AI Engineer GenAI & Multi-Agent Systems

Role: AI Engineer GenAI & Multi-Agent Systems Location: Bangalore Experience: 4-9 years Immediate Joiners Only AI Engineer GenAI & Multi-Agent System s Key Responsibiliti es Design and build multi-agent AI systems capable of planning, reasoning, and task executi on Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestrati on Implement Agentic workflows (planner executor critic memory loop s) Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge groundi ng Develop tool-using agents that integrate with APIs, databases, and enterprise syste ms Architect and deploy AI copilots and autonomous assistants for business workflo ws Optimize LLM performance using fine-tuning, prompt chaining, and caching strategi es Implement short-term and long-term memory mechanisms (vector stores, knowledge graph s) Design multi-agent collaboration protocols (hierarchical, swarm, role-based agent s) Deploy scalable solutions using MLOps + LLMOps practices (monitoring, evaluation, guardrail s) Ensure AI safety, governance, and responsible AI practic esRequired Skills & Qualificatio ns Bachelors/Masters in Computer Science, AI, or related fie ld 38 years experience in AI/ML with strong focus on Generative AI Strong Python development skil ls Hands-on experience wit h:o LLMs & GenAI frameworks: OpenAI, Hugging Face Transforme rso Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kern elo RAG pipelines & vector DBs: FAISS, Pinecone, Weavia te Experience building API-driven, tool-integrated AI agen ts Strong understanding o f:o Prompt engineering & prompt optimizati ono Chain-of-thought reasoning and tool augmentati ono Context management and token optimizati on Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptabl e) Knowledge of Docker, Kubernetes, CI/CD pipelin esPreferred Qualificatio ns Experience building multi-agent orchestration systems with role-based coordinati on Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree-of-Though t) Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfo o) Knowledge of graph-based reasoning / knowledge grap hs Building autonomous systems or copilots in enterprise environmen ts Domain experience in industrial, energy, or IoT environmen tsKey Competenci es Systems thinking for designing autonomous AI architectur es Strong problem decomposition for agent task desi gn Ability to balance latency, cost, and accuracy in LLM syste ms Communication with business stakeholders to translate workflows into agent pipelin es Innovation mindset with focus on applying agentic AI in producti onTech Stack (Modern GenAI Stac k) Languages: Pyth on Frameworks: LangChain, CrewAI, AutoGen, Semantic Kern el LLMs: OpenAI GPT, Azure OpenAI, Claude, Lla ma Vector DB: Pinecone, Weaviate, FAI SS Orchestration: Airflow, Prefe ct Deployment: Docker, Kubernet es Cloud: Azure AI Studio / Azure ML (preferre d)KPIs / Success Metri cs Autonomous task completion rate of agen ts Reduction in manual workflows via AI automati on Latency and cost optimization of LLM pipelin es Accuracy and reliability of agent outpu ts Adoption rate of AI copilots across tea ms Role: AI Engineer GenAI & Multi-Agent Systems Location: Bangalore Experience: 4-9 years Immediate Joiners Only AI Engineer GenAI & Multi-Agent System s Key Responsibiliti es Design and build multi-agent AI systems capable of planning, reasoning, and task executi on Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestrati on Implement Agentic workflows (planner executor critic memory loop s) Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge groundi ng Develop tool-using agents that integrate with APIs, databases, and enterprise syste ms Architect and deploy AI copilots and autonomous assistants for business workflo ws Optimize LLM performance using fine-tuning, prompt chaining, and caching strategi es Implement short-term and long-term memory mechanisms (vector stores, knowledge graph s) Design multi-agent collaboration protocols (hierarchical, swarm, role-based agent s) Deploy scalable solutions using MLOps + LLMOps practices (monitoring, evaluation, guardrail s) Ensure AI safety, governance, and responsible AI practic esRequired Skills & Qualificatio ns Bachelors/Masters in Computer Science, AI, or related fie ld 38 years experience in AI/ML with strong focus on Generative AI Strong Python development skil ls Hands-on experience wit h:o LLMs & GenAI frameworks: OpenAI, Hugging Face Transforme rso Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kern elo RAG pipelines & vector DBs: FAISS, Pinecone, Weavia te Experience building API-driven, tool-integrated AI agen ts Strong understanding o f:o Prompt engineering & prompt optimiz