Senior AI/ML Engineer - Forward Deployed EngineerWork Location: Washington, DC - Hybrid; at least three days onsite per week
Position SummaryThe 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 EvidenceThe 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.
