AI Engineering Lead

CACI; Washington (District of Columbia); Vor Ort; USD 180.000 - 240.000; Vollzeit

Zusammenfassung

CACI is seeking an AI Engineering Lead to build and guide a multidisciplinary team delivering secure, production-ready AI applications and agent-based solutions for federal contracts. You will steer the full software lifecycle from discovery to sustainment, balancing mission needs with engineered security and scalability.

The role emphasizes leadership, system design, and implementation of AI capabilities connected to enterprise data and workflows using LangChain and Azure AI services.

Qualifikationen

• Must obtain/maintain public trust to begin employment.
• Experience designing and supporting production software with AI models.
• Experience with LangChain or similar agent frameworks; explain design choices.
• Strong Python API/microservices background; testing and CI/CD.

Aufgaben

• Lead, mentor, and coordinate a multidisciplinary team of AI and software engineers and supporting roles.
• Provide technical direction across architecture, design, integration, testing, deployment, and operations.
• Guide development using agentic frameworks and implement RAG and tool integrations.
• Translate objectives into technical roadmaps, user stories, and acceptance criteria.
• Establish engineering standards for secure, scalable AI applications and observability.

Kenntnisse

AI leadership

Python

APIs & microservices

CI/CD

Team coaching

Ausbildung

Bachelor's degree + 15 years experience

Tools

LangChain

Microsoft Agent Framework

Azure/Azure OpenAI

Jobbeschreibung

Job Title: AI Engineering Lead

Job Category: Information Technology

Time Type: Full time

Minimum Clearance Required to Start: None

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

The Opportunity

We are seeking an AI Engineering Lead to build and lead a multidisciplinary team delivering secure, production-ready AI applications and agent-based solutions to support the United States Secret Service (USSS) contract supporting the Department of Homeland Security. The lead will provide technical direction across the software development lifecycle, from discovery and solution design through development, testing, deployment, and sustainment. The team will use frameworks such as LangChain and Microsoft Agent Framework to develop AI capabilities that integrate with enterprise data, applications, and workflows.

This role combines hands-on technical leadership with functional team management. The lead will translate mission and business needs into a prioritized roadmap, organize work across AI engineers and supporting roles, and establish engineering practices that support quality, security, scalability, and measurable outcomes. The position requires strong judgment across the broader GenAI engineering stack; experience with a particular framework is valuable, but the ability to deliver and operate secure AI systems is essential.

Responsibilities

• Lead, mentor, and coordinate a multidisciplinary team that may include AI and software engineers, data engineers, product or business analysts, UX specialists, and DevSecOps staff.
• Provide technical direction for AI applications and agentic solutions, including architecture, design patterns, framework selection, integration, testing, deployment, and ongoing operations.
• Guide development using industry-standard agentic frameworks.
• Lead implementation of retrieval-augmented generation (RAG), tool and API integrations, agent workflows, and other capabilities that connect AI models to authorized enterprise data and business processes.
• Translate mission objectives and user needs into technical approaches, product backlogs, user stories, acceptance criteria, and a sequenced delivery roadmap.
• Establish engineering standards for Python and API development, reusable components, code review, automated testing, CI/CD, documentation, and secure software delivery.
• Direct evaluation of AI system quality, including accuracy, relevance, grounding, safety, and performance; use test data and user feedback to guide improvements.
• Establish monitoring and observability for application health, model behavior, latency, usage, and cost; lead troubleshooting and continuous improvement.
• Coordinate with cybersecurity, data governance, infrastructure, cloud, product, and mission stakeholders to address access controls, privacy, security, and operational requirements.
• Manage team priorities, staffing and skill alignment, delivery dependencies, risks, and progress reporting; communicate decisions and issues to technical and nontechnical stakeholders.
• Promote responsible AI practices, including appropriate human review, traceable outputs, data protection, and clear handling of uncertainty and failure conditions.
• Familiarity with AI safety frameworks such as the NIST AI Safety Framework to support implementation of alignment controls in artificial intelligence LLMs and agents
• Contribute to the development of the AI Safety/Alignment policies, procedures, etc., for ensuring ethical, controllable, and aligned artificial intelligence systems and agents

Qualifications

• Required:
• Must be able to obtain and maintain a public trust to begin employment
• Bachelor's degree + 15 years of experience in artificial intelligence, machine learning, software engineering, or related field; equivalencies considered (Master's + 12 years; 21 years with no degree; AA + 17 years)
• Demonstrated experience designing, building, and supporting production software that integrates AI models with enterprise applications, data, and APIs.
• Experience developing AI or agent-based applications with LangChain, Microsoft Agent Framework, or comparable frameworks; ability to explain framework design choices and tradeoffs.
• Strong software engineering background in Python, APIs, microservices, automated testing, version control, and CI/CD.
• Experience with generative AI patterns such as RAG, prompt and context design, tool calling, agent workflows, and model or application evaluation.
• Experience deploying or operating AI-enabled applications in a cloud environment, preferably Microsoft Azure and Azure OpenAI or Azure AI services.
• Experience establishing or applying security controls for AI applications, including identity and access management, authorization-aware data retrieval, privacy protections, and secure handling of sensitive information.
• Experience leading multidisciplinary teams, setting priorities, reviewing technical work, coaching staff, and