Lead Gen AI engineer

Generative AI Lead Engineer, Schoolnet India Limited
Hyderabad | Full-time | 8+ years experience (2+ years in production GenAI/LLMs)
About Schoolnet
Schoolnet India Limited is one of India's largest EdTech social enterprises, reaching close to 25 million learners across 100,000+ schools. Our AI-enabled products span personalised adaptive learning, AI teaching assistants, and intelligent classroom devices, all built to operate in low-bandwidth, infrastructure-constrained environments.
The Role
You will be the senior engineer and technical lead for our GenAI initiatives, designing the architecture, building the most complex components, and setting technical direction for the team. The systems you own range from multi-agent applications and RAG pipelines to models running on classroom devices at the edge. This is a hands-on role focused on turning early product concepts into production GenAI that is scalable and cost-efficient.
Key Responsibilities
Own the GenAI roadmap from prototype to production, leading decisions on model selection, build vs buy, and architecture
Design multi-agent systems (orchestration, tool use, memory, A2A and MCP) and production-grade RAG pipelines
Lead edge and on-device inference for low-connectivity environments using quantization and distillation (Ollama, vLLM)
Build a systematic, versioned, and tested approach to prompt engineering
Optimise cost, latency, and throughput through caching, batching, and model routing
Establish CI/CD for AI systems with tracing and cost, latency, and quality monitoring (Langfuse, LangSmith)
Build evaluation harnesses and regression suites (LLM-as-judge, A/B testing)
Implement guardrails, bias and hallucination mitigation, and data-privacy compliance
Secure the GenAI stack against prompt injection and data leakage, with dependency and vulnerability scanning
Set engineering standards, maintain quality through design and code reviews, and partner with Product, Design, and QA
Required Skills
8+ years in software or ML engineering, including 2+ years building GenAI/LLM systems in production
Experience tech-leading projects from design through to production
Deep hands-on experience with LLMs, RAG, agents, tool use, and embeddings, plus a modern agent framework (Google ADK, LangGraph)
Strong prompt-engineering skills and an evaluation-driven mindset
Strong Python and solid engineering fundamentals (APIs, testing, containers, cloud, CI/CD)
Experience with relational, NoSQL, and vector databases
Familiarity with application security for systems handling sensitive user data
Real LLMOps experience covering deployment, monitoring, and observability
Track record of optimising AI systems for cost, latency, and reliability at scale
Preferred
Edge AI and on-device inference; fine-tuning and PEFT (LoRA)
Multimodal experience (speech, vision, OCR); full-stack development
EdTech or scalable SaaS background; GCP deployment experience
Familiarity with responsible-AI and data-privacy frameworks

Work arrangement
No