About the Role

We’re looking for a VP Engineering – Generative AI Applications to lead the design, build, and scale of ML- and GenAI-powered production systems at Naukri.com. You will drive end-to-end execution of agentic applications (multi-agent workflows), RAG-based systems, and LLMpowered experiences that directly impact hiring outcomes for recruiters and jobseekers. This is a hands-on leadership role: you will shape architecture, guide technical decisions, and lead high-performing teams delivering reliable, scalable, and measurable GenAI products.

Responsibilities

Own engineering delivery for GenAI application initiatives: from problem definition to production rollout and iteration.

Lead development of agentic applications (multi-step reasoning/workflows) with robust orchestration, safety, evaluation, and monitoring.

Build and scale RAG systems (retrieval, ranking, context construction, grounding, citations, hallucination control) for text-heavy domains.

Drive best practices for prompt engineering, tool-use patterns, function calling, guardrails, and quality loops. Partner with Product/Business stakeholders to define success metrics, SLAs, and measurable outcomes (quality, latency, cost, conversion).





Establish engineering excellence around scalable backend systems: APIs, workflow engines, async systems, reliability, observability, and cost controls.

Hire, mentor, and manage a team of engineers and ML practitioners; build a culture of ownership, speed, and quality.

Collaborate with platform/data/search teams for feature stores, data pipelines, indexing, retrieval, experimentation, and evaluation frameworks.

Qualifications

Strong experience in building ML-powered production applications (end-to-end).

Robust hands-on experience with Python and modern ML development practices.

Proven expertise in NLP / text data (classification, extraction, embeddings, semantic matching, etc.).

Experience building or leading teams delivering Generative AI applications and/or agentic systems.

4+ years of people management experience (hiring, mentoring, performance management).

Practical experience with: o Machine Learning, Deep Learning, Generative AI o Prompt engineering, RAG, tool use/function calling o Scalable backend systems (APIs, services, distributed systems, async patterns) o SQL databases (any) and NoSQL (at least one)

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