AI/ML Software Engineer
Peraton, Annapolis, MD, United States
Minimum Requirements
Minimum of a BS degree with 5 years of experience, MS degree with 3 years, or PhD with meaningful exposure to AI/ML systems or LLM-based products
Hands‑on experience building agentic systems using multi‑step reasoning, tool use, RAG pipelines, or autonomous task execution
Strong Python skills (3.12+); comfort with async/await patterns, type hints, and modern Python tooling
Experience with workflow or task orchestration systems (Airflow, Prefect, Celery, or similar distributed execution frameworks)
Familiarity with agentic frameworks and an understanding of the underlying concepts (chains, tool calling, agent loops) that transfer across tools
Experience working with LLM APIs (OpenAI, Anthropic, AWS Bedrock, or similar)
Comfort working across the stack: FastAPI/Python backends, React frontends, Docker containerization, and PostgreSQL
A product mindset: you think about the end user, not just the technical implementation
Comfort operating with some ambiguity in a fast‑moving environment
US Citizenship is a requirement for this position
Desired Additional Experience
Experience with workflow orchestration frameworks for workflow/activity patterns, task queues, worker lifecycle management
Familiarity with federal compliance environments: FedRAMP, FIPS 140‑2/3, IronBank container hardening, OPA policy enforcement, or Section 508 accessibility
Experience building plugin or extension systems: dynamic code loading, container isolation, API mixin patterns
Exposure to orchestration patterns: supervisor agents, parallel tool calls, human‑in‑the‑loop flows, DAG‑based pipeline execution
Experience with observability tooling: OpenTelemetry, Jaeger, Prometheus, Grafana, or similar distributed tracing/metrics stacks
Familiarity with prompt engineering, evaluation frameworks, or agent observability
Experience with container orchestration (Docker SDK, Kubernetes) and distributed storage (S3, MinIO, JuiceFS)
Prior work building internal tooling, enterprise automation products, or platforms for government customers
Peraton Labs is seeking an AI/ML Software Engineer to join the Labs Agentic AI team. You will design, build, and ship AI‑powered systems—a compliance‑ready, low‑code platform for dynamically generating and orchestrating AI agentic workflows. The role engages across the full product lifecycle, from architecting multi‑step agentic pipelines backed by Temporal.io to building the plugin system, APIs, and interfaces that bring them to life within federal‑grade security and accreditation constraints.
This is a role for someone who thinks deeply about how AI agents should behave in high‑trust environments, cares about reliability and auditability, and can move fluidly between distributed orchestration, backend systems, and product‑facing features.
Responsibilities
Design and implement agentic AI capabilities using Python‑based frameworks (LangChain, LangGraph, DeepAgents) and orchestrated workflows
Build and maintain integrations with LLM APIs (Anthropic/Claude, OpenAI, AWS Bedrock, Ollama) to power intelligent, multi‑step automations
Develop full‑stack product features (FastAPI + React) that surface AI capabilities to users— from REST APIs and streaming interfaces to workflow builders and dashboards
Instrument agent pipelines with OpenTelemetry tracing, provenance audit trails, and observability tooling for debugging and performance evaluation
Write clear, well‑tested, maintainable code that passes strict pre‑commit validation, and contribute to engineering standards in a compliance‑driven environment
Evaluate agent performance, debug distributed workflows, and continuously improve reliability and output quality
#J-18808-Ljbffr
Minimum of a BS degree with 5 years of experience, MS degree with 3 years, or PhD with meaningful exposure to AI/ML systems or LLM-based products
Hands‑on experience building agentic systems using multi‑step reasoning, tool use, RAG pipelines, or autonomous task execution
Strong Python skills (3.12+); comfort with async/await patterns, type hints, and modern Python tooling
Experience with workflow or task orchestration systems (Airflow, Prefect, Celery, or similar distributed execution frameworks)
Familiarity with agentic frameworks and an understanding of the underlying concepts (chains, tool calling, agent loops) that transfer across tools
Experience working with LLM APIs (OpenAI, Anthropic, AWS Bedrock, or similar)
Comfort working across the stack: FastAPI/Python backends, React frontends, Docker containerization, and PostgreSQL
A product mindset: you think about the end user, not just the technical implementation
Comfort operating with some ambiguity in a fast‑moving environment
US Citizenship is a requirement for this position
Desired Additional Experience
Experience with workflow orchestration frameworks for workflow/activity patterns, task queues, worker lifecycle management
Familiarity with federal compliance environments: FedRAMP, FIPS 140‑2/3, IronBank container hardening, OPA policy enforcement, or Section 508 accessibility
Experience building plugin or extension systems: dynamic code loading, container isolation, API mixin patterns
Exposure to orchestration patterns: supervisor agents, parallel tool calls, human‑in‑the‑loop flows, DAG‑based pipeline execution
Experience with observability tooling: OpenTelemetry, Jaeger, Prometheus, Grafana, or similar distributed tracing/metrics stacks
Familiarity with prompt engineering, evaluation frameworks, or agent observability
Experience with container orchestration (Docker SDK, Kubernetes) and distributed storage (S3, MinIO, JuiceFS)
Prior work building internal tooling, enterprise automation products, or platforms for government customers
Peraton Labs is seeking an AI/ML Software Engineer to join the Labs Agentic AI team. You will design, build, and ship AI‑powered systems—a compliance‑ready, low‑code platform for dynamically generating and orchestrating AI agentic workflows. The role engages across the full product lifecycle, from architecting multi‑step agentic pipelines backed by Temporal.io to building the plugin system, APIs, and interfaces that bring them to life within federal‑grade security and accreditation constraints.
This is a role for someone who thinks deeply about how AI agents should behave in high‑trust environments, cares about reliability and auditability, and can move fluidly between distributed orchestration, backend systems, and product‑facing features.
Responsibilities
Design and implement agentic AI capabilities using Python‑based frameworks (LangChain, LangGraph, DeepAgents) and orchestrated workflows
Build and maintain integrations with LLM APIs (Anthropic/Claude, OpenAI, AWS Bedrock, Ollama) to power intelligent, multi‑step automations
Develop full‑stack product features (FastAPI + React) that surface AI capabilities to users— from REST APIs and streaming interfaces to workflow builders and dashboards
Instrument agent pipelines with OpenTelemetry tracing, provenance audit trails, and observability tooling for debugging and performance evaluation
Write clear, well‑tested, maintainable code that passes strict pre‑commit validation, and contribute to engineering standards in a compliance‑driven environment
Evaluate agent performance, debug distributed workflows, and continuously improve reliability and output quality
#J-18808-Ljbffr