Senior Vice President Engineering

Job Title VP Engineering – Generative AI Applications (GenAI / Agentic Systems) Company Info Edge (India) Ltd. – Naukri.com About Info Edge: We are Info Edge, a pioneer in the Indian internet ecosystem. You may have heard about us when you are looking for a job (Naukri, iimjobs, hirist, AmbitionBox, Job Hai, BigShyft), a house (99acres), a life partner (Jeevansathi) or while you were studying (Shiksha). We run all these in house. We also invest actively and you might recognize us if you order food online (Zomato) or buy insurance online (Policy Bazaar). In short, we constantly strive to run sustainable businesses in the consumer internet space in India. We are $9-Billion in market cap but are a lot more in how we touch everyone’s life on a day-to-day basis. And we aspire to do more. Our Vision: To create world-class platforms that transform lives 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 LLM-powered 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). Strong 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) Good-to-Have Skills Experience with search datastores like Elasticsearch / Solr / Vespa Background in Information Retrieval (ranking, relevance, query understanding) Experience with Vector Search and hybrid retrieval (BM25 + embeddings) Experience managing remote / distributed teams (multi-location, async collaboration, outcomes-based execution) Preferred Traits (What We Value) Strong product sense: you can translate ambiguous problems into shippable milestones. Engineering rigor: you care about reliability, observability, evaluation, and operational excellence. Comfortable operating in fast-moving environments with high ownership and accountability. Ability to communicate clearly with stakeholders across engineering, product, and leadership. Why Info Edge / Naukri.com Work on large-scale, high-impact systems shaping the future of hiring. Opportunity to lead applied GenAI innovation with meaningful data, reach, and business outcomes. Collaborate with strong teams across platform, data, ML, and product.