AI Engineer - Application Development

CACI bv 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 utilizing the latest AI tools to enhance productivity and user experience.

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
• 5+ years of experience with software implementation across all aspects of the SDLC
• 1+ years of 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 architecture, 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