Senior AI/ML Data Engineer

Lead enterprise AI data platform engineering to support Boeing’s Agentic AI transformation across vector search, RAG, and large language model applications.

Responsibilities

• Architect, build, and maintain enterprise-scale data platforms for vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems, and LLM applications.
• Define and implement controls for data quality, data lineage, source attribution, and prompt and context traceability.
• Drive explainability and evaluation practices for AI system outputs, including measurement and improvement loops.
• Own architectural decision-making for AI-supporting data infrastructure, balancing performance, scalability, security, reliability, maintainability, and cost.
• Collaborate with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity teams, and Software Engineers to deliver production-grade capabilities from AI requirements.
• Translate complex AI, machine learning, and data architecture topics into 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 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 capability.

Requirements

• Active TS/SCI with CI Polygraph
• Expert proficiency in Python, SQL, and 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

Technologies

• Python
• SQL
• Azure
• AWS
• Google Cloud
• Vector databases
• Embedding pipelines
• Retrieval-Augmented Generation (RAG)
• CI/CD pipelines
• Orchestration platforms
• Observability tooling

Benefits

• Generous company match to your 401(k)
• Industry-leading tuition assistance program that pays your institution directly
• Fertility, adoption, and surrogacy benefits
• Up to $10,000 gift match when you support your favorite nonprofit organizations

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 in complex enterprise environments managing security, infrastructure, technology 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 through 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 efforts within large government, defense, intelligence, or highly regulated organizations

Location and Work Model

• Washington, DC (hybrid)
• Reston, VA
• Hybrid work authorized: minimum 2-3 days onsite

Additional Information

• Contingent upon program award
• Summary pay range: $242,000 - $305,000 per year
• Minimum experience: 20 years
• Education: Bachelor’s degree may be substituted for 4 years of experience; Master’s degree may be substituted for 6 years of experience
• Application privacy policy: https://www.boeing.com/careers/privacy-statement