Strategic Deployment Engineer, Chanakya

Posted Yesterday
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2 Locations
In-Office
Mid level
Artificial Intelligence • Software
The Role
Own end-to-end deployment of Sarvam's full AI stack in on-prem, air-gapped, and classified client environments. Act as technical SPOC from scoping to steady-state, diagnose integration and inference failures, manage deployment pipelines and model serving, drive adoption via training/documentation, and feed field learnings back into product.
Summary Generated by Built In
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

Strategic Deployment Engineers are Sarvam's forward-deployed technical assets. Embedded with clients, you own the full lifecycle of AI system deployments — including in air-gapped, classified, and on-prem environments — and in complex enterprise accounts where standard playbooks don't apply. You are the technical SPOC for your assigned accounts. Success is measured by whether the system works, the client trusts us, and the deployment creates durable capability — not by ticket closure. You will operate with autonomy and carry real accountability: for the system, for the relationship, and for outcomes.

What You'll Do
  • Own end-to-end deployment of Sarvam's full AI stack in client environments — on-prem, air-gapped, classified infrastructure, and complex enterprise accounts

  • Serve as technical SPOC for assigned accounts, from scoping and PoC through to steady-state operations

  • Diagnose and resolve integration failures, model drift, inference issues, and infrastructure breakdowns without escalation ladders

  • Surface field learnings that feed back into the product layer and replicable deployment library

  • Manage deployment pipelines, model serving, and environment configuration in non-standard, constrained settings

  • Drive client-side adoption through documentation, training, and operational handover where required

  • Own client satisfaction (CSAT, time-to-value, uptime) for your accounts; flag risks before they become escalations

What We're Looking For
  • 3–6 years in software or ML engineering, with at least one full-cycle on-prem or enterprise deployment delivered end-to-end

  • Production-grade experience in Python, Docker, Linux systems administration, REST APIs, and CI/CD pipelines

  • Hands-on experience with LLM inference stacks — vLLM, TGI, Ollama, or equivalent — and RAG architectures and vector stores

  • Experience deploying in constrained environments: air-gapped networks, limited connectivity, non-standard hardware, or complex regulatory requirements

  • Full-stack debugging instinct — comfortable diagnosing across infrastructure, networking, and application layers without a specialist to hand

  • Demonstrated ability to ship and maintain a working system end-to-end in environments where reliability was non-negotiable

  • Proven ability to navigate ambiguous client requirements and make the call without explicit guidance

Signals We Look For
  • You've shipped and maintained a working system end-to-end in environments where the bar for reliability was non-negotiable

  • You've navigated ambiguous client requirements and made the call without explicit guidance

  • Open-source projects, side products, or entrepreneurial stints that demonstrate technical craft and sustained follow-through

Who You Are
  • You treat ambiguity as the baseline — you don't need perfect information to move

  • You own outcomes, not tasks. If something is broken in your line of sight, you fix it, flag it, or escalate — you don't wait to be asked

  • You operate in high-pressure, forward-deployed environments without daily oversight, and you thrive there

  • You are available and responsive when your clients are

  • You have a strong bias for action and an equal openness to being wrong

  • You are intellectually restless — the hardest, least-understood problems are the ones you find most energising

Bonus Points
  • Prior experience with strategic or complex enterprise accounts

  • MCP server experience or familiarity with agentic frameworks

  • Open-source projects, side products, or entrepreneurial stints that demonstrate technical craft and sustained follow-through

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.

Skills Required

  • 3-6 years in software or ML engineering with at least one full-cycle on-prem or enterprise deployment delivered end-to-end
  • Production-grade experience in Python
  • Production-grade experience with Docker
  • Linux systems administration experience
  • Experience with REST APIs
  • Experience with CI/CD pipelines
  • Hands-on experience with LLM inference stacks (vLLM, TGI, Ollama or equivalent)
  • Experience with RAG architectures and vector stores
  • Experience deploying in constrained environments (air-gapped networks, limited connectivity, non-standard hardware, regulatory constraints)
  • Full-stack debugging across infrastructure, networking, and application layers
  • Demonstrated ability to ship and maintain reliable end-to-end systems in production
  • Ability to navigate ambiguous client requirements and make autonomous decisions
  • Prior experience with strategic or complex enterprise accounts
  • MCP server experience or familiarity with agentic frameworks
  • Open-source projects, side products, or entrepreneurial stints demonstrating sustained follow-through
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The Company
HQ: Bangalore, Karnataka
50 Employees
Year Founded: 2023

What We Do

We are an AI/ML research and development company on a mission to build reliable, performant, enterprise-grade AI systems at scale for India. We are committed to build the full-stack for generative AI for the rich & diverse landscape of India, mainly investing in: 1) Models: developing both efficient large scale Indic language models as well as bespoke enterprise models 2) Platform: building an enterprise-grade platform that empowers organisations to develop and ship creative and performant genAI applications at scale 3) Ecosystem: contributing to open-source models and datasets, as well as leading efforts for large scale data curation in public-good space

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