[Hiring] AI Platform Engineer @Polygon Labs

Role Description

We are hiring an AI Platform Engineer to help build the platform that powers every agent at Polygon Labs. Polygon is a cryptocurrency company focused on on-chain payments infrastructure. As we shift to having agents manage the majority of work across engineering, business development, compliance, support, and finance, people will supervise and guide those agents while making key decisions.

You will join a small, flat Platform Team reporting to the AI Platform Lead. This team owns the entire AI platform, including the agent runtime, MCP servers, guardrails, evaluations, observability, and spend tracking. The team proactively identifies opportunities where AI can accelerate, improve, or automate work company-wide—including tasks that haven’t yet been automated.

Our internal customers are Operators: domain experts in every function who manage fleets of agents and define standards of quality. This is a hands-on IC role, where you will write code, ship to production, and take ownership of your deliverables.

Your Responsibilities

• Move agentic workflows into production, taking prototypes to robust systems for real users and owners, with SLAs (e.g. spec-to-PR agents, AI code review, incident triage, KYB review).
• Build and manage MCP servers, including system design, hosting, security, authentication (e.g. per-user OAuth), and keeping a clean connector inventory for Slack, GitHub, Jira, HubSpot, and internal services.
• Develop autonomous agents that act and plan across tools through trust stages: shadow, suggest, execute, and autonomous.
• Embed guardrails into the platform, providing each agent its own identity, scoped credentials, audit logs, CI checks, approval gates, allowlists, and least-privilege access.
• Build evaluation frameworks (test sets, regression suites, live scoring in production) so every agent releases with quality metrics tied to business outcomes.
• Instrument agents for observability: tracing, logging, latency, cost, drift detection, and daily dashboards for Operators.
• Track AI spend across providers (Anthropic, OpenAI, OpenRouter), setting budgets, alerts, and spend attribution to teams, agents, and workflows.
• Support Operators by developing features from their requests, writing documentation, running enablement sessions, and building self-service tools.
• Create skills and plugins centralizing company knowledge (processes, standards, security, brand), versioning and reviewing these to ensure consistent, repeatable agent output.
• Proactively find and automate manual, repetitive processes across the company, measuring outcomes and iterating rapidly.

Qualifications

• 5+ years as a software, platform, or infrastructure engineer, including experience prior to AI coding tools.
• Solid grasp of system design, data modeling, testing, debugging, and code review.
• 6-12 months shipping LLM-based systems to production, with agentic workflows in use by real end users.
• Daily, hands-on experience with AI coding agents like Claude Code and Codex to write, test, and review production code.
• Experience building autonomous or multi-step agents with tool use (Claude Agent SDK, Anthropic/OpenAI APIs, or similar).
• MCP server experience (OAuth flows, scoped tokens, user-level access control).
• Identity and access experience: Okta (or similar IdP), SSO (SAML/OIDC), SCIM provisioning, group-based and device policies.
• Creating automated system identities (GitHub Apps, service accounts, API keys, secret managers like 1Password).
• Designing guardrails: least-privilege, audit logs, CI checks, approval gates, allowlists, and policy-as-code.
• Creating evals for LLM systems: test sets, rubrics, CI regression, release gates, and live production scoring.
• Instrumenting production system observability: tracing, metrics, alerting, dashboards (OpenTelemetry, Grafana, Datadog, Langfuse, LangSmith, Braintrust).
• Tracking AI spend across vendors: per-key limits, cost centers, budgets, actionable alerts.
• Strong in at least one of TypeScript, Python, Go; working knowledge of CI/CD (GitHub Actions/etc), cloud infrastructure.
• Track record of independently identifying and automating manual processes (two or three concrete examples).
• Clear, concise written communication (specs, runbooks, RFCs).

Preferred Qualifications

• Cryptocurrency, blockchain, payments, or fintech experience (regulated industry/audit a plus).
• Experience writing agent skills, plugins, or shared prompt libraries for organizational reuse.
• Familiarity with model gateways (OpenRouter, LiteLLM, Portkey): key management, routing, fallback.
• Experience extending open-source coding agents (OpenCode, Pi).
• Awareness of emerging agent identity standards (MCP enterprise-managed auth, Okta Cross App Access).
• Context/retrieval engineering: vector stores, agent memory, permissioned retrievals.
• ML engineering: model evaluation, fine-tuning, model routing.
• Experience with agent runtimes/sandboxes (Modal, n8n, containerized environments).
• Public technical work: open-source tools, servers, blog posts, talks about agent production experience.

How You’ll Work

• Treat Operators as the customer—supporting engineers and non-engineers in every business function.
• Listen to needs, refine vague asks into actionable requirements, and communicate technical concepts plainly to executives or subject matter experts.
• Assertively but diplomatically push back on unsafe or low-value requests, suggesting alternatives.
• Operate autonomously: write specs, break down projects, ship and iterate independently, and communicate progress asynchronously across time zones.
• Use judgment to distinguish critical automations from temporary demos, and validate changes with affected users.
• Own outcomes post-merge: pilot, monitor, fix, and iterate as needed.
• Work transparently in public channels, tickets, written docs, and runbooks.
• Create reusable assets (skills, plugins, templates, tools) from frequent learnings or solutions, making them broadly accessible across the company.

Success in 90 Days

• 30 days: Ship production changes to a live system (e.g. AI SDLC pipeline, code review, or spend analytics). Gain familiarity with agent runtime, MCP servers, spend tracking.
• 60 days: Take end-to-end ownership of a platform area, publishing a spec and meeting with relevant Operators.
• 90 days: Ship an agent with live-scored eval suite and Operator dashboard; complete an Operator request independently; propose and launch at least one unsolicited automation.

Benefits

• Remote first global workforce
• Industry leading Medical, Dental and Vision health insurance*
• Company matching 401k with 3% match*
• $1,500 Home Office Set Up Allowance (life-time max)
• $200 Annual Book Allowance Program
• $75 Monthly internet or phone reimbursement
• Flexible Time Off
• Company issued laptop
• Egg freezing, mental health, and employee wellness benefits