Co-founder/Head of Engineering
DI · Engineering Enterprise Decisions
📍 Singapore or India · 3–4 years experience · Full-time · Hybrid / Remote · Early team · Equity opportunity
We are building something that has not been built before.
We are building an AI platform that replaces months of consulting workshops with an agentic system that conducts structured discovery, surfaces decision logic, and generates implementation-ready solution blueprints for enterprise finance transformations.
Our Initial products to focus on— one of the most complex, high-stakes design problems in enterprise finance. We are building a knowledge engine of 300+ structured questions, 100+ design rules, and a multi-agent pipeline that reasons from business objectives directly into deployable system designs.
We are pre-revenue, early team, and building fast. This is a founding engineering role. You will shape the product, the architecture, and the engineering culture from day one.
What we are looking for
Must have:
· Strong full-stack experience — Python backend, React/Next.js frontend
· Hands-on LLM integration — prompt engineering, structured output, Anthropic/OpenAI APIs
· Agentic AI — experience building sequential or orchestrated agent workflows, not just single-turn chatbots
· Vector databases and RAG — Pinecone, Weaviate, or similar
· Document processing — PDF/Word/Excel ingestion and structured parsing
· PostgreSQL — schema design for audit-trail and knowledge-base applications
· Cloud deployment — AWS, GCP, or Azure
Strong advantage:
· Document generation — python-docx, structured report output
· Enterprise software integrations — EPM platforms (Anaplan, OneStream, Oracle) or ERP APIs
· Knowledge graph or graph database experience
Education
Degree in Computer Science, Engineering, or a related technical discipline from a recognised university in Singapore or India.
NUS · NTU · IITs · BITS Pilani · NITs · IIITs · or equivalent
Why join Us:
◆ Founding role — you are employee #1 on the engineering side. Your name is on the architecture.
◆ Real problem, real market — EPM implementations fail at alarming rates and the industry has not changed in 20 years. We are targeting a large, expensive, genuinely broken market.
◆ Equity participation — this is a founding hire. We will structure meaningful equity for the right person who joins at this stage.
◆ Cutting-edge AI work — agentic systems, domain reasoning, structured output generation, knowledge graphs. Problems that are genuinely hard and genuinely unsolved.
What the first 90 days look like
Days 1–30: Learn the domain and product vision. Review the prototype, question library, and decision rule engine. Propose your architecture. Agree the stack. Ship the first working version of the AI interview engine.
Days 31–60: Build the decision rule engine and document ingestion pipeline. Wire the three-agent pipeline. Get the first end-to-end flow working — from document upload through to a draft blueprint output.
Days 61–90: Support the first two pilot engagements with real finance SMEs. Iterate fast. Build the blueprint generator. Prepare the platform for a third pilot with a system integrator partner.
Current stack
LLM / AI: Claude API (Anthropic) · OpenAI · custom agent orchestration
Backend: Python (FastAPI) · PostgreSQL · Pinecone
Frontend: Next.js · React · Tailwind CSS
Infra: AWS or GCP · Docker · GitHub Actions
You will have strong input into what we keep, change, and add.
How to apply
Send a connection request or message on LinkedIn or email us at info@diintl.com with three things:
1️⃣ Something you have built with LLMs or agentic systems — a link, a repo, or a description of what it did and how it worked
2️⃣ Your take on the above product idea — what excites you, and what you think the hardest technical problem will be
3️⃣ Where you studied and what you graduated in