AI Platform Engineer

IMPORTANT RECRUITING INSTRUCTIONS

This is an urgent search. Our client is hiring for a critical, high-visibility project and wants this engineer in place quickly. Please prioritize qualified candidates you can submit in the next one to two weeks. About the Opportunity Our client is a growing boutique technology consulting firm serving enterprise clients. They're building a greenfield platform that governs how AI agents interact with enterprise systems, including what they can access, what requires approval, and how every action is recorded. This engineer builds the core of that platform from an established design spec, working alongside the Solutions Architect. Perks include a fully remote role, great benefits, generous PTO, certification support, and the chance to build a new AI governance platform from the ground up. Must-Haves (non-negotiable) 5+ years in backend, platform, or infrastructure engineering on production systems Hands-on experience building at least one of: policy/access-control systems, audit logging, or workflow orchestration. Specific tools (OPA, Cedar, Temporal, SPIFFE) are not required; comparable experience is fine. Solid working knowledge of LLMs and AI agents: how they work, how they connect to enterprise systems, and the risks they introduce. Hands-on AI development is not required, but general curiosity is not enough. Candidates should be able to speak to it with substance. Production AWS experience (required) Containerized deployments (Kubernetes, EKS, ECS, or similar) Comfortable building from a design spec with limited existing code Work authorization: US citizens and green card holders only. No visa sponsorship available. Strong Pluses AWS certifications (Solutions Architect, DevOps Engineer, Security Specialty, or Machine Learning). Certified candidates will be highly considered. Hands-on experience building AI agents or LLM applications Identity and authentication (OAuth/OIDC, Entra ID, or similar) Enterprise middleware (ESBs, message queues) and legacy system integration Observability tooling such as OpenTelemetry Compliance frameworks such as SOX, NERC-CIP, or HIPAA Critical infrastructure or regulated industry background Please Do Not Submit Data scientists, ML researchers, or analytics profiles without platform engineering experience Candidates with only Azure or GCP experience and no production AWS work Front-end or full-stack developers without backend infrastructure depth DevOps profiles focused only on pipelines and tooling, with no experience building access control, audit, or orchestration systems Candidates requiring sponsorship now or in the future Compensation $120K to $160K base plus benefits. Full-time, fully remote within the US. Please confirm base and total compensation expectations before submitting. Candidates currently above $160K may be considered, if stellar (stellar means they check all of the requirements AND a couple pluses). Submission Requirements Current resume A short recruiter summary covering why they fit the must-haves, their current and expected compensation, work authorization, location, availability, AWS certifications, and other active interviews The candidate's answers to these two questions: "Describe a system you built that controlled who or what could take action, such as access control, approvals, or audit logging. What did it protect, and how did it work?" "If an AI agent needed to update a system like SAP or Oracle, what controls would you put in place before that action happened?" Confirmation that you've spoken with the candidate, they're interested, and you have the right to represent them Specific, detailed answers are the best indicator of fit. Candidates who answer in generalities are unlikely to advance. Thank you for your help on this one. Strong, well-screened submittals will move quickly. Client is a minority- and woman-owned business...growing rapidly in the tech space. Opps for growth exist. Open PTO is a huge plus! JOB Description: AI Platform Engineer Our client is building a platform that governs how AI agents interact with enterprise systems, including what they can access, what requires approval, and how every action is recorded. They're looking for an AI Platform Engineer to help build it from the ground up. This is a greenfield build from an established design spec, ideal for an engineer who wants to shape a platform from day one. Key Responsibilities Build the core control-plane infrastructure that enforces separation between propose, decide, and execute actions across all agents Implement business-rule and guardrail engines, risk-model registries, and configuration-governance workflows, including dual approval, versioning, and rollback Build access-control and policy-enforcement layers (OPA/Cedar-style policy engines) scoped beyond native system-of-record roles Implement immutable, hash-chained audit logging that satisfies enterprise compliance evidence requirements Build the governed connector framework, including staging, retry, and circuit-breaker logic, that mediates all writes back to systems of record Stand up identity and workload-identity infrastructure (SPIFFE, Entra ID federation, or similar) for agent registration and authentication Implement observability instrumentation (OpenTelemetry, tracing/spans) so every governed action is traceable end to end Build and maintain the synthetic test data environment and scenario/regression harness used to validate the platform independent of production systems Collaborate with the Solutions Architect to keep the platform's integration contract stable and backward-compatible as new agents onboard Support infrastructure provisioning and deployment automation, including containerization and CI/CD What You Bring 5+ years in backend, platform, or infrastructure engineering on production systems Hands-on experience building policy/access-control systems, audit logging, or workflow orchestration (OPA, Cedar, Temporal, SPIFFE, or comparable tools) Solid working knowledge of LLMs and AI agents, including how they connect to enterprise systems and the risks they introduce Production experience with AWS Experience with containerized deployments (Kubernetes, EKS, ECS, or similar) Identity and authentication experience (OAuth/OIDC, Entra ID, or similar) Comfort building from a design spec with limited existing code Bachelor's degree in computer science, engineering, or a related field, or equivalent experience Preferred Experience AWS certifications (Solutions Architect, DevOps Engineer, Security Specialty, or Machine Learning) Hands-on experience building AI agents or LLM applications Experience integrating enterprise middleware (ESBs, message queues) and legacy systems of record Familiarity with compliance-driven audit requirements (SOX ITGC, NERC-CIP, HIPAA, or similar) Experience building AI governance or control-tower platforms, including approval routing, risk scoring, and agent onboarding Background supporting critical infrastructure or highly regulated environments Why Join Competitive salary and a comprehensive benefits package Fully remote, with flexible work arrangements that support work-life balance Clear paths for professional growth and career advancement Certification support to keep building your skills An inclusive, collaborative culture where your work is visible and valued Dimensional Thinking