Senior Gen AI Engineer

at TalentXO

Senior Gen AI Engineer

TalentXO

Company

Home

Senior Gen AI Engineer

at TalentXO

Posted by tabbasum shaikh

4 - 7 yrs

₹34L - ₹40L / yr

Bengaluru (Bangalore)

Skills

Python

LLM

OpenAI

Gemini

RAG

Retrieval Augmented Generation (RAG)

IITs

BITS

NITs

IIITs

Role & Responsibilities

As a Senior GenAI Engineer you will own the AI layer of our product — building the features that make Zenskar intelligent. This is not a research role and not a prompt-engineering role. You will build production AI systems that enterprise clients depend on, which means reliability, observability, and rigorous evals matter as much as the AI capability itself. You own the full vertical — the model, the pipeline, and the UI.

Build and own CS Copilot — a real-time assistant for customer success teams, spanning STT pipelines, live transcription, and LLM-powered suggestions
Build LLM-powered document understanding features — extracting structured, reliable data from unstructured enterprise documents
Own AI feature UIs end-to-end — you build the interface, not just the model integration layer
Design and maintain an eval framework — define what 'working' means for each AI feature and catch regressions before users do
Drive model selection and integration decisions — choosing the right provider and approach for each use case, managing latency and cost
Own AI platform reliability — observability, fallback behaviour, and graceful degradation when models fail
Work closely with product, customer success, and the full-stack engineer — AI features only matter if they are usable and trusted by real users

THE IMPACT YOU'LL MAKE-

You will define what AI means at Zenskar — the features you ship will be the most visible and differentiated parts of the product
CS Copilot, if done well, changes how enterprise customer success teams operate every single day — this is a high-stakes, high-visibility surface
You will establish the engineering culture around AI reliability at Zenskar — evals, observability, and disciplined iteration
Your work will directly accelerate enterprise deals — AI features are increasingly a buying criterion for our clients
You will be the person who brings engineering rigour to a domain where most companies ship demos and call it a feature

Ideal Candidate

Strong Senior GenAI / AI Backend Engineer Profiles
Mandatory (Experience 1) – Must have 4+ years of total software development experience, with at least 2+ years working on AI/LLM-based features in production
Mandatory (Experience 2) – Must have strong backend engineering experience using Python (FastAPI / Django preferred) and building production-grade systems
Mandatory (Experience 3) – Must have hands-on experience building LLM-based applications, including OpenAI / Gemini / similar models in real projects
Mandatory (Experience 4) – Must have experience with RAG (Retrieval Augmented Generation) including chunking, embeddings, and retrieval pipelines
Mandatory (Experience 5) – Must have experience designing end-to-end AI pipelines, including chaining, tool usage, structured outputs, and handling failure cases
Mandatory (Experience 6) – Must have experience building agentic AI systems (multi-step workflows, tool orchestration like LangGraph / CrewAI or custom agents)
Mandatory (Experience 7) – Must have strong coding and system design skills, not just prompt engineering or experimentation
Mandatory (Experience 8) – Must have experience shipping AI features in production, not just POCs or research projects
Mandatory (Experience 9) – Must have experience working with APIs, backend services, and integrations
Mandatory (Experience 10) – Must have understanding of AI system reliability, including latency, cost optimization, fallback handling, and basic eval thinking
Mandatory (Company) – Product companies / startups, preferably Series A to Series D
Mandatory (Note) - Candidate's overall experience should not be more than 7 Yrs
Mandatory (Tech Stack) – Strong in Python + AI/LLM ecosystem, experience with modern AI tooling and frameworks
Mandatory (Exclusion) – Reject profiles that are only Prompt Engineers, Data Scientists, or Frontend Engineers without strong backend + system building experience
Preferred (Skill) – Experience with fine-tuning (LoRA / QLoRA) or open-source model deployment (vLLM / Ollama)
Preferred (Frontend) – Basic ability to build or contribute to frontend (React or similar)
Highly Preferred (Education) – Candidates from Tier-1 institutes (IITs, BITS, NITs, IIITs, top global universities)

Role & Responsibilities

Build and own CS Copilot — a real-time assistant for customer success teams, spanning STT pipelines, live transcription, and LLM-powered suggestions
Build LLM-powered document understanding features — extracting structured, reliable data from unstructured enterprise documents
Own AI feature UIs end-to-end — you build the interface, not just the model integration layer
Design and maintain an eval framework — define what 'working' means for each AI feature and catch regressions before users do
Drive model selection and integration decisions — choosing the right provider and approach for each use case, managing latency and cost
Own AI platform reliability — observability, fallback behaviour, and graceful degradation when models fail
Work closely with product, customer success, and the full-stack engineer — AI features only matter if they are usable and trusted by real users

THE IMPACT YOU'LL MAKE-

You will define what AI means at Zenskar — the features you ship will be the most visible and differentiated parts of the product
CS Copilot, if done well, changes how enterprise customer success teams operate every single day — this is a high-stakes, high-visibility surface
You will establish the engineering culture around AI reliability at Zenskar — evals, observability, and disciplined iteration
Your work will directly accelerate enterprise deals — AI features are increasingly a buying criterion for our clients
You will be the person who brings engineering rigour to a domain where most companies ship demos and call it a feature

Ideal Candidate

Strong Senior GenAI / AI Backend Engineer Profiles
Mandatory (Experience 1) – Must have 4+ years of total software development experience, with at least 2+ years working on AI/LLM-based features in production
Mandatory (Experience 2) – Must have strong backend engineering experience using Python (FastAPI / Django preferred) and building production-grade systems
Mandatory (Experience 3) – Must have hands-on experience building LLM-based applications, including OpenAI / Gemini / similar models in real projects
Mandatory (Experience 4) – Must have experience with RAG (Retrieval Augmented Generation) including chunking, embeddings, and retrieval pipelines
Mandatory (Experience 5) – Must have experience designing end-to-end AI pipelines, including chaining, tool usage, structured outputs, and handling failure cases
Mandatory (Experience 6) – Must have experience building agentic AI systems (multi-step workflows, tool orchestration like LangGraph / CrewAI or custom agents)
Mandatory (Experience 7) – Must have strong coding and system design skills, not just prompt engineering or experimentation
Mandatory (Experience 8) – Must have experience shipping AI features in production, not just POCs or research projects
Mandatory (Experience 9) – Must have experience working with APIs, backend services, and integrations
Mandatory (Experience 10) – Must have understanding of AI system reliability, including latency, cost optimization, fallback handling, and basic eval thinking
Mandatory (Company) – Product companies / startups, preferably Series A to Series D
Mandatory (Note) - Candidate's overall experience should not be more than 7 Yrs
Mandatory (Tech Stack) – Strong in Python + AI/LLM ecosystem, experience with modern AI tooling and frameworks
Mandatory (Exclusion) – Reject profiles that are only Prompt Engineers, Data Scientists, or Frontend Engineers without strong backend + system building experience
Preferred (Skill) – Experience with fine-tuning (LoRA / QLoRA) or open-source model deployment (vLLM / Ollama)
Preferred (Frontend) – Basic ability to build or contribute to frontend (React or similar)
Highly Preferred (Education) – Candidates from Tier-1 institutes (IITs, BITS, NITs, IIITs, top global universities)

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About TalentXO

Founded :

2018

Type :

Product

Size :

20-100

Stage :

Profitable

About

N/A

Company social profiles

N/A

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