Senior Forward Deployed Engineer

ten8labs; Gurugram District; Hybrid; INR 2,500,000 - 6,000,000; Full time

Benefits offered by this job

Founding-team ESOPs

Courses and certifications budget

Direct work with founders

Job summary

ten8labs seeks a founder-mentored engineer to own client engagements from initial discovery to production AI solutions integrated with clients’ ERP, CRM, and databases. You will lead small teams, shape scope, pricing, and delivery while ensuring value, reliability, and cost efficiency.

You will prototype rapidly, deploy in client environments (cloud, private cloud, or on-premises), and drive adoption by training users and handing over ownership to the client.

Qualifications

• 5+ years in software/ML engineering or solutions engineering with client-facing work.
• At least one AI/data system shipped to production in a real business.
• Proficient in Python and another language (TypeScript/Java/Go).
• Experience with production infra: Docker, CI/CD, and at least one major cloud.

Responsibilities

• Frame client problems with owners and operators and map workflows.
• Prototype and deliver a working version to clients within days onsite.
• Architect AI agents, RAG and workflow systems balancing accuracy, latency, cost and data privacy.
• Deploy into client environments—cloud, private cloud or on-premises—with logging and guardrails.
• Set up evaluations and monitoring to prove system performance and adapt accordingly.
• Train users and hand over to client owners; monitor adoption post go-live.
• Mentor entry-level engineers and build reusable playbooks and accelerators.

Skills

Python

TypeScript

Go

APIs

LLM

Docker

CI/CD

Kubernetes

Cloud

Tools

LangGraph

LlamaIndex

Semantic Kernel

Job description

You will own client engagements from the first conversation to a system people rely on. You frame the problem with the business owner, design the solution, build the hard parts yourself, and lead one or two engineers to production. You are measured on outcomes the client feels: time to value, adoption, reliability and cost, not hours or milestones.

This is a founding role in our forward-deployed practice. You will help set how we scope, price, hire for and run engagements.

What you'll do

• Frame the problem. Run discovery with owners and operators, map how the work actually flows, and choose where AI should act and where a human stays in charge
• Prototype fast. Get a working version in front of the client in days, onsite, and iterate with them
• Design and build for production. Architect AI agents, RAG and workflow systems that meet real limits on accuracy, latency, cost and data privacy; write the critical code yourself
• Deploy into the client's environment. Cloud, private cloud or on-premises, integrated with their ERP, CRM, databases and identity systems, with logging, guardrails and human review where it matters
• Prove it works. Set up evaluations and monitoring that show whether the system does its job, and act on what they show
• Drive adoption. Train users, hand over to a named owner on the client side, and track usage after go-live
• Lead and mentor. Guide entry-level FDEs on design, code quality and client conduct
• Build the practice. Turn each engagement into reusable components, playbooks and accelerators, and bring field learnings to our products
• Support the business. Help scope and estimate proposals, join sales conversations as the technical lead, and spot follow-on work

What you need

• 5+ years in software engineering, ML engineering or solutions engineering, including client-facing or customer-embedded work
• At least one AI or data system you took from scoping to production in a real business, and can walk us through in detail
• Strong Python and one more language (TypeScript, Java or Go); APIs, microservices and enterprise integrations
• Deep applied LLM experience: RAG, vector stores, context engineering, structured outputs, tool use and agent frameworks such as LangGraph, LlamaIndex or Semantic Kernel
• Production infrastructure: Docker, CI/CD and one major cloud (AWS, Azure or GCP); comfort with Kubernetes and Linux
• Experience with evaluation, monitoring and cost and latency trade-offs for LLM systems
• The judgment to say no to the wrong project and the communication to explain why to a business owner

Nice to have

• Deployments in constrained or regulated settings: BFSI, healthcare, manufacturing or on-premises and private-cloud setups
• Self-hosted model serving (vLLM, TGI, Ollama) and open-weight models
• MCP servers, Claude, OpenAI, Gemini or Azure OpenAI in production
• A founder, early-startup or consulting background

How we'll measure success

In 3 months

You have led one engagement to a production go-live

In 6 months

You run two engagements in parallel, each with a measurable result for the client

In 12 months

You have hired or grown at least one FDE, and our playbook and reusable library carry your work

About ten8labs

ten8labs puts AI into production inside Indian and USA businesses. We are a deep-tech AI product lab with offices in Gurugram and Austin, Texas, and we work forward-deployed: our engineers sit with the client, find the work worth automating, build it into their real systems, and stay until people use it every day.

Most AI projects in Indian mid-market companies stall between the demo and daily use. The data lives in spreadsheets, ERPs and communication threads. Our forward deployed engineers close that gap.

We also build our own product, ten8brain, a risk intelligence platform. What we learn in the field shapes it, and engineers who join now help define how the practice works.

What we offer everyone on the team

• Real ownership from week one: your work ships into a client's business, not a backlog
• Exposure to many industries and problems in your first year
• Founding-team ESOPs
• Direct work with the founders on scoping, delivery and product
• A budget for courses, model credits and certifications