AI Engineer (Co-Founder role)

Compensation: ₹12L – ₹40L • 10.0% – 20.0%

Equity-Only Position: This role is for a significant equity stake with no cash salary until funding. Please disregard the listed salary figures, as they are platform requirements. Include a confirmation that you have read and accept these terms; we will only respond to candidates who do so.

ABOUT BRANDBRAHMA BrandBrahma is an agentic AI marketing platform — a unified system of AI Operating Systems (Naming OS, Branding OS, Marketing OS and Marketplace OS) covering startup naming, branding, marketing and domain services. Our main product, Marketing OS — a complete digital marketing automation suite — is already built and shipped, alongside 4 Agentic AI systems powered by 30+ AI agents, a working orchestration layer, and a feedback layer. All of it built solo by the founder, fully bootstrapped, used by founders and marketers globally. This is not a job. This is a co-building opportunity for someone who wants their name on something real.

THE OPPORTUNITY The foundation is built and shipped. You're not starting from zero — you're taking a live orchestration layer, 30+ live agents, a shipped marketing automation suite, and a growing stream of real usage data, and turning it into the next layer of the company: a purpose-built marketing model that powers where Marketing OS goes next — a genuinely futuristic marketing automation product built on our own model, not just API calls to someone else's. You will be the first technical hire and the architect of BrandBrahma's next technical era. You'll work directly with the founder to decide whether we fine-tune an open-source model, train a domain-specific model from scratch, or build a hybrid system — and then build it. Your decisions will define the technical DNA of the company going forward. What you'll own from day one:

• Turning the existing feedback layer's data (every agent run, every human-in-the-loop approval, every Marketing OS interaction) into structured, proprietary training data

• Domain-specific fine-tuning pipeline: brand quality scoring, naming embeddings, domain valuation models, marketing-copy quality models

• The path toward a purpose-built marketing/branding LLM — evaluating fine-tuning vs. training your own model, and owning that roadmap end to end

• Architecting the model layer that will sit behind Marketing OS as it evolves from "shipped product" to "our own model powering it"

• Extending the existing orchestrator (intent detection, task planning, tool routing, memory, goal tracking) as new agents and use cases get added

• Tool adapter layer: keeping all 30+ agents and Marketing OS wrapped as clean, orchestrator-callable APIs as the fleet grows

• User session and long-term memory architecture (Supabase + vector DB)

• API design for marketplace and CRM integrations

• The data flywheel: making sure every agent run and every Marketing OS action continues to feed back into model improvement, now at a more sophisticated level than the current feedback loop

WHO WE'RE LOOKING FOR You are an entrepreneurial engineer who builds to ship, not to impress. You've worked with LLMs deeply enough to know their failure modes — and you're excited by the idea of building or fine-tuning a model, not just calling one via API. You think in systems and care about product outcomes as much as code quality. You want equity in something you helped create, not just a salary for work you executed. Must-haves:

• 4+ years of software engineering, with at least 1 year working with LLMs in production
• Strong Python and/or TypeScript — comfortable across the full stack
• Hands-on experience with OpenAI, Anthropic, or open-source model APIs
• Real experience with fine-tuning or training models — not just prompting them
• Understanding of agentic patterns: tool use, memory, planning, multi-step reasoning
• Experience building and deploying REST APIs
• Comfort with ambiguity and a bias toward shipping fast
• Entrepreneurial mindset — you think about user outcomes, not just tickets

Strong advantages:

Fine-tuning experience with Llama, Mistral, or similar open-source models Experience with RAG, vector databases (Pinecone, Weaviate, pgvector) Background in NLP, information retrieval, or recommendation systems Familiarity with Next.js / React and Supabase Prior startup experience or personal side projects shipped to real users Interest in brand strategy, naming, marketing automation, or the creator/startup ecosystem

WHAT YOU GET Equity & ownership 10%–20% equity (vesting over 4 years, 1-year cliff) Founding team title on all materials Carried in fundraising narrative as technical co-founder ESOP participation post-funding round

Compensation & growth Market-rate salary triggered on seed funding Direct access to investors and YC network You define your own roadmap and tech choices

You'll also get: Full access to all platform data from day one — no hidden metrics Budget for API credits, tools, and infra from day one Async-first, no micromanagement, no unnecessary meetings A founder who understands product deeply and will not slow you down

OUR PROMISE TO YOU We will be completely transparent about our runway, fundraising status, and revenue. If we pivot, you'll know why before it happens. Your equity will be documented and protected from day one. You'll be introduced as a co-founder in every investor conversation. We're not looking for an employee. We're looking for a partner.