AI Engineer

About Brainforge

At Brainforge, we're on a mission to transform data into actionable insights that drive business success. As a rapidly growing data analytics consulting company, we partner with clients across various industries to deliver cutting-edge solutions that unlock the full potential of their data. Join our dynamic team and be a part of shaping the future of data analytics.

Transforming raw data into actionable insights

We help businesses boost revenue, save time, and make smarter decisions with Data and AI

Quick Links

https://www.brainforge.ai/

https://www.linkedin.com/company/brain-forge/

We are looking for a self-starting engineer who can engineer the full AI stack — from raw data to production agents — and sit in client conversations to make sure what we build actually fits the problem.

In this role, you’ll engineer context (customer, company, content, code, and control data), design and ship agent surfaces, build evaluation and observability so things don’t silently break in production, and proactively bring tooling and direction to the AI team. You’ll be a founding-team member: client-facing one day, building agent harnesses the next.

In this role, you will:

• Engineer the full AI stack end-to-end — from raw context (customer, company, content, code, control data) all the way to production agents users actually rely on
• Design agent surfaces (chat, slash commands, side panels, background agents) and the backend, APIs, and integrations that make them useful — not just the LLM layer
• Build and maintain evaluation frameworks, observability, and golden-question harnesses (Arize, Braintrust, or in-house) so regressions are caught before clients are
• Sit in client conversations: scope discovery, push back on AI solutions that don’t fit, and write SOW language we can actually deliver
• Bring tooling, harnesses, and platform direction to the AI team proactively — don’t wait to be told what to adopt
• Review AI-generated code with the same rigor as human-written code, and compound learnings into reusable skills and playbooks the team can keep using

Your background looks something like:

• 2+ years of relevant engineering experience including professional work, personal projects, etc.
• Experience owning AI/LLM systems end-to-end in production — not just shipping a feature, but the full path from data and context to the user surface
• Strength in at least two of: context/knowledge engineering, agent orchestration, evals & observability, backend/API, surface UX
• Experience with inference and evaluation platforms
• Experience with RAG, semantic search, vector stores, embeddings
• Experience building features end-to-end with TypeScript, React.js, and Node.js
• Ability to thrive in a fast-paced startup environment with evolving requirements and priorities
• Comfortable using AI coding agents (e.g. Cursor, Copilot, Codex) in day-to-day development, and reviewing AI-generated code with the same rigor as human-written code—spotting bugs, security issues, and design debt before merge.

Preferred technical background:

• Agent frameworks & tooling: OpenCode, OpenClaw, Hermes Agent, OpenWork
• Agent architecture: background agents, agent surface design
• AI system design: context engineering / knowledge engineering, memory systems
• Evaluation & observability: Arize, Braintrust
• Developer tools for AI: Cursor, Codex
• Skills & capability frameworks, harnesses for testing and iteration

As a person, you…

• are first and foremost a builder.
• love working in a startup environment (you either have experience working in a startup or are really drawn to the zero-to-one phase)
• want to be at the cutting edge of building world-class products on top of language models
• are fascinated by LLMs. You love to play with them, figure out what makes them tick and get them to do what you want. You scour the web and reddit for others doing the same (you probably follow @goodside on twitter)
• value working with people who are kind, ambitious and pragmatic