Top Tech Jobs & Startup Jobs

Senior client-facing role owning GTM, pipeline, and account strategy for defence and strategic clients. Build decision-level relationships, translate technical AI capability into proposals, lead RFI/RFP and PoC scoping, negotiate commercially, collaborate with engineers and product, manage account health, and surface requirements and competitor/policy shifts.

Design and implement production-grade backend systems for on-prem and constrained deployments: MCP servers, ingestion pipelines, agentic backends, APIs, containerised tooling, and operational/debugging support for deployments.

Build distributed microservices and task-graph execution engines for LLM-driven workflows. Integrate multiple LLM providers and tools, implement gRPC/REST APIs, document ingestion and embedding pipelines, vector search knowledge bases, safe code-execution sandboxes, and contribute to MCP server implementations while maintaining containerized infrastructure and observability.

Own financial reporting, controllership, compliance, and accounting operations. Manage month/quarter/year close, audits, tax filings, AP/AR/payroll, build management reporting, automate finance processes, and support fundraising and international consolidation.

Own the full enterprise sales cycle: prospect, engage C-level stakeholders, conduct discovery, negotiate and close deals. Collaborate with BDRs/SDRs, marketing, and product, maintain CRM discipline, forecast pipeline, and ensure smooth handoffs to customer success to drive acquisition and long-term partnerships.

Lead go-to-market and positioning for enterprise AI products. Build vertical narratives, sales enablement content, case studies, demos, and ROI benchmarks. Partner with product and sales, gather field insights, and support long-cycle enterprise deals in financial services, public sector, and healthcare.

Design, build, and maintain ML systems for a multilingual dubbing platform. Develop automated validation, monitoring, and evaluation workflows. Optimize inference pipelines for performance, cost, and reliability, run experiments, and collaborate with product and engineering to productionize models.

Build and deploy vision-language models across the full lifecycle: data pipelines, training/fine-tuning on GPU clusters, evaluation and benchmarks, inference optimization, production integrations, and client-facing solutions for document processing and visual search.

Work with product and customers to design, build, deploy, monitor, and iterate production-grade agentic AI systems across channels. Implement multi-agent architectures, data pipelines, integrations, and evaluation metrics; own client engagements from kickoff to go-live.

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.