Senior Agentic AI Scientist

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September 25

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Leidos

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Defense • Cybersecurity • Science

Leidos is a leading systems integrator in science, technology, and engineering, providing solutions that transform and enable the missions of its customers. The company operates across various markets, including aviation, defense, energy, government, healthcare, intelligence, science, and space. Leidos is involved in AI, digital modernization, cyber operations, and integrated and mission software systems. With a commitment to diversity, equity, inclusion, and sustainability, Leidos also engages in charitable efforts and community enrichment programs. Additionally, it contributes to developing solutions for counter-unmanned aerial systems and electric vehicle infrastructure for military applications.

10,000+ employees

Founded 1969

🔒 Cybersecurity

🔬 Science

📋 Description

• Create AI agents to plan, act, assess, and deliver measurable outcomes • Design, implement and deploy agentic workflows to automate and optimize labor-intensive workflows and empower the human workforce • Work as part of Leidos AI Accelerator on R&D and customer-facing goals to transition research into contract impact • Fine-tune and optimize generative models, potentially applying domain adaptation with supervised and unsupervised approaches • Develop using a combination of open source models, agentic tools, large proprietary commercial models, and small language models • Develop novel approaches to securing agentic workflows and evaluating results for accuracy, performance, and impact • Ensure AI systems adhere to ethical guidelines, transparency, and fairness principles • Conduct research, develop prototypes, perform applied research, evaluate and document results, and potentially publish/present findings • Contribute to teams developing solutions for deployment into operational environments or integration into mission systems • Collaborate with multidisciplinary teams and present complex AI outputs to non-technical stakeholders

🎯 Requirements

• Multiple openings from Mid to Senior levels with varying minimums: 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: Master’s degree in Computer Science, Engineering or related field and 15+ years of relevant experience, or a Doctorate degree with 13+ years of experience • Practical experience with Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen • Practical 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 • Skilled in data exploration using Python-based tools (e.g., Pandas, NumPy, Jupyter) • 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 • Self-starter with a high degree of intellectual curiosity • Proficiency in Python and Machine Learning libraries such as Tensorflow • Ability to obtain a Secret clearance • Preferred: Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation (RAG), and memory/context management • Preferred: Hands-on experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI • Preferred: Experience deploying into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes) • Preferred: Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency • Preferred: Expertise in designing and implementing safety, guardrails, and bias-mitigation strategies for autonomous agents and multi-agent systems • Preferred: Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration, and coordination at scale • Preferred: Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems • Preferred: Experience integrating agents with cloud-native workflows, streaming data pipelines, and real-time decision-making environments

🏖️ Benefits

• competitive compensation • Health and Wellness programs • Income Protection • Paid Leave • Retirement • Competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement (more details available on company site)