Senior AI/ML Data Engineer

Lead the design and delivery of enterprise-scale AI/ML data infrastructure enabling vector search, RAG, and agentic capabilities.

Responsibilities

• Architect, build, and maintain enterprise-scale data platforms for vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems, and large language model applications.
• Define and implement controls for data quality, lineage, source attribution, and prompt and context traceability, including explainability and evaluation of AI outputs.
• Drive architectural decisions for AI-enabled data infrastructure, balancing performance, scalability, security, reliability, maintainability, and cost.
• Collaborate with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity, and Software Engineers to translate AI requirements into production-grade capabilities.
• Translate complex AI, machine learning, and data architecture concepts into 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 duplicated 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 across the organization.
• Evaluate emerging AI technologies, including vector database platforms, retrieval frameworks, and engineering approaches to strengthen organizational AI capabilities.

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 RAG architectures
• Experience with CI/CD pipelines, orchestration platforms, infrastructure automation, and observability tooling

Technology Focus

• Python, SQL
• Azure, AWS, Google Cloud
• Vector databases, embedding pipelines
• Retrieval-Augmented Generation (RAG)
• CI/CD pipelines, orchestration platforms, observability tooling

Education & Experience

• Minimum experience: 20 years
• Bachelor’s degree (may be substituted for 4 years of experience) or Master’s Degree (may be substituted for 6 years of e)

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 working in complex enterprise environments with 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 experience delivering complex technical solutions from strategic requirements through operational deployment while balancing schedule, performance, capability, and cost objectives
• 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

Work Model

• Location: Washington, DC (hybrid)
• Minimum onsite: 2-3 days onsite

Additional Location Details

• Washington, DC or Reston, VA

Contingencies

• Contingent upon program award

Compensation

• Annual salary range: USD 242,000 - 305,000

Benefits

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

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