Associate AI Engineer at Innovative… · Arlington

Summary: Innovative Defense Technologies (IDT) is a leading defense technology company focused on rapidly delivering mission-critical software and systems solutions to the U.S. government. They are seeking an Associate AI Engineer to design and deliver engineering-focused AI solutions that support planning, reasoning, and tool use in real-world environments. Responsibilities: - Design and Build AI Solutions: Design and implement end-to-end agentic AI systems that support planning, reasoning, tool use, and multi-step execution in real-world environments. Build modular, testable components that move from prototype to operational capability - Integrate Models and Tools: Develop integrations across LLMs, APIs, data sources, and Model Context Protocol (MCP) interfaces to enable intelligent agents to interact with external systems, retrieve context, and take action safely and reliably - Develop Retrieval Pipelines: Build and optimize Retrieval-Augmented Generation (RAG) pipelines that connect models to live knowledge sources, structured data, and enterprise content to improve factual grounding, contextual relevance, and response quality - Engineer Conversational and Agentic Interfaces: Create conversational systems and intelligent agents with memory, contextual awareness, adaptive decision-making, and support for multi-turn user and system interactions - Implement and Evaluate AI Workflows: Translate technical objectives into working pipelines, run experiments, evaluate agent behavior, and iterate on prompts, orchestration logic, retrieval quality, and system performance to improve reliability and usability - Scope and Define Requirements: Gather, document, and validate technical and functional requirements from project artifacts, stakeholders, and mission needs to ensure feasibility, completeness, and alignment with operational goals - Collaborate Across Teams: Work closely with engineers, technical leads, and mission stakeholders to integrate AI capabilities into broader software and system architectures. Participate in technical reviews, design discussions, and delivery planning - Support Technical Quality: Contribute to testing, debugging, and performance optimization of AI-enabled applications, including edge cases involving context management, retrieval failures, tool execution, and orchestration logic - Learn and Apply Emerging Practices: Stay current on advances in LLMs, agent frameworks, orchestration methods, and applied AI engineering practices, and bring that knowledge into practical system design and implementation - Communicate Technical Work: Clearly document architectures, workflows, assumptions, and implementation decisions so that solutions are maintainable, explainable, and transferable across teams Required Qualifications: - Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Applied Mathematics, Artificial Intelligence, or a related technical field, or equivalent full-time professional experience - 0–3 years of full-time professional experience in software engineering, machine learning engineering, AI engineering, or related technical roles - Ability to travel up to 10% of the time as needed - Proficiency in Python, including experience with core libraries such as NumPy and Pandas - Experience building software with one or more modern AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LangGraph, Semantic Kernel, or AutoGen - Familiarity with Large Language Models (LLMs), prompt engineering, agent orchestration, or conversational AI systems - Familiarity with retrieval systems, vector databases, embeddings, or RAG-based application design - Understanding of software engineering fundamentals, including version control, testing, debugging, and writing maintainable code - Ability to work independently on technical tasks while collaborating effectively in a team environment - Strong problem-solving skills, curiosity, and a builder mindset focused on turning ideas into working systems Preferred Qualifications: - Experience building agentic AI systems that use tools, memory, planning, or multi-step execution - Familiarity with Model Context Protocol (MCP) integrations or similar model-to-tool integration patterns - Experience deploying AI services, APIs, or workflows in cloud or production environments - Experience with vector databases, retrieval infrastructure, knowledge graph integration, or enterprise search - Exposure to evaluation methods for LLMs and agents, including reasoning quality, hallucination reduction, tool-use reliability, and retrieval performance - Experience with Docker, REST APIs, Git-based development workflows, or CI/CD pipelines - Experience working on defense, government, or other mission-oriented technical programs - Strong interest in building practical AI systems that must operate reliably in complex, real-world environments Required Skills: Python, AI/ML frameworks, Large Language Models Important Skills: Retrieval-Augmented Generation, Model Context Protocol, Software engineering fundamentals Nice-to-Have Skills: Curiosity, Builder mindset Benefits: Generous benefits package, Competitive PTO, Paid holidays, 401(k) with immediate vesting and matching, 9/80 optional schedule (2nd and 4th Friday off every month), Tuition Assistance Reimbursement Program, Professional Development Resources, Pre-Tax Commuter Benefits, Organization-Wide Monthly Tech Connect Events, Annual Employee Recognition Awards, Regular Social Events and Catered Lunches