Lead AI Engineer

Overview

Lead the AI team at Helpshift, designing and delivering AI Agents, LLM-powered initiatives and RAG pipelines while leading a group of backend, frontend and full-stack engineers.

What you'll do

• Lead and mentor a team of backend and frontend developers, fostering a high-performing, collaborative engineering culture.
• Own the technical direction, architecture, and strategy for LLM, AI Agent, and ML initiatives.
• Architect and build AI Agents, RAG pipelines (including multimodal RAG), LLM-based services, and evaluation frameworks.
• Design, build, and deploy scalable AI/ML systems from concept to production.
• Collaborate closely with PMs, ML Engineers, and Data Scientists to convert business requirements into AI-driven solutions.
• Oversee full SDLC for your squad, ensuring strong engineering practices around coding, testing, quality, and reliability.
• Conduct detailed technical reviews and provide guidance to maintain code quality.
• Troubleshoot performance, scalability, and reliability issues in production AI systems.
• Champion continuous improvement, automation, and innovation within the team.
• Keep the team up-to-date with advances in LLMs, LLMOps, fine-tuning techniques, vector search, and generative AI.

What you'll need

• 8–10 years of experience in software development.
• More than 5 years of hands-on experience in AI/ML.
• More than 2 years in an engineering leadership role, preferably leading a cross-functional team.
• Hands-on experience building AI Agents / Agentic workflows.
• Hands-on experience building LLM pipelines (inference, orchestration, guardrails).
• Hands-on experience building RAG systems (vector search, knowledge bases, multimodal RAG).
• Hands-on experience with LLM fine-tuning (SFT, LoRA, instruction tuning).
• Hands-on experience with LLMOps workflows (monitoring, evaluation, optimization, versioning).
• Strong understanding of ML algorithms, embeddings, transformers, vector semantics, and distributed systems.
• Experience with Vector Databases such as Elasticsearch, Weaviate, Pinecone, or Milvus.
• Proficiency with ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tooling.

Nice to have

• Solid foundation in backend technologies such as Python, Java, Go, Node.js, and experience with Kafka.
• Knowledge of the Gaming industry or Customer Support domain.
• Familiarity with frontend frameworks (React, Angular, Vue.js).
• Exposure to functional programming (Clojure preferred; the team uses Clojure).
• Experience in startup/high-growth environments.
• Open-source contributions in AI/ML/LLM projects.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Experience building production-grade LLM-powered automation for customer support or gaming.
• Publications, presentations, or contributions related to LLMs, RAG, or AI Agents.

Details

• Location: Pune, Maharashtra, India.
• Hybrid work setup.
• Benefits include worker's insurance and paid time offs, with other employee benefits to be discussed by the Talent Acquisition team in India.