Key skills
PythonTypeScript/JavaScriptFull-stack developmentLarge language modelsAI integrationAPI integrationDockerKubernetesIntellectual curiosityProblem-solvingCollaborationJavaScriptTypeScriptAIMLNLPGenerative AILarge Language ModelsOpenAIPyTorchTensorFlowLangChainLangGraphReactNext.jsNode.jsAWSAzureGCPBedrockVertex AISDLCCI/CDPrototypingCommunication
About this role
Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. They are seeking a motivated AI Engineer to contribute to AI solutions that serve critical national and global missions, focusing on designing, building, and deploying agentic AI systems to optimize workflows and enhance human capabilities.
Responsibilities:
- Collaborate closely with Agentic AI Scientists and product teams to design, build, and deploy agentic AI systems that automate and optimize labor-intensive workflows while enabling the human workforce with new, AI-powered capabilities
- Develop and maintain full-stack software that supports agentic AI workflows
- Build user-facing interfaces and tools, implementing backend services and APIs, and writing application logic that enables agent communication, orchestration, and tool use
- Integrate AI models and agents with external systems and services via APIs, supporting testing and debugging, deploying solutions into target environments, configuring monitoring and logging, and ensuring reliable, secure execution of agentic AI systems in production
- Contribute to the development of approaches for securing agentic workflows and for evaluating system behavior with respect to accuracy, performance, reliability, and mission impact
- Help ensure that AI systems adhere to ethical guidelines and principles of transparency, accountability, and fairness
- Conduct applied research, develop prototypes, and evaluate and document results, including contributing to technical reports, publications, or conference presentations
- Be part of teams delivering solutions for deployment into operational environments or integrating AI capabilities into existing mission systems
- Take ownership of complex features while collaborating effectively within a multidisciplinary team
- Actively share discoveries, seek feedback, and contribute to a culture of continuous learning and innovation across the AI Accelerator
Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related field with 2+ years of relevant professional experience, or a Master's degree with relevant experience
- Strong software engineering fundamentals with hands-on experience building production systems
- Proficiency in modern programming languages, including TypeScript/JavaScript for application development and Python for AI integration and prototyping
- Experience building full-stack applications, including frontend development (React) and backend services/APIs (Node.js / python)
- Practical understanding of large language models (LLMs) and experience using agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, A2A, or MCP
- Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation (RAG), and memory/context management
- Experience integrating AI systems with external services, data sources, and mission systems via secure APIs
- Familiarity with deploying and operating applications in virtualized and containerized environments (e.g., Docker, Kubernetes, VMware)
- Experience with logging, monitoring, testing, and debugging distributed systems
- Self-starter with strong problem-solving skills, intellectual curiosity, and the ability to collaborate effectively within a multidisciplinary team
- Ability to obtain a Secret clearance
- Strong understanding and hands-on experience with generative AI techniques, including prompt engineering, tool orchestration, and common NLP tasks such as summarization, entity extraction, and semantic search
- Experience with the full Software Development Lifecycle (SDLC), including DevSecOps practices and CI/CD pipelines
- Hands-on experience integrating commercial and government AI services such as Azure OpenAI, AWS Bedrock, GCP Vertex AI, or similar platforms
- Familiarity with modern frontend tooling and frameworks (e.g., Next.js, component libraries, state management, and frontend testing)
- Experience with MCP Toolbox or building mcp servers via fastmcp or similar frameworks
- Experience with evaluation, observability, and telemetry for AI systems and agents (e.g., LangSmith, OpenAI Evals, custom monitoring solutions)
- Experience developing and deploying agentic AI solutions, including autonomous planning–execution–reflection loops and multi-agent collaboration
- Familiarity with cloud-native architectures, event-driven systems, streaming data pipelines, and real-time decision-making workflows
- Experience designing and implementing AI safety, security, and guardrail mechanisms, including access control, auditability, and bias mitigation
- Hands-on experience with GPU-accelerated ML workloads (e.g., PyTorch, TensorFlow, CUDA) for teams that require custom model training or optimization