You'll be embedded directly with client engineering teams — in their codebases, in their standups, in their friction
Your job is to close the activation gap: run discovery on how engineering actually works today, identify where existing SDLC processes break when you introduce coding agents, and rewire how teams deliver software. Delivering change by building together and teaching by example
Work alongside clients in their codebases, demonstrating agentic workflows in context
Pair with individual engineers to help them cross the threshold from "I tried it" to "this has changed how I work every day"
Teach by doing, making codebases agent-friendly with rules files, custom skills, MCPs, etc
Run discovery with engineering leadership to map where the real workflow friction is — not where they think it is
Identify how existing SDLC processes break when you introduce coding agents — QA bottlenecks, poorly scoped requirements, review debt — and redesign them
Scope and deliver upskilling programmes built around the client's stack and culture, not generic content
Document what's working and feed it back to the practice — you're helping build the playbook, not just running it
Identify repeatable patterns across engagements and contribute to how Tribe scales this service
Requirements
You've genuinely reorganised how you work around agentic coding tools — Claude Code or Codex is your daily driver, and you can articulate specifically what changed
You've spent meaningful time inside large engineering organisations (100+ engineers) and understand why enterprise moves the way it does
You have consulting or consulting-adjacent experience, or have led developer productivity/DX from the inside at an AI-forward company
You find the enterprise transformation problem genuinely interesting, not a necessary evil
You get energy from bringing the whole room up two levels — not just the engineers who are already excited
Tech Stack
SDLC
Benefits
Impact: Be at the frontier of how enterprises actually adopt agentic coding — not in theory, in real codebases with real constraints
Timing: This is the year it happens. Enterprise AI adoption is the defining challenge for our partners right now, and Tribe is uniquely positioned to lead it
Variety: Work across industries, stacks, and organizational cultures — no two engagements look the same
Practice: Help build something from the ground up — the frameworks, playbooks, and patterns that define how this work gets done at scale
Team: Work alongside people who have reorganized how they work around these tools and are serious about what comes next