Operations Engineer
Coast · New York, NY
About this role
## Operations Engineer — Coast ### About Coast Coast is re-imagining the U.S. B2B card payments infrastructure for commercial fleets—modernizing decades-old technology for fleets that need better digital experiences and transparent financial services. Coast builds payments and spend management for fleet businesses (fuel cards, corporate cards, and bill pay). The company is becoming **AI-native**, using AI to handle repeatable work so teams can focus on customers and the hardest problems. ### About the Role This is a **builder role with an operator’s mindset**. You’ll find high-leverage work across Sales, Customer Success, Marketing, Support, Finance, Risk, Product, and Operations—owning it end to end, from first conversation to production. Some weeks you’ll write code; others you’ll run workshops or redesign processes with teams. You’ll join as one of **two AI Operations Engineers**, reporting to the **AI Lead**. ### What You’ll Do - **Find and prioritize the work**: Sit with teams, map workflows, estimate time saved, and turn findings into a ranked backlog with the AI Lead. - **Build autonomous agents**: Ship event-driven agents that perform multi-step work across the stack. You’ll own engineering that off-the-shelf tools can’t do: - **Loop and orchestration**: design agent loops, sub-agent handoffs, and decide when to act alone or escalate to a human. - **Memory and context**: model shared memory as a knowledge graph; decide what each agent sees, remembers, and forgets. - **Custom tooling**: build the tools agents need. - **Traces and evals**: trace every run, score outputs against test sets from real outcomes, and prove each version improves. - **Measure impact**: define success metrics, track adoption and time saved, and report results to leadership. - **Run what you ship**: own reliability, latency, and cost in production; catch regressions early; partner with Security and IT on access, audit trails, and sensitive data handling. - **Enable the company**: architect shared infrastructure (knowledge bases, application databases, templates, tools, connectors) and help teams adopt it via training, office hours, and hackathons. - **Stay on the cutting edge**: evaluate new models/tools, compare against current systems, and continuously raise the bar. ### Projects you might take on - **Autonomous product help docs**: Capture questions from customers (support tickets/calls) and employees (Slack), detect missing/outdated articles, draft updates, route for review, and learn from what gets approved and shared. - **Deal coach for large trials**: Build an agent that creates value calculators and tailored pitch decks from call transcripts and account data—coaching AEs/CSMs through trials with next steps and learning which plays win. ### Requirements - **2–5 years** in operations, product, solutions, forward-deployed engineering, internal tools, or a similar role at a fast-moving company. - Track record shipping **AI workflows/automations** used daily—show what you built. - Hands-on fluency with **Claude Code, Cursor, or similar coding agents**, plus LLM tooling (prompt design, tool use, MCP). - Built at least one agent with **persistent memory** and/or a **feedback loop** that improved it over time. - Experience with **evals**: building test sets, scoring outputs, and using results to improve agents. - Comfort writing/reading code: **SQL**, plus **Python or TypeScript** scripting, APIs, and webhooks. - Clear communication with non
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