AI/ML Data Engineer

Overview

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.

What you will do

What You’ll Do

• 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.

Establish and implement controls for:

• 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.

What you should have

• 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.

Technical:

• 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.

Leadership & Communication:

• 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.

What we'd like you to have

• 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.

About BigBear.ai

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.

BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.