Senior FDE | 4- 7 Years | AI-powered customer engagement for BFSI

Geektrust; Bengaluru; Presencial; INR 3.000.000 - 5.600.000; Jornada completa

Descripción de la vacante

Geektrust in Bengaluru, India seeks a Senior Forward Deployed Engineer to own our most complex customer deployments end-to-end, acting as the technical lead for key BFSI accounts. You will architect solutions, write and optimise production prompts, and drive each deployment to live production across multiple accounts.

You’ll be the technical face of Geektrust in front of senior enterprise stakeholders, mentoring mid-level and junior engineers and shaping deployment playbooks and best practices.

Formación

• 4-5+ years building and shipping production software, with meaningful time in customer-facing or forward-deployed roles.
• Hands-on experience building with LLMs / GenAI in production (agents, RAG, tool calling, evaluations).
• Experience with enterprise BFSI, fintech, or regulated domains is a strong plus.
• Strong Python and software engineering fundamentals; clean, maintainable, well-tested code.

Responsabilidades

• Own the most complex, high-visibility deployments end-to-end across multiple accounts.
• Architect agent solutions; design conversations, configure tools, and integrate with client systems.
• Lead prompt engineering for Voice and In-App AI Agents and optimise production prompts.
• Drive go-live, reliability, latency, and quality in production environments.
• Lead technical integrations via APIs, SDKs, and telephony; mentor junior engineers.
• Run solutioning sessions, demos, and workshops with enterprise stakeholders.
• Define standards, deployment playbooks, and review team work to raise delivery quality.
• Collaborate with product/engineering to turn field learnings into platform improvements.

Conocimientos

Python

LLM/GenAI

APIs & integration

Cloud AWS

LLMOps

Educación

Bachelor's degree in Computer Science or Engineering

Herramientas

AWS

SDKs

Webhooks

Descripción del empleo

We're looking for a Senior Forward Deployed Engineer to own our most complex, high-visibility

customer deployments and act as the technical lead for key BFSI accounts, taking our Voice

and In-App AI Agents from kickoff to live production and measurable business impact.

This is a hands-on, customer-facing senior engineering role, not a research or purely advisory

one.

You’ll architect the solution, write and optimise the production prompts and conversation design, build the integrations, run evaluations, and drive each deployment to go-live, often

across multiple accounts in parallel. You’ll be the technical face of Revrag AI in front of senior

enterprise stakeholders.

Key Responsibilities

• Own the most complex, high-visibility customer deployments end-to-end, from scoping
• and solution design through integration, go-live, and measurable business impact, often
• across multiple accounts in parallel.
• Architect and build the agent solution: design conversation flows, configure tools and
• guardrails, and integrate with the client's systems for each use case.
• Own prompt engineering for Voice and In-App AI Agents: write, iterate, and systematically
• optimise production prompts and conversation design, including multilingual and
• edge-case handling, driven by evaluation frameworks.
• Lead technical integration with customer systems via APIs, SDKs, and telephony, and own
• reliability, latency, and quality in production.
• Be the primary technical owner and trusted advisor for enterprise BFSI stakeholders,
• running solutioning sessions, demos, and workshops.
• Define prompting standards, deployment playbooks, and best practices, and review other
• engineers' work to raise the delivery bar.
• Partner with product and engineering to turn recurring field learnings into platform
• capabilities, and influence the roadmap.
• Mentor mid-level and junior Forward Deployed Engineers.
• May occasionally travel to or work from client sites to support deployments, represent Revrag
• AI on-site with the customer, and help ensure smooth operations.

Required Qualifications

Experience

• 4-5+ years building and shipping production software, with meaningful time in
• customer-facing, forward-deployed, or solutions engineering roles.
• Proven track record of independently owning and delivering complex technical projects to
• production and to business outcomes.
• Hands-on experience building with LLMs / GenAI in production (agents, RAG, tool calling,
• evaluations).
• Experience working with enterprise customers, ideally in BFSI, fintech, or another regulated
• domain.

Technical Skills

• Strong Python and software engineering fundamentals, clean, maintainable, well-tested
• code.
• Strong prompt engineering and conversation design for LLM agents: system prompts, tool
• use, structured outputs, guardrails, and evaluation-driven iteration.
• Deep understanding of LLM application development and LLMOps.
• Strong grasp of APIs, webhooks, SDK integration, asynchronous processing, and backend
• Experience on cloud platforms (AWS preferred), with comfort debugging latency, reliability,
• and production observability.
• Excellent communication, able to lead customer conversations, demos, and technical
• workshops with senior stakeholders.

What We’re Looking For

You’re a great fit if you:

• Have independently taken complex systems from ambiguity to production and owned the
• outcome.
• Are as comfortable writing and debugging prompts and agent logic as integrating backend
• systems.
• Set a high bar for quality and can raise it for others.
• Communicate with credibility in front of senior enterprise stakeholders.
• Thrive where there's no playbook, and create the playbook others follow.
• Care deeply about customer success and business impact.

Success in This Role

You’ll be successful if you:

• Take flagship BFSI deployments live faster and with higher quality, driving measurable
• accuracy, latency, and conversion gains.
• Become the trusted technical partner for key accounts.
• Define the prompting and deployment standards the Forward Deployed Engineering team
• runs on.
• Turn field learnings into platform improvements.
• Level up the team through mentorship and reviews.