AI Engineer (LLMs, Agentic Systems & Model Training)

Job Title: AI Engineer (LLMs, Agentic Systems & Model Training)Location: MumbaiEmployment Type: Full-TimeExperience Level: Mid–SeniorAbout the RoleWe are seeking a highly skilled AI Engineer with deep expertise in Large Language Models (LLMs), AI Agents, and advanced retrieval and fine-tuning techniques. The ideal candidate has hands-on experience training and optimizing LLMs, building agentic workflows, utilizing vector embeddings, and implementing Agentic RAG and Cache-RAG architectures. Strong proficiency in Python and Java is required.Key ResponsibilitiesLLM Development & Model TrainingFine-tune, train, and optimize LLMs (open-source or proprietary) for specific business use cases.Implement supervised fine-tuning (SFT), RLHF, PEFT/LoRa, and other parameter-efficient training methods.Evaluate and improve model performance using modern benchmarking and evaluation tools.AI Agents & Autonomous WorkflowsBuild and deploy AI agents capable of tool use, planning, memory, and multi-step reasoning.Architect agentic systems that interact with external APIs, internal tools, and knowledge sources.Optimize agent reliability, latency, and cost using best practices.RAG & Vector EmbeddingsDesign and implement Agentic RAG, Cache-RAG, and hybrid retrieval pipelines.Work with vector databases (Postgres Vector, Pinecone, FAISS, Milvus, Chroma, Weaviate, etc.).Generate and manage embeddings for semantic search, retrieval-augmented generation, and caching.Ensure integrity, quality, and relevance of retrieval datasets.Software EngineeringDevelop scalable AI services using Python and Java.Build APIs, microservices, and data pipelines that support AI workflows.Write efficient, production-ready, clean, and well-documented code.Collaboration & ResearchPartner with data scientists, ML engineers, product teams, and researchers.Stay current with state-of-the-art LLM research, agent frameworks, and vector search technologies.Propose and prototype innovative AI features and architectures.Required Skills & QualificationsBachelor’s/Master’s in computer science, AI, Machine Learning, or related field.Strong proficiency in Python and Java, with demonstrable project experience.Hands-on experience fine-tuning and training LLMs (e.g., Llama, Mistral, GPT variants, Qwen, Gemma).Deep understanding of transformer architectures, tokenization, and inference optimization.Experience with agent's frameworks (LangChain, AutoGen, OpenAI Agents, LlamaIndex agents, custom agents).Practical knowledge of vector embeddings, ANN search, and RAG methodologies.Familiarity with GPU pipelines, distributed training, and model deployment.Understanding of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).Preferred QualificationsExperience with multi-modal LLMs (vision, audio, code).Knowledge of model quantization (GPTQ, AWQ) and inference acceleration.Experience with orchestration tools (Ray, Prefect, Airflow).Contributions to open-source AI projects.What We OfferCompetitive salary and benefitsOpportunity to work with cutting-edge AI systemsA collaborative environment that encourages innovationCareer growth and leadership opportunities

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