Applied Researcher - Agentic AI Systems

Note: The job is a remote job and is open to candidates in USA.

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. They are seeking a hands-on applied researcher to invent, prototype, and operationalize agentic AI systems, focusing on multi-agent coordination and automation for deployment in enterprise environments.

Responsibilities

• Comfortable with modern tools to support configuration and software development (examples: Codex, Claude Code)
• Research, prototype, and evaluate multi-agent architectures (supervisor/worker, hierarchical, HITL) and translate successful patterns into reusable libraries/services
• Agent/orchestration frameworks (examples: LangGraph-style state machines, AutoGen-style agent teams, CrewAI-style workflows)
• Build secure agent-to-tool integrations using open connectivity standards
• Agent tool-integration protocols (examples: Model Context Protocol (MCP), structured tool/function calling patterns)
• Create deployment automation for agentic services: reproducible environments and repeatable enterprise releases on Kubernetes
• IaC & environment provisioning (e.g., Terraform)
• Kubernetes packaging & configuration management (examples: Helm, Kustomize)
• Stand up production-like stacks on AWS + Kubernetes and codify them into repeatable, automated, tooling
• Debug and refine AI-driven workflows, ensuring that work can be generalized
• Create trials and collect metrics for demonstrating success of automated deployments and connectivity between enterprise components
• Build observability-first agent systems (tool-call telemetry, step tracing, eval hooks)
• Research and apply nonhuman/workload identity patterns for agentic services and integrate into deployment automation
• Model serving/inference platforms (examples: Ollama, vLLM, Ray Serve)
• Observability/instrumentation standards (examples: OpenTelemetry) and common backends (examples: Prometheus, Grafana, Jaeger)
• (Optional, as mission needs) Experiment with scalable serving patterns for LLM endpoints on Kubernetes

Skills

• Bachelor's degree and 8+ years relevant experience (software engineering, applied R&D, platform/DevSecOps, AI/ML engineering, cyber engineering). Additional years may substitute for degree
• Proven hands-on delivery: prototypes that ran, tools others used, automation others depended on
• Strong development skills; experience building LLM-enabled systems and/or multi-agent workflows
• Practical experience with Kubernetes and modern deployment/IaC practices; Terraform, K8s familiarity
• Must be a US Citizen with the ability to obtain and maintain a Secret clearance
• Experience productizing internal platforms ("paved roads"): templates, reference architectures, golden paths, and guardrails
• GitOps delivery experience (Argo CD/Flux or similar), and observability pipeline experience (OpenTelemetry or similar)
• Workload identity / service-to-service auth experience (SPIFFE/SPIRE, mTLS, policy enforcement)
• Familiarity with research methodologies, with a focus on establishing validation of techniques (e.g., F1 scores, ROC/AUC, correlation methods)
• Ability to obtain and maintain a TS/SCI clearance
• Experiment with scalable serving patterns for LLM endpoints on Kubernetes

Benefits

• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement

Company Overview

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. It was founded in 1969, and is headquartered in Reston, Virginia, USA, with a workforce of 10001+ employees. Its website is https://www.leidos.com.