Job Description
About Darwinbox
Darwinbox is Asia's fastest-growing HR technology platform, designing the future of work by building the world's best HR tech, driven by a fierce focus on employee experience and customer success, and continuous, iterative innovation. We are the preferred choice of 1200+ global enterprises to manage their 4.5million+ employees across 130+ countries. Darwinbox's new-age HCM suite competes with local as well as global players in the enterprise technology space (such as SAP, Oracle, and Workday). The firm has acquired notable customers ranging from large conglomerates to unicorn start-ups: DP World, JG Summit, Starbucks, DLF, JSW, Adani Group, Crisil, CRED, Vedanta, Mahindra, Glenmark, Mitra Adiperkasa, EFS Facilities Management, VNG Corporation, and many more.
Our vision of building a world-class product company from Asia is backed by marquee global investors like Microsoft, Salesforce, Sequoia Capital, TCV, KKR, and Partners Group.
Why Join Us?
The way Darwinbox is evolving is unlike anything we have seen before. AI is transforming our platform, our customer experience, and the future of HR technology; this role will be at the forefront of turning that vision into reality. You will help bring our AI ambition to life in the field, working on high-impact problems with strategic customers while shaping how Darwinbox scales its next generation of intelligent products. This is the founding cohort of an entirely new function at Darwinbox — the first FDEs will shape how the team operates, which customer engagements get the embedded model first, and how it scales. You will work zero layers removed from the customer and touch a stack broader than any pure product engineering role allows: the Darwinbox platform, Python at production scale, the LLM stack of your choice (Claude, GPT, Gemini), MCP servers, agent frameworks, and whatever the customer happens to run on their side.
You’ll experience a culture of:
Disproportionate Rewards for top performance
Accelerated Growth in a hyper-growth environment
Continuous Learning and Professional Development
Meaningful Relationships and a Collaborative Environment
🚀 Role Overview
The Forward Deployed Engineer embeds with Darwinbox's most strategic enterprise customers to ship production-grade AI agents and Agentic Flows on the Darwinbox HCM platform inside each customer's environment. The role centres on three skill areas: production Python engineering for AI agents, deployment of LLM applications (prompt engineering at scale, RAG, agent orchestration, evaluation frameworks), and architecting REST API and webhook integrations with payroll, ATS, SSO/IDP, learning, and ERP systems. You will work hands-on inside customer environments on HR workflow problems that exceed the platform's standard configuration surfaces.
🎯 What Success Looks Like in This Role
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.
📋 Requirements & Qualifications
Required
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.
