Freelance Full Stack Machine Learning Engineer Jobs in Columbus, OH

Required Qualifications

• Minimum of a BA/BS degree with 2 years of experience; MS degree with 0 years of experience
• Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Information Systems, or Computer Engineering
• Hands-on experience building with AI agents — 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
• Familiarity with agentic frameworks and an understanding of the underlying concepts (chains, tool calling, agent loops) that transfer across tools
• Experience operating CI/CD pipelines in GitHub Actions and/or GitLab CI
• Experience with cloud infrastructure (AWS) including VPC, IAM, S3, RDS, CloudTrail, and KMS
• Hands-on experience with Kubernetes (Amazon EKS preferred), including cluster upgrades, RBAC, Helm, and GitOps workflows
• Experience building and maintaining Terraform/OpenTofu infrastructure-as-code
• Strong skills in release planning, deployment automation, validation, and rollback procedures
• Experience with monitoring, logging, and alerting systems (CloudWatch, Prometheus, Grafana, or similar)
• Ability to perform anomaly detection, log analysis, and troubleshoot configuration and security issues
• Practical understanding of secrets management, least privilege, supply chain security, and audit evidence
• Experience performing vulnerability remediation and managing IAVM or similar compliance requirements
• Familiarity with DAST and runtime security testing tools (e.g., OWASP ZAP, Burp, Nuclei)
• Experience with identity provider integration (SSO/SAML/OIDC) and RBAC administration
• Comfort operating with some ambiguity in a fast-moving environment

Clearance Requirements

• U.S. Citizenship is required
• Ability to obtain a Public Trust

Desired Qualifications

• Production experience with agent frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, OpenAI Agents SDK, Anthropic tool-use, or comparable) and a sound point of view on when each is the right tool
• Experience designing and operating retrieval-augmented generation (RAG) systems — chunking strategies, embedding models, vector stores, hybrid retrieval, reranking, and grounding/citation patterns
• Experience integrating with knowledge graphs, document stores, or curated content repositories as agent-accessible sources
• Experience evaluating agent and LLM systems — building eval harnesses, golden datasets, regression testing, and observability for non-deterministic systems
• Exposure to orchestration patterns: supervisor agents, parallel tool calls, human-in-the-loop flows, DAG-based pipeline execution
• Experience building plugin or extension systems: dynamic code loading, container isolation, API mixin patterns
• Familiarity with prompt engineering, evaluation frameworks, or agent observability
• Familiarity with federal compliance environments: FedRAMP, FIPS 140-2/3, IronBank container hardening, OPA policy enforcement, or Section 508 accessibility
• Experience with observability tooling: OpenTelemetry, Jaeger, Prometheus, Grafana, or similar distributed tracing/metrics stacks
• Experience with container orchestration (Docker SDK, Kubernetes) and distributed storage (S3, MinIO, JuiceFS)
• Experience designing synthetic or transactional monitoring tied to user journeys and critical service flows
• Experience developing SLOs, service health indicators, and high-fidelity operational alerting
• Experience with modern delivery patterns such as trunk-based development, merge-request-driven change, and automated release quality controls
• Experience in security-focused CI/CD or DevSecOps environments
• Experience coordinating with customer security teams or operating within compliance frameworks
• Prior work building internal tooling, enterprise automation products, or platforms for government customers

Peraton is seeking a talented and motivatedFull Stack & DevSecOps Engineerto join a dynamic team building and operating a cutting-edge Agentic AI platform. This hybrid role sits at the intersection of application engineering and platform operations — combining the responsibilities of a Full Stack Engineer specializing in Agentic AI and External Integrations with those of a DevSecOps / Platform Engineer.

In this role, you will design, develop, and maintain the integrations and intelligent agent capabilities that power a next-generation decision-support platform, while also owning the delivery infrastructure, CI/CD pipelines, cloud operations, and platform health that keep it running securely and reliably. You will work across the full stack to connect AI agents with diverse external data sources, package real-world capabilities as reliable agent tools, and ensure that the systems you build are secure, scalable, observable, and production ready.

If you are passionate about applied AI, thrive in fast-moving environments, and take pride in building platforms that real users depend on — from the application layer down to the infrastructure — this is an opportunity to make a meaningful impact supporting critical missions.

Location:Columbus, Ohio — candidates must currently reside in the area or be willing to relocate.

Key Responsibilities

Full Stack & Agentic AI Engineering

• Design and build integrations to external sources of information, including public APIs, licensed data feeds, partner systems, customer enterprise systems, web content, document repositories, and structured databases
• Package external capabilities as agent tools and skills with clean interfaces, predictable inputs/outputs, sound error handling, and documentation usable by both AI agents and human configurators
• Develop and maintain full-stack components spanning FastAPI/Python backends, React frontends, Docker containerization, and PostgreSQL
• Build and consume web APIs (REST, GraphQL, or comparable), handling production integration concerns such as authentication, pagination, rate limiting, retry/backoff, schema mapping, deduplication, and caching
• Implement and maintain workflow and task orchestration pipelines using systems such as Airflow, Prefect, Celery, or comparable agent orchestration patterns
• Integrate LLMs into production or near-production applications, leveraging APIs such as OpenAI, Anthropic, or AWS Bedrock
• Apply security best practices specific to agentic and external integration work — including secrets management, OAuth and API-key handling, defensive parsing, and prompt-injection awareness
• Collaborate across teams with a product mindset, keeping the end-user experience central to technical decisions

DevSecOps & Platform Engineering

• Build and maintain CI/CD pipelines across GitHub Actions and/or GitLab CI, enabling secure, repeatable, and efficient delivery workflows
• Implement and improve automated testing and quality gates within the software delivery lifecycle, including build validation, integration checks, security testing, and deployment controls
• Plan and execute releases and deployments — coordinating change windows, managing release artifacts, running deployment automation, validating post-deployment health, and supporting rollback procedures
• Support operational ownership of Amazon EKS / Kubernetes environments, including cluster lifecycle activities, upgrades, troubleshooting, RBAC, Helm-based deployments, pod identity, and GitOps-aligned workflows
• Build and maintain AWS infrastructure supporting platform and application needs across services such as VPC, IAM, S3, RDS, CloudTrail, and KMS
• Contribute to infrastructure provisioning and lifecycle management through OpenTofu / Terraform and related infrastructure-as-code practices
• Administer user management for the platform — identity provider integration (SSO/SAML/OIDC), RBAC, provisioning and deprovisioning workflows, and periodic access reviews
• Design and operate a mature monitoring, logging, and alerting stack using CloudWatch, Prometheus/Grafana, or equivalent tooling
• Routinely assess system logs to detect anomalies, configuration drift, misuse, and security-relevant events; triage findings and drive remediation
• Build and maintain synthetic and transactional monitoring that exercises real authentication flows, user journeys, and critical service transactions
• Track and remediate Information Assurance Vulnerability Management (IAVM) notices and other vulnerability advisories — maintain inventory accuracy, drive patching to closure, and produce compliance reporting evidence
• Implement and maintain DAST and runtime security testing in delivery pipelines using tools such as OWASP ZAP, Burp, Nuclei, or equivalent
• Support security-focused CI/CD practices including secrets management, least privilege, software supply chain integrity, and audit evidence generation