AI Engineer

Description

The company is hiring an AI Engineer for its AI Center of Excellence, which sits within the CTO organization and drives the adoption and scaling of AI across the company's mission, program and business work.

This is a prototype-focused role. You will join programs for rotations of 1-2 months, put working AI applications into production, set good practices, and pass knowledge to teams so they can run the systems on their own.

You will build with current GenAI tools, including RAG pipelines, conversational AI platforms and multi-agent systems, drawing on the team's catalog of proven templates. Between rotations, you will feed what you learned back into the catalog as reusable patterns.

The role suits engineers who enjoy working across many areas more than owning one system long term, who get satisfaction from helping others succeed, and who want to influence how the Federal Government uses AI across different mission areas.

The posting is expected to close on 3/1/2027.

Responsibilities

• Deliver production-ready AI solutions during 1-2 month rotations, such as RAG pipelines, conversational platforms and multi-agent systems fitted to each program's mission and technology stack.
• Build and adapt AI solutions with vector databases, orchestration frameworks and managed AI services, adding observability, security and cost controls.
• Connect LLM APIs and AI services to existing workflows, add responsible AI guardrails, set up monitoring and alerts, and fix integration problems in both cloud and on-premises environments.
• Run hands-on training, write documentation, and pair-program with teams so they can operate and change AI applications without help.
• Improve existing templates, build new reusable patterns, and document techniques learned in the field for the catalog.
• Check that each team has reached full operational independence through a structured handoff and validation process.
• Keep up with new GenAI tools, assess whether they fit federal use cases, and share findings through demos and written notes.

Requirements

• 3-5 years of building production applications in Python or JavaScript, using Git workflows and current development practices.
• Hands-on work with LLM-powered apps, agent patterns, RAG, prompt engineering, vector databases and observability concepts. Experimentation counts, though it is preferred rather than strictly needed.
• Track AI performance on latency, cost and quality, handle common failure modes, and apply responsible AI practices such as bias detection and guardrails.
• Solid experience designing, building and debugging RESTful and event-driven integrations.
• Experience with AWS, Azure or GCP, containerization, CI/CD, infrastructure-as-code concepts, and secure handling of APIs and keys.
• Working knowledge of basic machine learning and how it applies to LLM systems.
• A record of delivering solutions quickly in unfamiliar settings where requirements keep changing.
• Clear written communication and the ability to explain complex AI topics to others.
• The judgment to make trade-offs under pressure, focus on what works, and reuse templates where possible.
• You use modern AI tools regularly and keep current through experimentation and community involvement.
• Experience with GitLab, Jira and iterative delivery.
• Ability to obtain and keep a Top Secret clearance, up to that level.
• Desired: Experience deploying agentic AI systems and using observability tools, vector databases, guardrails, embeddings and structured outputs.
• Desired: Experience with AWS Bedrock or GovCloud, Azure OpenAI, Kubernetes, Terraform and CI/CD pipelines.
• Desired: Proficiency in JavaScript, TypeScript or Python for front-end and back-end work, with frameworks such as React or FastAPI.
• Desired: Experience leading client engagements, switching between projects, and transferring knowledge well.
• Desired: Familiarity with DoD and federal missions, security requirements, and compliance frameworks such as ATO and NIST.
• Desired: Open-source contributions, technical writing, conference talks, or similar community work.
• Desired: Security+, AWS certifications, or other relevant technical credentials.

Conditions

Full-time, regular position with no security clearance required to start.

No travel required.

The role can be based in more than one location. The salary range shown is the national average for the position.

Final pay depends on factors including location, federal contract labor categories and wage rates, relevant prior experience, specific skills and competencies, education, and certifications.

The proposed salary range is $82,100-$172,400.

Benefits

• Flexible time off that lets you take the time you need.
• Comprehensive benefits, including healthcare, wellness, financial, retirement, family support, continuing education and time off.
• Learning and development resources to support your career goals.