Strategic Deployment Engineer

About the role

Strategic Deployment Engineers are forward‑deployed technical assets who own the full lifecycle of AI system deployments in client environments, including on‑prem, air‑gapped and classified settings.

Key responsibilities

• Own end‑to‑end deployment of Sarvam’s full AI stack in on‑prem, air‑gapped, classified and complex enterprise accounts.
• Serve as the technical single point of contact for assigned accounts from scoping and PoC through steady‑state operations.
• Diagnose and resolve integration failures, model drift, inference issues and infrastructure breakdowns without escalation.
• Manage deployment pipelines, model serving and environment configuration in constrained settings.
• Drive client‑side adoption through documentation, training and operational handover.

Required profile

• 3–6 years of software or ML engineering experience with at least one full‑cycle on‑prem or enterprise deployment.
• Proven ability to ship and maintain reliable systems in high‑pressure, ambiguous client environments.
• Experience navigating ambiguous requirements and making decisions without explicit guidance.

Required skills

• Python programming.
• Docker containerisation.
• Linux systems administration.
• REST APIs and CI/CD pipelines.
• LLM inference stacks such as vLLM, TGI or Ollama.
• RAG architectures and vector stores.