AI Engineering Lead

Description

The company is building a team that delivers secure, production-ready AI applications and agent-based solutions for the United States Secret Service (USSS) contract, which supports the Department of Homeland Security.

The work covers the full software lifecycle, from discovery and solution design through development, testing, deployment and ongoing sustainment.

The AI capabilities will be built with LangChain and Microsoft Agent Framework and will connect to enterprise data, applications and workflows.

The role mixes hands-on technical work with managing a team. You will turn mission and business needs into a ranked roadmap, organize work across AI engineers and supporting roles, and set engineering practices for quality, security, scalability and measurable results.

The company values deep judgment across the wider generative AI engineering stack. Experience with one particular framework helps, but being able to deliver and run secure AI systems is required.

Responsibilities

• Lead, mentor and coordinate a mixed team that may include AI and software engineers, data engineers, product or business analysts, UX specialists and DevSecOps staff.
• Set the technical direction for AI applications and agentic solutions, covering architecture, design patterns, framework choice, integration, testing, deployment and day-to-day operations.
• Guide development using widely adopted agentic frameworks.
• Lead the build of retrieval-augmented generation (RAG), tool and API integrations, agent workflows and other features that link AI models to authorized enterprise data and business processes.
• Turn mission goals and user needs into technical approaches, product backlogs, user stories, acceptance criteria and a sequenced delivery roadmap.
• Set standards for Python and API work, reusable components, code review, automated testing, CI/CD, documentation and secure software delivery.
• Oversee evaluation of AI system quality across accuracy, relevance, grounding, safety and performance, and use test data and user feedback to drive improvements.
• Set up monitoring and observability for application health, model behavior, latency, usage and cost, and lead troubleshooting and continuous improvement.
• Work with cybersecurity, data governance, infrastructure, cloud, product and mission stakeholders on access controls, privacy, security and operational needs.
• Manage priorities, staffing and skill fit, delivery dependencies, risks and progress reporting, and explain decisions and issues to both technical and nontechnical audiences.
• Build responsible AI practices, including human review, traceable outputs, data protection, and clear handling of uncertainty and failure cases.
• Apply AI safety frameworks such as the NIST AI Safety Framework to put alignment controls in place for LLMs and agents.
• Help write AI safety and alignment policies and procedures that keep AI systems and agents ethical, controllable and aligned.

Requirements

• You must be able to obtain and maintain public trust before you start.
• A bachelor's degree plus 15 years of experience in artificial intelligence, machine learning, software engineering or a related field. Equivalents are considered: a master's plus 12 years, 21 years with no degree, or an associate degree plus 17 years.
• You have designed, built and supported production software that connects AI models with enterprise applications, data and APIs.
• You have built AI or agent-based applications with LangChain, Microsoft Agent Framework or a similar framework, and can explain the design choices and tradeoffs involved.
• You have a strong software engineering background in Python, APIs, microservices, automated testing, version control and CI/CD.
• You have worked with generative AI patterns such as RAG, prompt and context design, tool calling, agent workflows and model or application evaluation.
• You have deployed or run AI-enabled applications in the cloud, preferably on Microsoft Azure with Azure OpenAI or Azure AI services.
• You have set up or applied security controls for AI applications, including identity and access management, authorization-aware data retrieval, privacy protections and secure handling of sensitive information.
• You have led multidisciplinary teams by setting priorities, reviewing technical work, coaching staff and coordinating delivery with product, cybersecurity, data and operations stakeholders.
• You can explain technical concepts, risks, options and recommendations clearly to engineering teams and to executive or mission stakeholders.
• Desired: experience leading AI initiatives in federal government, law enforcement, investigative or national security settings, including sensitive data handling, ATO processes and compliance requirements.
• Desired: hands-on work with MLOps, model lifecycle management, AI governance frameworks, and production AI monitoring and observability tools.

Conditions

Full-time, regular employee position.

No minimum clearance is required to start.

Travel of up to 10% is required, local only.

Pay depends on factors such as location, Federal Government contract labor categories and wage rates, relevant experience, specific skills, education and certifications.

The proposed salary range is $103,800 - $218,100.

The company is an equal opportunity employer.

Benefits

• Flexible time off that lets you take the time you need.
• Access to learning resources and continuing education.
• Comprehensive healthcare, wellness, financial, retirement and family support benefits.
• Competitive compensation and learning and development opportunities.