Full-Stack AI Engineer, Titan Capital

Location: Gurgaon Sec 67, in office/hybrid | Experience: 2+ years | Type: Full-time

About

Titan Capital is a leading early-stage venture capital firm investing in India's most ambitious startups at the seed stage. With a portfolio spanning 300+ companies in consumer, fintech, SaaS, healthcare and emerging technologies, Titan partners closely with exceptional founders to build category-defining companies.

Our investment team builds its own solutions and MVPs - sourcing engines, portfolio trackers and diligence agents that the firm now depends on daily. We are hiring one go-getter AI-native engineer to own data, IT and AI resources at Titan: to develop the solutions the team needs, decide which prototypes merit investment, move them into a secure production environment, and build the architecture that enhances Titan’s AI-native capabilities.

What will you do?

- Build solutions in collaboration with the team. In many cases, you will own a problem from the requirement itself as the sole builder. In others, you will take a prototype the team has already built into production, working alongside whoever built it, understanding the intent, and agreeing jointly on what to harden, what to rebuild and what to retire.
- Own the operational foundation end to end: deployment, CI/CD, monitoring, backups, secrets management, role-based access and audit logging.
- Build the evaluation and guardrail layer. An agent that is correct eighty percent of the time on deal data remains a liability until its accuracy can be measured and bounded.
- Design scalable APIs and data models (Node.js / Express.js, MongoDB) and clear, responsive interfaces (React / Next.js).
- Own production incidents personally, from alert through resolution to post-mortem.
- Integrate LLMs and AI APIs into production applications: retrieval, agents, tool use,



and structured extraction from unstructured documents.
- Work AI-natively yourself. Coding agents, evals and automation are how we expect this role to ship at the pace of a small team rather than one person.
- Maintain our data posture under India's DPDP Act and under LP security review.
- Work from problem definition rather than a specification. Translate the requirements of the investment and operations teams into technical solutions, and challenge them where the trade-offs warrant it.
- Raise the technical capability of the team. Review what non-engineers ship, provide patterns and guardrails, and ensure the team can keep prototyping.
- Study how leading teams are deploying AI, and bring the architectures worth adopting back to Titan Capital.

What are we looking for?

- An AI-native builder. You reach for LLMs, coding agents and automation as a default working method, not as an experiment..
- Demonstrated experience shipping LLM-based systems into production, with real users depending on them. Fluency in prompt engineering, retrieval design and evaluation. You can distinguish a production-ready model output from one that is not.
- Backend, where this role sits heaviest. Three plus years of experience building APIs and data models in Node.js / Express.js with MongoDB, working with SQL, and handling messy third‑party data. Job queues, retries, rate limits and schema drift are familiar territory.
- Frontend, React / Next.js.



Pixel-perfect design work is not required. Interfaces that are fast, clear and difficult to misuse are.
- Networking and infrastructure fundamentals. HTTP, DNS, TLS, VPCs, load balancing, authentication flows and latency budgets. You can trace a slow request from browser to database and account for the time.
- Genuine DevOps competence, including hands-on responsibility for systems running in production.
- A working security instinct. You understand the cost of a credential in a repository, the case for role-based access, and the response required when a vendor token is compromised. Application security or ethical hacking experience is an advantage.
- Comfort inheriting code you did not write. Some of your work begins as someone else's prototype, and you can read it, respect the intent behind it, and rebuild it constructively.
- An ownership mindset that does not depend on structure around it.
- Robust collaborative skills. You can sit with a team member, extract the real requirement from an imprecise brief, and explain a technical trade-off without jargon.

Nice to have: founding engineer experience, internal tooling or data infrastructure, entity resolution and deduplication, exposure to venture capital or private markets. Interview process?

- Initial screening: A conversation to understand your background, experience, and fit for the role.
- Technical rounds: 1-2 technical discussions, which may include live coding, system design, and practical problem-solving exercises.
- Take-home assignment: A practical assignment designed to understand how you approach an open-ended problem and translate it into a working solution.
- Final conversations: 1-2 discussions with the leadership team to assess mutual fit, working style, and alignment with the role.

📌 Full Stack AI Engineer (Gurugram)
🏢 Titan Capital
📍 Gurugram