• Proven experience designing and delivering enterprise-scale AI, machine learning, generative AI, or Agentic AI solutions.
• Demonstrated success architecting and implementing production cloud-native data systems for advanced analytics and AI workloads.
• Proven experience delivering in complex enterprise environments with security, infrastructure dependencies, governance requirements, and competing priorities.
• Extensive experience designing data pipelines for machine learning models, vector databases, semantic search, and generative AI applications.
• Proven ability to deliver complex technical solutions from strategic requirements to operational deployment while balancing schedule, performance, capability, and cost.
• Experience building and operating enterprise-scale vector search, RAG, knowledge management, and LLM-based platforms.
• Experience supporting AI adoption in large government, defense, intelligence, or highly regulated organizations.

Technology Focus

Python, SQL, Azure, AWS, Google Cloud, MLOps, vector databases, embedding pipelines, Retrieval-Augmented Generation (RAG), CI/CD pipelines, observability tooling

Work Model

• Hybrid authorized with minimum 2-3 days onsite.
• Work location: Washington, DC or Reston, VA.

Compensation and Contingencies

• Annual salary range: USD 242,000 - 305,000.
• Contingent upon program award.