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Founding AI Engineer Location: Gurugram, India Full-time About Zstate As AI models become increasingly capable, the industry needs better ways to measure reasoning, reliability, and real-world performance. Zstate AI is building the evaluation and posttraining infrastructure powering the next generation of AI systems. We create expertdriven benchmarks, reward signals, RL environments, and highquality datasets that help frontier AI models become more capable, reliable, and trustworthy across diverse realworld domains. Zstate AI is led by a founding team from IITs, IIMs, and DCE, bringing together deep technical and strategic expertise to build categorydefining AI infrastructure. We are backed by Giraffe Studios, a venture studio focused on deeptech startups founded by Himanshu Aggarwal (Cofounder & CEO, Aspiring Minds) and Mohit Tandon (Cofounder, Delhivery). As one of our earliest hires, you'll work directly with the founders to solve challenging engineering problems and help shape both the product and the company from day one. What this role looks like You are one of the first engineers at Zstate AI. Our enterprise clients hand us real workflows that take too much expert time, and your job is to turn those workflows into agents that work. You will design and build multistep agents that use tools, retrieve context, hold state, and complete the work end to end, from an early prototype to a production deployment the client actually relies on. A day in the life Spend your mornings sketching agent architectures on a whiteboard or in a notebook: subagents, routing, handoffs, planning, and state management for long tasks. Build those agents with LLMs, tool use, retrieval, and memory in LangChain, LangGraph, or whatever framework fits the problem best. Write evaluation frameworks that let you iterate on prompts and architecture using LLMasjudge and deterministic evaluators, so you can prove the agent is improving. Integrate the agent with the client systems it needs to talk to: APIs, databases, vector stores, MCP, and other tool integrations. Ship it to production, then set up observability, tracing, logging, and error analysis so you can watch it behave in the real world. Sit with clients and domain experts, translate their workflow into a spec, and keep iterating as production feedback comes in. Who you are 3-8 years of experience in backend or fullstack engineering, with a real track record of shipping production systems. At least one year of handson AI engineering: building agents, LLM workflows, or similar. Practical experience with LangChain, LangGraph, or similar frameworks, including tool use and multistep reasoning. A habit of using prompt engineering and evaluation frameworks to iterate on behaviour with real feedback. Strong proficiency in Python and/or TypeScript, plus APIs, system design, and preferably cloud experience. The instinct to own a project end to end, from architecture to a client using it in production. High ownership, strong execution, and the tendency to improve systems without waiting to be asked. Extra credit Experience with RAG patterns, vector stores, and knowledge retrieval. Experience with agent observability tooling like LangSmith and debugging agents in production. Experience working directly with enterprise clients on technical scoping and delivery. Exposure to RLHF, SFT, or posttraining workflows. Why this matters Competitive compensation for the right candidate. You will ship agentic systems that real enterprise clients use in production, not features that sit on a roadmap. Early access to the techniques and frameworks behind the most advanced agentic systems in the world. High ownership from day one: no ticket queues, no layers, direct impact. A culture that rewards engineering and research depth and curiosity over credentials. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.