PubMatic is seeking a senior engineer with 2-5 years experience in Generative AI and AI agent development. The role involves building and optimizing AI agents using Retrieval-Augmented Generation, vector databases, and large language models. Responsibilities include technical leadership, collaborating with cross-functional teams, leading design and deployment of AI features, fine-tuning LLMs, developing RAG-powered agents, optimizing vector databases, prompt engineering, and evaluating model performance. Required skills include expertise in LLMs, AI agent design, agentic frameworks (LangGraph, CrewAI, AutoGen), vector databases (FAISS, Pinecone, Weaviate, Milvus), observability tools (Langfuse), Python, TensorFlow, PyTorch, Hugging Face Transformers, and data preprocessing. A bachelor's degree in engineering or equivalent is required. The position offers a hybrid work schedule (3 days in office, 2 days remote) and benefits including parental leave, healthcare insurance, broadband reimbursement, and office amenities.
What you'll do
Provide technical leadership and mentorship to engineering teams
Similar jobs
More roles worth a look
Related opportunities based on specialty and working model so candidates can keep momentum.
Collaborate with architects, product managers, and UX designers to create innovative AI solutions
Lead design, development, and deployment of AI-driven features with end-to-end ownership
Drive quick iterations based on customer feedback in a fast-paced Agile environment
Spearhead technical design meetings and produce detailed design documents
Ensure solutions align with long-term product strategy and technical roadmaps
Implement and optimize LLMs including fine-tuning, deploying pre-trained models, and evaluating performance
Develop AI agents powered by RAG systems integrating external knowledge sources
Design, implement, and optimize vector databases and indexing algorithms
Create and fine-tune sophisticated prompts for LLMs
Utilize evaluation frameworks and metrics to assess and improve generative models
Work with data scientists, engineers, and product teams to integrate AI capabilities into products and tools
Stay updated with latest research and trends in LLMs, RAG, and generative AI
Continuously monitor and optimize models for performance, scalability, and cost efficiency
Requirements
2 to 5 years of total experience with strong understanding of LLMs and their underlying principles (transformer architecture, attention mechanisms, hyperparameter tuning)
Proven experience designing and building AI agents including multi-agent orchestration, tool-use patterns, multi-step planning, and agent memory architectures
Hands-on experience with agentic frameworks such as LangGraph, CrewAI, or AutoGen
