AI Engineer

CACI International•Washington, DC

13d•$120,800 - $265,800

About The Position

The AI Engineer designs, develops, tests, documents, maintains, and supports AI-enabled applications and agent-based solutions for a United States Secret Service contract supporting the Department of Homeland Security. The role spans the software development lifecycle, translating mission and user needs into secure, reliable capabilities that integrate AI models with enterprise data, applications, and workflows. Solutions may use frameworks such as LangChain and Microsoft Agent Framework, cloud-based AI services, and established software engineering practices. The engineer collaborates with product, functional, data, cybersecurity, infrastructure, DevSecOps, and software engineering teams. Work includes building and evaluating retrieval-augmented generation (RAG), tool and API integrations, and agent workflows; improving quality through automated testing and user feedback; and supporting deployment, monitoring, incident resolution, maintenance, and continuous improvement. The role also contributes to AI safety and alignment policies, procedures, and controls to support ethical, controllable, and aligned AI systems and agents.

Requirements

Bachelor's degree and 10 years of experience in artificial intelligence, machine learning, software engineering, or a related field; stated equivalencies include a master's degree plus 7 years, 16 years with no degree, or an associate degree plus 12 years.
At least five years of experience in software engineering, application development, AI/ML engineering, or a related technical field.
Demonstrated experience developing software applications or services using Python and APIs.
Hands-on experience building generative AI or machine learning applications that integrate models with data, applications, or workflows.
Experience using LangChain, Microsoft Agent Framework, or a comparable framework to build AI or agent-based capabilities.
Understanding of RAG, prompt and context design, model or application evaluation, and integration with enterprise data.
Experience with automated testing, version control, and CI/CD practices.
Familiarity with cloud-based application development and deployment.
Understanding of secure software development and the need to protect sensitive information and restrict access to enterprise data.
Ability to collaborate with technical teams, product staff, and functional stakeholders, and to communicate technical work clearly.

Nice To Haves

Experience developing production applications using both LangChain and Microsoft Agent Framework.
Experience with LangGraph or other approaches for building stateful, multi-step agent workflows.
Experience with Azure OpenAI, Azure AI services, or Azure AI Foundry.
Experience implementing authorization-aware RAG, data filtering, and access controls for retrieval and tool use.
Experience with AI evaluation methods, test sets, tracing, observability, and monitoring for quality, latency, and cost.
Experience integrating AI applications with enterprise systems, microservices, and web interfaces.
Familiarity with responsible AI practices, including human review, explainability, and safe handling of uncertain or unsupported outputs.
Relevant cloud, AI, or software engineering certifications.
Experience with Microsoft Azure.

Responsibilities

Design, develop, test, document, and maintain AI-enabled applications and services.
Implement AI and agent workflows using LangChain, Microsoft Agent Framework, or other suitable frameworks and services.
Develop RAG capabilities, including data ingestion, retrieval, grounding, and integration with authorized enterprise information sources.
Integrate AI models with APIs, enterprise applications, and business workflows, including appropriate tool use and human review.
Work with product owners, users, and functional specialists to understand needs and translate them into technical designs, user stories, and acceptance criteria.
Develop and maintain application components, APIs, and services using Python and established software engineering practices.
Create and execute automated tests and evaluations to assess accuracy, relevance, grounding, safety, and performance.
Troubleshoot application and model behavior and use test results, telemetry, and user feedback to improve solution quality.
Support deployment and operations, including CI/CD, monitoring, documentation, incident resolution, and ongoing maintenance.
Apply security and privacy requirements, including identity and access controls, authorization-aware retrieval, and protection of sensitive data.
Collaborate with data, cloud, cybersecurity, DevSecOps, and software engineering teams to integrate solutions into the enterprise environment.
Contribute reusable components, technical documentation, and engineering practices that improve consistency and maintainability.
Use familiarity with AI safety frameworks, such as the NIST AI Safety Framework, to support alignment controls in AI models and agents.
Contribute to AI safety and alignment policies and procedures for ethical, controllable, and aligned AI systems and agents.