Agentic AI Engineer

At Leidos, you'll contribute to AI solutions that serve critical national and global missions—ranging from defense and intelligence to healthcare, energy, and space exploration. Our work emphasizes Trusted Mission AI: systems that are transparent, ethical, resilient, and accountable. You’ll collaborate with multidisciplinary teams to transition AI research into operational environments where accuracy, security, and reliability are non-negotiable. Joining Leidos means applying your expertise to solve some of the most complex and meaningful challenges of our time.

We are looking for a motivated Agentic AI engineer who wants to work on challenging problems in a variety of domains – including enterprise IT, health, defense, intelligence, and energy – to get results that apply and go beyond the state of the art for measurably better outcomes.  We apply our knowledge, capabilities, and experience to develop and deploy Trusted Mission AI – AI that deserves to be trusted by system owners, end users, and the public – to be accurate, ethical, reliable, and adaptable.  We are looking for a researcher that is expert in envisioning, developing, and securing AI agents using generative AI and LLM-based tools to transform and add value to human workflows.

Primary Responsibilities.

The Agentic AI Engineer will collaborate with Agentic AI Scientists to build and deploy AI agents to both automate and optimize labor-intensive workflows, as well as empowering the human workforce to discover entirely new capabilities.  As a member of the Leidos AI Accelerator, they will be tasked at different times with both R&D as well as customer-facing goals, to speed the transition of novel applied research and solutions development into impact on contract.

The tasks of the Agentic AI Engineer will include writing software code to support AI agent communication, connecting models and agents to external services via API calls, support testing and debugging tasks, deployment into target environments, setting up monitoring, and ensuring reliable execution of agentic AI systems.  They will utilize a combination of open source models, agentic tools, and large proprietary commercial models.  They will be developing novel approaches to securing agentic workflows and to evaluating the results for accuracy, performance, and impact.  They will be expected to ensure AI systems adhere to ethical guidelines, transparency, and fairness principles.

They should expect they may conduct research, develop prototypes, evaluate and document results, potentially through publication and presentation at conferences and other public forums.  They should also expect they may be part of a team developing solutions for deployment into operational environments, or for integration into mission systems.  They should be a self-starter while also working well within the team, collaborating and sharing discoveries and seeking feedback. 

Multiple openings at various levels. The various position’s minimum education and experience requirements are as follows:

• T1: Bachelor's degree in Computer Science, Engineering or related field and relevant experience
• T2: Bachelor's degree in Computer Science, Engineering or related field and 2+ years of relevant experience, or a Masters degree with relevant experience

Basic/Required Qualifications.

• Practical understanding of 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)
• Familiarity with deployment 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
• Ability to obtain a Secret clearance

Preferred Qualifications.

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

LeidosAI

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.