Sarvam AI is a startup building a sovereign, India-centered AI stack and multilingual models for government and enterprise use.
About Sarvam Sarvam is building the bedrock of Sovereign AI for India. The company is developing India’s full-stack sovereign AI platform, building across research, models, infrastructure and applications with a singular focus on making AI genuinely work for India. Sarvam works with leading enterprises and public institutions and is backed by Lightspeed, Peak XV, and Khosla Ventures. Sarvam partners with India’s leading brands, including Tata Capital, SBI Life, CRED, IDFC, and LIC. ABOUT THE ROLE We’re looking for an FDE to work directly with enterprise clients integrating our platform into their business workflows. You will be embedded with clients - understanding their operational processes, configuring the platform for their needs, debugging issues end-to-end, and ensuring they achieve high-quality outcomes across their use cases. This is a hands-on, client-facing engineering role. You’ll split time between writing code (integration scripts, platform configuration, bug fixes) and working directly with client engineering and business teams. You’ll develop deep expertise in the platform and become the trusted technical point of contact for your accounts. WHAT YOU'LL DO - Own the technical arc of customer engagements, from scoping the solution through to the system running in production. - Design end-to-end AI systems that meet real reliability, latency, accuracy, and cost constraints. Make the architectural decisions that hold up at production scale. - Build the system yourself, across whatever the stack and product call for. Engagements range from voice and conversational systems at enterprise customers, to developer tooling around Sarvam's APIs, to translation and dubbing pipelines for media customers, to agentic workflows and the MCP servers and infrastructure that underpin them. FDSEs are hands-on engineers, not technical project managers. - Deploy into the customer's environment, working closely with their engineering team on data, infrastructure, and integration constraints. - Set up evaluations that meaningfully measure whether the system is doing its job, and iterate based on what the data shows. - Work across engagements over time, picking up new domains, products, and customer contexts as priorities shift. - Bring what you learn in the field back to Sarvam's product and research teams, and shape what gets built next. WHO WE'RE LOOKING FOR We're hiring across levels, 4+ years of experience would be preferred. Strong AI fundamentals, range across the stack, high agency, and a clear track record of shipping matter more than years of experience. We're looking for engineers with a technical degree in Computer Science, Electrical Engineering, or equivalent. - High agency. You unblock yourself. You don't wait for direction. When a customer is stuck or an engagement is ambiguous, you figure out what to do next and do it. - Strong AI fundamentals. You deeply understand how LLMs and agents work in production: context engineering, memory, RAG, tool use, structured outputs, and the failure modes that actually show up at scale. You've worked with agentic frameworks (LangGraph, LlamaIndex, Google ADK, or equivalent) and with both open and closed source models. - Evals mindset. You know how to evaluate agentic AI systems. You can set up eval pipelines, define metrics that matter for a given use case, and have clear opinions on what good evaluation looks like versus what's just noise. - Systems thinker. You can reason about architecture, reliability, scale, trade-offs, and failure modes across services, databases, queues, and messaging systems (Kafka, SQS, or equivalent). You make design decisions that hold up at production load, not just in a notebook. - Range, and the ability to pick things up fast. Strong Python, comfortable across backend, data pipelines, and cloud infrastructure (AWS, GCP, or equivalent). You can be useful on a voice agent, a backend service, an evaluation harness, or a developer-facing integration. When you don't know a stack, you pick it up in hours, not weeks. - Builder who stays current. You ship. You have things on the internet, in production, in open source, or in personal projects, that prove it. You follow the frontier closely, try new tools as they launch, and have strong opinions on what's actually useful versus hype. - Customer instinct. You can sit in a room with a customer's engineering team, understand what they actually need, and translate that into clean technical work. You communicate clearly with technical and non-technical stakeholders. EVEN BETTER IF - You've built and deployed AI agents into production, where they did real work for real users. - You have experience deploying AI systems in regulated environments (BFSI, public sector) or with on-premise / VPC deployments. - You have a history of side projects, open source contributions, or shipped products. - You've worked in a customer-facing or product-embedded engineering role before. - You've used Sarvam's models or APIs in your own projects. Why Sarvam? Sarvam is a fast-moving, high talent-density team building full-stack AI for India, working on problems that push the frontiers of AI with real population-scale impact. - Work alongside researchers, engineers, builders, and business leaders who move fast and hold each other to a very high bar - High ownership and high impact, from day one - Everything we do is AI-first, from the way we build and ship to the way we think about problems - You can work on problems that could change how an entire country learns, works, and communicates If you want to work on problems at the frontier of AI in India, Sarvam is the place to be.