Senior AI/ML Engineer — Forward Deployed Engineer

Work Location: Washington, DC — Hybrid; at least three days onsite per week

Position Summary

The Senior AI/ML Engineer serves as a senior Forward Deployed Engineer and accountable technical lead supporting one or more Federal Agencies. The role translates ambiguous mission needs into secure, usable, accessible, and Government-owned AI capabilities. The incumbent provides hands-on architecture, engineering, AI assurance, delivery leadership, and stakeholder advisory support across discovery, design, development, testing, deployment, operations, and knowledge transfer.

Essential Responsibilities

• Lead agency-specific AI solution discovery, feasibility analysis, architecture, engineering design, integration, deployment, and operational support.

• Translate incomplete mission needs into measurable problem statements, user needs, acceptance criteria, prioritized backlogs, experiments, and release plans.

• Architect and implement AI-enabled applications using appropriate methods, including classical ML, document intelligence, NLP, LLM integrations, RAG, agentic workflows, multi-agent patterns, MCP server-based components, APIs, and deterministic automation.

• Select the simplest safe and effective solution rather than defaulting to generative AI.

• Lead the technical design of data flows, identity and access controls, trust boundaries, fallback and rollback methods, observability, and resilience.

• Direct MLOps/LLMOps practices, including version control, CI/CD, model/artifact registration, evaluation, monitoring, retraining or refresh workflows, and release management.

• Define and oversee AI evaluation methods for accuracy, groundedness, relevance, hallucination, calibration, fairness, robustness, explainability, and operational impact.

• Lead AI-specific adversarial testing for prompt injection, jailbreaks, data poisoning, retrieval manipulation, insecure tool use, agent-loop failures, secrets exposure, model extraction, and vector-store corruption.

• Ensure human-in-the-loop controls, documented override and escalation mechanisms, audit logging, and clear distinction between AI-generated and human-verified outputs.

• Produce or direct production-ready architecture artifacts, technical documentation, model cards, test evidence, SBOM inputs, operational runbooks, and release packages.

• Coordinate directly with Federal Agency CIO/OCIO organizations, AI governance teams, enterprise platform teams, cloud organizations, architecture review boards, security authorization teams, privacy, accessibility, legal, records, and other Government stakeholders.

• Support RAIA, PIA/PTA, ATO/RMF, SSP, SAP, SAR, POA&M, and related compliance documentation.

• Ensure custom code, prompts, configurations, models, datasets, embeddings, and deployment assets are developed and maintained in Government-controlled repositories.

• Serve as the technical primary point of contact for assigned Federal Agency stakeholders and provide planned/unplanned coverage for other key personnel.

• Act as, or work directly with, the designated Security Lead to certify security evidence for each applicable deliverable.

Minimum Qualifications

• Bachelor’s degree in computer science, data science, software engineering, information systems, statistics, engineering, or comparable field; Master’s degree preferred.

• Seven or more years of hands-on experience in AI/ML engineering, software engineering, cloud engineering, enterprise architecture, or data engineering, including delivery of AI-enabled systems.

• At least two years of hands-on production experience in one or more of generative AI, LLM integration, RAG, model evaluation, AI agents, or production AI system operations.

• Demonstrated ability to deliver across AI, application development, data engineering, UX, integration, and operations in ambiguous environments.

• Demonstrated experience designing secure enterprise or Federal AI architectures, including cloud AI platforms, APIs, data pipelines, vector databases, model orchestration, MCP, evaluation systems, and MLOps.

• Working knowledge of Federal or comparably regulated security, privacy, accessibility, Responsible AI, ATO/RMF, FISMA, FedRAMP, and PII/CUI protection practices.

• Demonstrated experience advising Government or executive stakeholders and leading technical delivery across multiple teams.

Required Certification Evidence

The candidate must hold and provide verifiable evidence of at least one relevant AI/ML credential, such as:

• Azure AI / Generative AI certification

• AWS Generative AI or Machine Learning certification

• Google Cloud Generative AI / ML credential

• Databricks Generative AI Engineer credential

• NVIDIA Generative AI credential

• Certified Artificial Intelligence Professional (CAIP)

• Equivalent recognized AI/ML certification

Certification evidence must be supplied at onboarding and annually thereafter. Self-attestation is not sufficient.

Preferred Qualifications

• Direct experience supporting Federal Agencies, especially systems involving PII, CUI, public-facing digital services, grants, enforcement, benefits, claims, or case-management operations.

• Experience with AWS, Azure AI Foundry, Google Vertex AI, AWS Bedrock, GitHub Copilot/VS Code, GitLab, JIRA, and Government-controlled CI/CD pipelines.

• Experience with accessibility-by-design and delivery of systems meeting Section 508/WCAG 2.1 A/AA.

• Experience supporting independent testing, red teaming, security assessment, and production ATO activities.