​​Staff Full Spectrum Cyber AI Researcher

Leidos

28d

About The Position

The Leidos Cyber Accelerator is seeking a hands-on applied researcher to invent, prototype, and operationalize agentic AI systems, and the automation required to deploy them in enterprise environments. You will evaluate emerging agentic patterns (multi-agent coordination, tool use, human-in-the-loop oversight), implement them as working systems, and build reusable automation and integration patterns (e.g., LLM-driven tool connectors/protocols) that enable secure, observable, repeatable paths for deployment, validation, and security testing.

Requirements

• 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.

Nice To Haves

• 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.

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.

Benefits

• Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers.
• Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement.
• More details are available here.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level