AI/ML Data Engineer at internal in US-VA-Reston

Job description

• BigBear.ai is seeking an AI/ML Data Engineer to architect, build, and operate enterprise-scale AI data platforms enabling vector databases, semantic search, Retrieval-Augmented Generation (RAG), and agentic AI systems. This role will establish the technical and governance foundations for production AI, including data lineage, source attribution, prompt/context traceability, explainability, and evaluation in mission environments .

Responsibilities

• Architect and evolve an enterprise AI data platform enabling vector search, semantic retrieval, RAG, and agentic workflows.
• Design cloud-native, distributed data systems optimized for performance, scale, security, reliability, and cost.
• Data quality, lineage, provenance/source attribution
• Prompt + context traceability and auditability
• Explainability and evaluation of AI outputs
• Partner across Data Science, ML Engineering, Software, Cybersecurity, and Enterprise Architecture to translate AI requirements into production-grade capabilities.
• Lead architectural decisions; drive reuse across organizations and eliminate duplication. Implement monitoring/observability/alerting and operational excellence best practices.
• Mentor engineers and raise engineering standards (design reviews, coding standards, CI/CD discipline).
• Evaluate emerging AI technologies (vector DBs, retrieval frameworks, evaluation stacks) and recommend adoption paths.

Requirements

• Active Top Secret / SCI with Polygraph is mandatory.
• Bachelor's in CS/Engineering/Math/Data Science (or equivalent experience).
• 20+ years in software engineering, data engineering, distributed systems, cloud architecture, or AI/ML platform development.
• Proven delivery of enterprise-scale AI/ML / GenAI / agentic systems.
• Track record of architecting production cloud-native data platforms supporting AI workloads.
• Experience in complex enterprises with security constraints, dependencies, governance, and competing priorities.
• Deep experience with data pipelines supporting ML models, vector databases, semantic search, and GenAI apps.
• End-to-end delivery ownership from strategic requirements through operational deployment.
• Expert in Python and SQL; strong software engineering practices.
• Deep experience with AWS, Azure, or GCP data/AI platforms.
• Strong understanding of distributed systems, cloud-native architecture, MLOps, platform engineering.
• Hands-on with vector DBs, embeddings, retrieval systems, RAG.
• Experience with CI/CD, orchestration, IaC/automation, observability.
• Exceptional written/verbal communication.
• Able to translate complex AI/data architecture concepts into mission impact, risk, and tradeoffs.
• Demonstrated ability to influence and drive consensus across stakeholders.
• Prior roles as Principal Engineer, Lead Data Engineer, Solutions Architect, Technical Lead.
• Built/operated enterprise vector search/knowledge management / RAG / LLM platforms.
• Large-scale distributed processing (e.g., Spark/Flink/Beam—whatever aligns to your stack).
• Experience supporting AI adoption in government/defense/intelligence or highly regulated environments.
• Familiarity with AI governance, evaluation frameworks, explainability, responsible AI.

Skills

Required

• Expert in Python and SQL
• Strong software engineering practices
• Exceptional written/verbal communication