CACI International Inc is seeking an AI Engineer to design and deliver AI-based solutions for a web-based workflow application for the Federal Government. The role involves developing AI-enabled features, building Proof of Concept solutions, and working with cross-functional teams to enhance user experience and productivity.
Responsibilities:
- Design and develop AI-enabled features for web-based workflow applications using LLMs, GenAI, and agentic AI patterns
- Build RAG pipelines using application data, policy documents, user manuals, help cards and business process publications
- Implement agentic workflows using orchestration frameworks (LangGraph, Agno, Haystack, CrewAI) for AI based application assistants
- Implement prompt engineering strategies and integrate AI/LLM APIs (OpenAI, Bedrock)
- Architect full-stack AI features with reliable API integrations, error handling, and graceful degradation
- Establish LLM observability (cost, latency, quality) and responsible AI guardrails (hallucination detection, output validation, CUI safeguards)
- Maintain full-stack applications (including Web Application development using modern technologies such as React, TypeScript, NodeJS, Python and Java)
- Address security vulnerabilities and ensure compliance with cybersecurity standards
- Participate in code reviews, CI/CD pipelines, and collaborative development workflows
- Document technical implementations and stay current with AI and ML developments
Requirements:
- Bachelor's degree in Computer Science, Data Science, Mathematics, or related STEM field. Masters degree preferred
- Minimum 5+ years relevant experience
- 5+ years of experience with software implementation across all aspects of the SDLC
- 1+ years hands-on experience developing generative AI / LLM-powered applications
- Expert-level proficiency in Python; strong JavaScript proficiency
- Experience with RESTful APIs and integrating AI/LLM APIs (OpenAI, Bedrock)
- Experience with prompt engineering techniques (few-shot, chain-of-thought, system prompts)
- Experience with LLM orchestration frameworks such as LangGraph, Agno, CrewAI, or similar
- Experience with RAG architectures, agentic patterns, and vector databases
- Strong understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, feature engineering, NLP)
- Experience with data analysis and ML libraries (pandas, NumPy, scikit-learn, or equivalent)
- Experience with containerization (Docker) and at least one major cloud platform (AWS, Azure, or GCP)
- Proficiency with Git version control and CI/CD pipelines
- Strong written and verbal communication skills
- Experience with vector databases (OpenSearch, pgvector) and embedding models
- Experience with AWS GovCloud, AWS Bedrock, or Azure OpenAI Service