Forward Deployed Engineer

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

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.

• 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.

• Bachelors degree in computer science data science software engineering information systems statistics engineering or comparable field; Masters 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.

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.

• 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.