Engineering Manager

BukuWarung; Jakarta Pusat; On-site; IDR 446,400,000 - 1,004,400,000; Full time

Job summary

BukuWarung is seeking a Tech Lead Manager to own a slice of Business Acceleration & AI — architecture, delivery and people — for a pod of 3–5 engineers. You’ll ship AI-powered tools in days using AI coding agents and LLM-native patterns, reporting to an Engineering Manager/Senior EM.

You’ll stay hands‑on with coding while guiding the team, balancing speed, quality and stakeholder alignment in a fast-moving environment.

Qualifications

• 8–10 years of software engineering experience with end-to-end ownership.
• Recent hands‑on experience building with AI/LLM tech — agents, RAG, LLM APIs, AI coding tools — not occasional Copilot use, but AI-powered tools or products you’ve actually shipped
• Proven ability to operate hands‑on while managing people — this is not a seat for someone who wants to step back from the code
• Direct experience managing or leading a small engineering team, formally or as a tech lead with real people responsibilities
• A demonstrated bias for speed — a track record of shipping 0‑to‑1 tools or products in days or weeks, not quarters
• Strong product instincts — comfortable scoping ambiguous, under‑specified problems directly with business stakeholders
• Judgment on where AI tooling helps and where it doesn’t — able to articulate a real boundary, not a slogan
• Comfortable operating in a fast‑moving, less‑finished environment than a mature platform — this is a builder’s seat, not a maintainer’s

Responsibilities

• Own architecture and technical direction for rapid internal tools and AI‑native product builds
• Stay hands‑on: personally build using AI coding agents and LLM‑native patterns, going from idea to working product in days — setting the pace and quality bar by doing, not by review comment
• Manage, coach and grow 3–5 engineers — 1:1s, performance conversations, hiring, and levelling calls
• Partner directly with business, ops, risk and GTM stakeholders to scope ambiguous problems fast, without waiting on a full PRD
• Make fast build‑vs‑buy‑vs‑prompt calls — know when a thin AI wrapper beats a custom build, and when it doesn’t
• Set and evolve how the team uses AI coding agents, LLM APIs and automation platforms to multiply output
• Own reliability and iteration speed for what you ship — these are internal‑facing tools, but business‑critical ones, so breakages have real cost
• Bring judgment on where AI tooling should replace manual work entirely versus augment it

Skills

8-10 yrs exp

AI/LLM development

Hands-on leadership

Team leadership

Rapid delivery

Product instincts

AI tooling judgment

Builder mindset

Tools

AI coding agents

LLM APIs

RAG workflows

Job description

About Job

We’re hiring a Tech Lead Manager to own a slice of Business Acceleration & AI — architecture, delivery and people — for a team of 3–5 engineers. This is a high-velocity builder’s seat: you and your team go from a stakeholder’s problem to a working, AI-powered tool in days, using AI coding agents and LLM-native patterns as your default way of building, not a side experiment. You report to an Engineering Manager / Senior EM and act as the technical and people anchor for your pod.

Skills & Qualification

• 8–10 years of software engineering experience, with real ownership of shipping products end-to-end
• Significant, recent hands‑on experience building with AI/LLM technology — agents, RAG, LLM APIs, AI coding tools — not occasional Copilot use, but AI-powered tools or products you’ve actually shipped
• Proven ability to operate hands‑on while managing people — this is not a seat for someone who wants to step back from the code
• Direct experience managing or leading a small engineering team, formally or as a tech lead with real people responsibilities
• A demonstrated bias for speed — a track record of shipping 0‑to‑1 tools or products in days or weeks, not quarters
• Strong product instincts — comfortable scoping ambiguous, under‑specified problems directly with business stakeholders
• Judgment on where AI tooling helps and where it doesn’t — able to articulate a real boundary, not a slogan
• Comfortable operating in a fast‑moving, less‑finished environment than a mature platform — this is a builder’s seat, not a maintainer’s

Responsibilities

• Own architecture and technical direction for rapid internal tools and AI‑native product builds
• Stay hands‑on: personally build using AI coding agents and LLM‑native patterns, going from idea to working product in days — setting the pace and quality bar by doing, not by review comment
• Manage, coach and grow 3–5 engineers — 1:1s, performance conversations, hiring, and levelling calls
• Partner directly with business, ops, risk and GTM stakeholders to scope ambiguous problems fast, without waiting on a full PRD
• Make fast build‑vs‑buy‑vs‑prompt calls — know when a thin AI wrapper beats a custom build, and when it doesn’t
• Set and evolve how the team uses AI coding agents, LLM APIs and automation platforms to multiply output
• Own reliability and iteration speed for what you ship — these are internal‑facing tools, but business‑critical ones, so breakages have real cost
• Bring judgment on where AI tooling should replace manual work entirely versus augment it