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Leidos · 1 day ago

Senior AI Engineer

United States

Full-time

Remote

Mid, Senior Level

$108K/yr - $195K/yr

4+ years exp

Leidos is a company that focuses on AI solutions for critical national and global missions. They are seeking a Senior AI Engineer to contribute to the development and deployment of Trusted Mission AI across various domains, including defense and healthcare, while collaborating with multidisciplinary teams to ensure the accuracy, security, and reliability of AI systems.

ComputerGovernmentInformation ServicesInformation TechnologyNational SecuritySoftware

No H1B

Security Clearance Required

Responsibilities

Collaborate with Agentic AI Scientists to build and deploy AI agents to automate and optimize workflows

Write software code to support AI agent communication and connect models and agents to external services via API calls

Support testing and debugging tasks, deployment into target environments, and set up monitoring for reliable execution of AI systems

Utilize open source models, agentic tools, and large proprietary commercial models to develop novel approaches for securing workflows and evaluating results

Conduct research, develop prototypes, evaluate and document results, and potentially publish findings at conferences

Be part of a team developing solutions for deployment into operational environments or integration into mission systems

Qualification

Large Language ModelsAPI integrationPythonDevSecOps practicesVector databasesGenerative AI modelsAI service integrationGPU programmingEnd usersEvaluation toolsCommunication skillsSelf-starter

Required

Practical experience with Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen

Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation (RAG), and memory/context management

Experience employing vector databases (Pinecone, Weaviate, FAISS)

Strong communication skills with the ability to present complex AI outputs in an accessible manner to non-technical stakeholders

Experience working with end users to streamline workflows and produce applied solutions

Experience with the Software Development Lifecycle (SDLC), including DevSecOps practices

Experience deploying into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)

Self-starter with a high degree of intellectual curiosity

Proficiency in modern software language such as Python and experience developing modular, production-grade AI pipelines

Ability to obtain a Secret clearance

Preferred

Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search

Hands-on experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI

Proficiency in scripting with Linux Bash, PowerShell, or equivalent automation tools

Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency

Expertise in designing and implementing safety, guardrails, and bias-mitigation strategies for autonomous agents and multi-agent systems

Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration, and coordination at scale

Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems

Experience integrating agents with cloud-native workflows, streaming data pipelines, and real-time decision-making environments