2 hours ago
Remote, United StatesSenior
Base Salary
$180k - $225k/yr
Responsibilities
- Architect, develop, and deploy Generative AI and LLM-based solutions for initial lighthouse projects and production use.
- Establish the AI COE reference architecture for RAG, agent orchestration, model routing, evaluation, and guardrails across Azure Commercial and Azure Government.
- Build AI applications and integrate them into enterprise systems, mission workflows, and the AI platform.
- Work hands-on with foundation models, agent frameworks, RAG architectures, fine-tuning approaches, evaluation harnesses, AI pipelines, vector databases, and monitoring.
- Lead technical evaluation of vendors through the multi-vendor RFI and Forward Deployed Engineering engagements.
- Develop reusable technical patterns, assets, AI engineering practices, and responsible AI, security, and governance approaches.
- Mentor spoke-team technical leads and operating-group AI developers and grow into broader AI COE technical leadership responsibilities.
- Collaborate on JANUS-tracked delivery and AI Advisory Council package preparation.
Requirements
- Typically 8+ years of progressive experience in AI development, machine learning engineering, or applied AI, including 3+ years of hands-on Generative AI or LLM experience.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; a Master’s degree or Ph.D. is preferred.
- Production experience deploying Generative AI or LLM applications, including RAG, agentic workflows, and tool-use patterns.
- Hands-on AI/ML solution development across design, training or fine-tuning, evaluation, deployment, and monitoring.
- Knowledge of PyTorch, LangChain, LlamaIndex, Semantic Kernel, or equivalent AI frameworks, plus foundation-model ecosystems such as Azure OpenAI, AWS Bedrock, and open-source models.
- Experience with cloud-native architecture on Azure, AWS, or GCP and with AI pipelines, vector databases, and data engineering for AI workloads.
- Experience in regulated or government environments, responsible AI, model risk management, NIST AI RMF, EU AI Act categorization, FedRAMP, IL5/IL6, or ATO processes is preferred.
- Experience with multi-vendor AI engagements, hyperscaler partnerships, or Forward Deployed Engineering models is preferred.
- US citizenship is required; an active Secret or TS clearance is preferred.
- Strong technical judgment, communication, cross-functional delivery leadership, and ability to set technical direction in ambiguous environments are required.
Benefits
- Hybrid work arrangement based at the Reston, Virginia office, with standard business hours, schedule flexibility, and occasional travel to spoke sites and customer engagements.
- Health, dental, and vision insurance.
- Paid time off and holidays.
- Retirement benefits including 401(k) matching.
- Educational reimbursement.
- Parental leave.
- Employee stock purchase plan.
- Tax-saving options.
- Disability and life insurance.
- Pet insurance; benefits may vary by employment type, location, and applicable agreements.
Tech Stack
Categories
AI ApplicationsSolutions Engineering
