Lead AI Engineer

CACI International•Stafford, VA

About The Position

We are seeking a system/software engineer to research, design and build Artificial Intelligence (AI) and Machine Learning (ML) solutions. As part of our team, you will help lay the foundation for future AI/ML initiatives while contributing to broader software development projects. You will work closely with a small cross-functional team to gather requirements, design, develop, and implement AI-driven features, seamless integrations, and deployment pipelines across a range of AI/ML use cases, including Generative AI.

Requirements

Bachelor's degree in computer science, software engineering, or a related field.
7 years of software development experience with 2-5 years of relevant experience in NLP, machine learning, or AI development
Experience designing agentic flows using supervisor, routing, and hierarchical patterns with frameworks such as LangGraph or equivalent
Experience with Linux and Linux based terminals
Understanding of RAG architecture and principles, experience implementing RAG systems, and familiarity with popular RAG frameworks and tools.
Knowledge of security best practices for AI systems
Strong programming skills, particularly in Python, Javascript, rust, golang
Experience with vector databases, embedding techniques, and data pipelines
Experience with information retrieval systems
Experience with RESTful APIs and Cloud Services (AWS, OCI)
Experience with data preprocessing, normalization, cleaning, encoding data into vector representations
Knowledge of text analytics and semantic search techniques
Experience with prompt engineering
Experience working with multiple teams in an agile environment, with data scientists, UI/UX designers, and subject matter experts to improve the overall system.
Self-motivated with ability to quickly adapt and learn emerging disciplines and techniques

Nice To Haves

Active Secret or Top-Secret clearance
T5 level background investigation (possesses or must be able to obtain)
Familiarity with version control systems (e.g., Git)
Experience with containerization (e.g., Docker)
Experience with relational databases, including schema design
Experience implementing observability, tracing, and evaluation frameworks for LLM-based applications
Understanding of CI/CD pipelines

Responsibilities

Forward thinking vision of how RAG can be integrated within a software development lifecycle and business practices, keeping abreast of new developments in RAG, NLP, and related fields.
Designing and implementing retrieval systems: Creating efficient ways to store and quickly access large amounts of relevant information.
Implementing safeguards: Developing mechanisms to prevent the system from retrieving or generating inappropriate or harmful content.
Developing and fine-tuning language models: Working with large language models to optimize their performance for specific tasks and domains.
Evaluation and testing: Designing and conducting tests to measure the system's accuracy, relevance, and overall performance.
Integrating retrieval and generation components: Ensuring seamless interaction between the retrieval system and the language model.
Follow a CACI agile methodology, attending daily standups, refinement sessions, and updating agile project management system to ensure transparency
Design and implement agentic workflows using supervisor and orchestration patterns with frameworks such as LangGraph, CrewAI, or similar multi-agent orchestration tools
Establish observability and evaluation pipelines using tools like Langfuse, LangSmith, or similar platforms to monitor, trace, and assess LLM application performance