Forward Deployed Engineer - India

About the role

Cursor is hiring a Forward Deployed Engineer in India to work inside enterprise engineering teams and ship production AI coding workflows built on Cursor.

<p>Cursor builds an AI-powered code editor for professional developers, with the stated mission of automating coding. Its Forward Deployed Engineers work directly alongside customer engineering teams to find what is slowing them down and to build Cursor-based workflows that improve how those teams ship software.</p><p>The role is end-to-end: you run discovery, design a practical solution, deliver an early version quickly and then harden it for real use with monitoring and a rollout plan. Cursor is explicit that this is not a demo position; you are accountable for systems that run in production. The posting lists Bengaluru, New Delhi and Mumbai as the locations for this role.</p><p>This listing was verified on the employer's own careers page on 6 October 2026. Please read the full posting and apply directly on the employer's site; Cloud Soft Solutions does not handle applications for this role.</p>

Responsibilities

<ul><li>Run discovery sessions with customer engineers to pin down the true bottleneck and agree on measurable success criteria</li><li>Design and build Cursor-powered workflows such as large refactors, code migrations, pull-request review loops and pipelines that turn incidents or specs into code</li><li>Deliver a working first version within days, then make it dependable over the following weeks through staged rollout, monitoring and iteration</li><li>Own production quality, including tracing, evaluations, metrics, debugging model behaviour and balancing latency against cost</li><li>Work hands-on in code with senior platform and engineering leaders while explaining trade-offs and outcomes clearly</li><li>Package what you build into reusable patterns and feed improvements back into the core Cursor product</li></ul>

Requirements & qualifications

<ul><li>Comfort working in ambiguity and turning loosely defined problems into scoped, shipped systems</li><li>Experience building and owning AI-native workflows in production (beyond prototypes), including debugging real model failures</li><li>Confidence leading discovery conversations and taking responsibility for customer results</li><li>Willingness to build across the stack: frontend, backend, infrastructure or prompt iteration as needed</li><li>Prior experience with production reliability: metrics, alerting, safe rollouts and incident response</li><li>Strong Python and TypeScript/JavaScript, plus the ability to pick up unfamiliar stacks quickly</li></ul>

Why this role in 2026

<p>This is a hands-on FDE role in which success is judged by working systems inside customer codebases rather than by presentations. You get direct exposure to how large engineering organisations adopt AI coding tools, and the posting expects you to own evals, tracing and cost/latency decisions, which are core production-AI skills. Many of the skills these roles call for, such as production LLM workflows, evals and customer-facing delivery, are covered in Cloudsoft's <a href="/programs/fde-forward-deployed-engineer-course/">FDE PRO course</a>.</p>

Application tips

<ul><li>Lead with one or two AI workflows you shipped to production and describe how you measured whether they helped</li><li>Mention concrete reliability work such as alerts you set up, a rollout you staged or an incident you handled</li><li>Show breadth: note any frontend, backend, infrastructure and prompt work you have done yourself</li><li>If you have used Cursor or similar AI coding tools on large refactors or migrations, describe the outcome</li><li>Keep your resume specific about Python and TypeScript/JavaScript projects, since both are named in the posting</li></ul>

Interview preparation

<p>Expect to discuss how you would scope a vague customer problem, design an AI-assisted engineering workflow and take it from first version to production. Prepare to talk through evals, tracing, model failure modes and latency/cost trade-offs, and practise explaining technical choices to senior engineering leaders. Useful reading: our <a href="/interview-questions/agentic-ai-interview-questions-2026/">agentic AI interview questions</a>, the <a href="/blog/fde-engineer-skills/">FDE engineer skills guide</a> and our article on <a href="/blog/fde-ai-poc-to-production/">taking AI from POC to production</a>.</p>

Career growth

<p>The posting describes turning field work into reusable patterns and product improvements, so the role builds a track record in both customer delivery and product influence. Experience embedding with enterprise engineering teams on AI tooling is directly relevant to senior FDE, solutions architecture and applied AI engineering paths.</p>