Builder Developer II

• *Job Description**

• *The Builder\-2 (Dev) Profile**

You are a full\-stack agent engineer. You can take a complex business requirement and build the multi\-step AI workflow that solves it, end to end, without someone breaking it down for you first.

• *1\. Core DNA**

• **AI\-Native Workflow.** You use AI to accelerate development, testing and documentation as a default, not an experiment. You have opinions about which tools earn their place.
• **Agentic Implementation.** You build, debug and deploy autonomous agents (LangGraph, AutoGen, Playwright\-LLM hybrids) that navigate complex ERP schemas and long\-running business logic.
• **Legacy\-to\-Modern Bridge.** You treat 20\-year\-old systems as puzzles for AI\-driven modernization, not as someone else’s problem.
• **Evidence Over Confidence.** You don’t ship an agent because the demo went well. You ship it because you can show what it does on the edge cases — and you know your own error rate rather than claiming there isn’t one.

• *2\. What You Own**

• *Your agent.** Design, build, debug, deploy, and keep running. Including the unglamorous parts: retries, state recovery, timeouts, what happens when the model is down.

• *The evidence it works.** Before you refactor an undocumented module, you capture what it currently does — characterization tests, real inputs, real outputs. After, you show the behaviour matches. Your Builder 3 sets the standard; meeting it is your job, not theirs.

• *Your blast radius.** You know exactly what your agent is permitted to touch, and you build so a wrong answer costs a review comment rather than a bad ledger entry.

• *3\. Your Elective Specialty (lean into one)**

• **The Agentic Architect (Systems)** — you don’t just build APIs, you build tool\-calling interfaces and state management for agentic graphs that survive long\-running business processes.
• **The UX/Interaction Builder (Product)** — the chatbox is just the beginning. You build generative UIs and browser\-use agents that navigate existing portals to get work done.
• **The Data \& Context Engineer (Data)** — master of the RAG pipeline. Vector stores, chunking strategy, and knowledge graphs that teach the AI how a Purchase Order relates to a GL entry.
• **The Reliability \& Eval Engineer (QA)** — you move the team from prompt vibes to prompt engineering. DSPy for programmatic optimization, red\-teaming agents to pressure\-test financial logic.
• **The Infra \& Agent\-Ops Builder (DevOps)** — you build the factory where agents live: tracing, logging and monitoring the thoughts of the AI.
• **The Domain Logic Translator (Business)** — you take 50 pages of accounting regulation and turn it into structured system prompts and agentic constraints.

• *What You’ll Actually Do**

• **Build execution agents.** Move beyond RAG into action — agents that navigate an ERP schema, find a data discrepancy and propose the fix.
• **Automate the untestable.** Wrap legacy business logic in modern tests and documentation using AI, starting with the modules everyone else has avoided.
• **Prove parity.** Capture what the old code does before you replace it, and show the new path matches — on the boring cases and the fiscal\-calendar, multi\-currency, partial\-shipment ones.
• **Prompt engineering and evals.** Use frameworks like DSPy to move from vibes\-based prompting to programmatic, optimized instructions.
• **Rapid prototyping.** Turn a “what if” into a working AI\-driven feature in days, not months.
• **Fix your own agents in production.** Read the traces, find why it went sideways, make it not happen again.

• *What Good Looks Like**

• (Illustrative — real targets agreed with the hiring manager.)*

• **30 days:** Shipped your first agentic workflow into a real environment, however small.
• **90 days:** Owning a legacy module end to end — parity evidence, tests, deployment — with minimal supervision.
• **6 months:** Other Builders are reusing patterns you built. You’re the person people ask about one thing in particular.

• *The Stack**

Python, SQL (Postgres/SQL Server), TypeScript, OpenAI/Anthropic, agentic coding tools, LangChain/LangGraph, DSPy, pgvector/Qdrant, dbt, Apache Hop/Airflow, Docker, Playwright, Weights \& Biases, OpenTelemetry, eval and tracing platforms (LangSmith / Langfuse / Braintrust or equivalent). And any other tool that helps us achieve greatness.

• *Who You Are**

• **You’ve shipped one.** You have built at least one autonomous agent or complex LLM workflow that real people used for real work — not a weekend demo. You know how it failed, because it did.
• **The early adopter.** You were using GPT\-3 before it was cool and had a local model running the week it leaked. More time on r/LocalLLaMA, GitHub Trending and AI Twitter than on LinkedIn.
• **Agent\-first thinker.** You think in capabilities and failure modes, not functions.
• **The manual\-task hater.** You have a physical reaction to repetitive work. If you do it twice, you’ve already started drafting the automation.
• **Technically fearless.** A 500\-table undocumented legacy schema isn’t complexity, it’s a puzzle about to get solved. You aren’t intimidated by spaghetti code — you’re the one who brings the sauce.
• **Rigor over hype.** You love the new models and you still ask for the numbers. You know the difference between a cool demo and a production\-grade agent handling financial data.

• *Why Join Us**

• **The Final Boss of complexity.** ERPs are the ultimate challenge for AI. Automate a General Ledger or a global supply chain and you’ve mastered the hardest problem in software.
• **Agentic autonomy.** We don’t do tickets. We do missions. You’ll have real freedom over the models, frameworks and agent architectures you think will win.
• **No red tape.** If the agent works and the evals pass, we ship. No Change Management Committee — a “Does It Work?” policy.
• **The Builder Tribe.** You won’t be the only AI person in the room. You’ll be part of a small squad of people equally obsessed with moving faster, where your automation hacks are your biggest contribution rather than a hidden side project.