Applied AI Engineer - Bangalore Location - Hybrid

Forward Deployed Engineer, Applied AI

Genpact • AI Value Studio • Reports into an Applied AI Lead

About the Role

As a Forward Deployed Engineer (FDE) on Genpact's Applied AI team, you will embed directly with our most strategic enterprise customers to ship production AI applications that solve real business problems. You will spend most of your week in Claude Code and at the client, turning ambiguous business problems into working software often within days, not months.

This is the role at the front line of how the world's largest companies actually adopt AI. You will own a workstream end-to-end: sitting with client teams to understand their workflows, designing the solution, building it, demoing it, and getting it into production. You will collaborate closely with Anthropic, our other AI partners, and Genpact's industry and delivery teams to make sure what you build lasts after you leave.

We expect our FDEs to operate autonomously, thrive in ambiguity, and represent Genpact at the highest level inside customer environments.

What You Will Do

• Work inside customer systems to build production applications with Claude and other frontier models, making sure they meet real customer requirements.
• Deliver technical artifacts: agentic workflows, MCP servers, sub-agents, agent skills, evaluation harnesses, and the integrations that wire them into the client's stack.
• Own a workstream end-to-end — discovery, architecture, build, demo, handoff. Make trade-offs between scope, speed, and quality in real time.
• Co-design solutions with client stakeholders at the Director and VP level. Sit in the client's room, take direction, and turn it into shipped code by the end of the day.
• Provide white-glove deployment support inside enterprise environments. Be the person the client trusts when something has to work.
• Identify and codify repeatable deployment patterns. Contribute reusable assets — code, prompts, skills, runbooks, reference implementations — back to the Genpact Applied AI practice.
• Stay current with the latest in LLM capabilities, agent frameworks, and the AI product development stack. Bring field insights back to our product and partner teams.

What We Are Looking For

• 4+ years in a technical, customer-facing role — Forward Deployed Engineer, Solutions Engineer, Solutions Architect, or software engineer with consulting experience. Former technical founders are strongly encouraged to apply.
• Daily, hands-on working fluency with Claude (or a comparable frontier LLM) as a build tool — not as a chatbot. You use it to ship every day.
• Production experience with LLMs: advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills in Python and, ideally, one or more of TypeScript, JavaScript, Java, or SQL. Experience shipping production applications.
• Track record of shipping something a customer or end-user actually paid for, used, or measured — a product, an internal tool, a notable open-source project, or a demo that closed a deal.
• Can hold your own in a client conversation with senior stakeholders. You do not need a PM to translate.
• High agency — comfortable navigating ambiguity in complex organizations and turning vague business problems into concrete technical plans.
• High cooperation mindset — you can balance competing priorities across customer teams, Genpact delivery, and partners with integrity.

Bonus

• Domain depth in a regulated industry: life sciences, financial services, healthcare, insurance.
• Hands-on experience with MCP, agent frameworks (Claude Code, Cursor, LangGraph, etc.), evaluation tooling, or LLM observability.
• Background in a top-tier product, startup, frontier-lab, or consulting environment — or a credible self-built equivalent.
• Experience operating in hybrid onshore/offshore delivery teams.
• Familiarity with security, privacy, and compliance considerations for enterprise AI deployment.

What We Are Not Requiring

• A specific degree. No degree requirement, no preference for any particular institution.
• Specific certifications. The bar is the work, not the credentials. Anthropic, AWS, or other AI certifications are nice to have, not required.
• A traditional ML or PhD background. We are hiring builders who use LLMs, not researchers who train them.

Interview Process

Our process is designed to evaluate the work, not the resume:

• Initial conversation with the hiring manager (45 min).
• Portfolio walkthrough — bring something you built recently with Claude or a comparable model and walk us through how you built it (45 min).
• Live build exercise — a 90-minute pair-build or take-home on a realistic client problem using Claude. Highest-signal step in our process.
• Client simulation — a working session with Genpact senior delivery and a simulated client stakeholder.
• Final conversations with practice leadership.

Location and Travel

US-based with hybrid working model. 25–50% travel to client sites and Genpact delivery centers.