Senior Gen AI Engineer

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 minimum 5+ years of total software development experience, with at least 2+ years working on Gen AI / 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)