Описание

This role is with the Builder Experience (BX) team, which aims to make the Product and Engineering organization fully AI-native by building shared AI infrastructure, setting AI development standards, and providing training and support.

Responsibilities

Build the paved path, including agent harness and orchestration, model access layer, MCP servers for internal system integration (source control, Jira, Confluence, CI, observability), evaluation, observability, and cost tracking
Set standards, including golden paths, AI-readable context for repositories, and rules for AI-generated code, especially for high-risk paths like pricing and customer data; automate checks where possible
Multiply others through workshops, office hours, pairing with engineering and product teams, and coaching champions
Stay ahead by dedicating about one day a week to learning, trying new tools and models, running short pilots, and recommending adoption or deprecation
Measure what matters by tracking adoption, delivery speed, quality, and cost, using data for future development decisions
Mentor BX students by guiding their work, reviewing it, and supporting their growth

Requirements

6+ years of software engineering experience with strong backend or platform experience and production systems
Daily, hands-on use of coding agents (Claude Code, Cursor or similar) beyond autocomplete; demonstrate agent workflows, skills, or tools built
Experience building tools, platforms, or services that other engineers depend on
Solid knowledge of APIs, integrations, CI/CD, and cloud environments
Security-minded habits, including secrets handling, least privilege, and auditability
Clear communication in English, both written and spoken, capable of explaining technical ideas to skeptical senior engineers and product managers

Nice to have

Built MCP servers, agent frameworks, or LLM evaluation pipelines
Experience in a platform, DevEx, or developer productivity team
A record of teaching, such as talks, internal workshops, blog posts, or open-source work
Background in insurance, fintech, or other regulated domains

We offer

About one day a week is protected for learning new tools and models, running pilots, and recommending adoption or deprecation

Hiring process

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