Forward Deployed Engineer

What You Will Do

Embed with 2–3 strategic enterprise customers in parallel as the technical owner of the Darwinbox deployment in their environment.

Run discovery with CHROs, HRBPs, and HRIS leads to surface the real problem behind the stated ask and translate it into a working technical design.

Deliver a working prototype within ~1 week of engagement kick-off, codify repeatable deployment patterns, and channel field insights into the Darwinbox platform roadmap.

Design and ship production-grade AI agents on the Darwinbox platform for HR workflows including leave, performance, attendance, onboarding/exit automation, and HR decision support.

Architect custom integrations between Darwinbox and customer-side payroll, ATS, SSO/IDP, learning platforms, and ERP stacks using REST APIs, webhooks, and event-driven patterns.

Travel 25–40 percent of the time to customer sites across India, Southeast Asia, and the Middle East as required.

Required

What we are looking for

Hands-on production Python engineering for enterprise SaaS, integrations, and AI agent development.

Production deployment of LLM applications: prompt engineering at scale, RAG pipelines, agent orchestration, and evaluation frameworks.

REST API and webhook integration design for systems interoperability (payroll, ATS, SSO/IDP, learning, ERP) with production-grade auth.

Customer discovery and technical translation with senior enterprise stakeholders (CHROs, HRBPs, HRIS leads).

Production LLM experience and willingness to travel 25–40 percent — candidates with only academic/demo AI exposure or hard travel constraints are unlikely to be the right fit.

Preferred

HCM domain knowledge across payroll, performance, attendance, talent, and recruitment workflows.

MCP server implementation or agent framework experience (LangGraph, CrewAI, AutoGen) and AI observability tools (LangSmith, Langfuse).

TypeScript or Java in addition to Python; multilingual capability across Hindi, English, or additional Indian / SEA languages.

Former technical founder experience, or experience in enterprise SaaS environments such as Salesforce (Agentforce), Atlassian, Databricks, Uniphore, UnifyApps, Sprinklr, Freshworks, Zoho, or similar settings with hands- on AI deployment work.

Experience And Qualifications

1–4 years of professional software engineering experience, including customer-facing (Hard requirement).

Bachelor's degree in computer science, Engineering, or related quantitative discipline; no certifications required.