Job Description
<h3>π Description</h3> β’ 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. β’ 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. β’ The tasks of the Senior 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. β’ 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. β’ They will be expected to ensure AI systems adhere to ethical guidelines, transparency, and fairness principles. β’ They should expect they may conduct research, develop prototypes, evaluate and document results, potentially through publication and presentation at conferences and other public forums. β’ They should also expect they may be part of a team developing solutions for deployment into operational environments, or for integration into mission systems. β’ They should be a self-starter while also working well within the team, collaborating and sharing discoveries and seeking feedback. β’ Multiple openings from Mid to Senior levels. The various positionβs minimum education and experience requirements are as follows: T3: Bachelor's degree in Computer Science, Engineering or related field and 4+ years of relevant experience, or a Masters degree with 2+ years of experience T4: Bachelor's degree in Computer Science, Engineering or related field and 8+ years of relevant experience, or a Masters degree with 6+ years of experience T5: Bachelor's degree in Computer Science, Engineering or related field and 12+ years of relevant experience, or a Masters degree with 10+ years of experience T6: Masterβs degree in Computer Science, Engineering or related field and 15+ years of relevant experience, or a Doctorate degree with 13+ years of experience <h3>π― Requirements</h3> β’ Practical experience with Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen
β’ Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation (RAG), and memory/context management
β’ Experience employing vector databases (Pinecone, Weaviate, FAISS)
β’ Strong communication skills with the ability to present complex AI outputs in an accessible manner to non-technical stakeholders
β’ Experience working with end users to streamline workflows and produce applied solutions
β’ Experience with the Software Development Lifecycle (SDLC), including DevSecOps practices
β’ Experience deploying into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)
β’ Self-starter with a high degree of intellectual curiosity
β’ Proficiency in modern software language such as Python and experience developing modular, production-grade AI pipelines <h3>ποΈ Benefits</h3> β’ Competitive compensation
β’ Health and Wellness programs
β’ Income Protection
β’ Paid Leave
β’ Retirement