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About the role
Mode of Interview Internal Virtual Internal – In-person Client Round – Virtual Job Description: AI Engineer – GenAI & Multi-Agent Systems. Role Overview We are looking for a highly skilled AI Engineer specializing in Generative AI and Multi-Agent Systems to design and deploy intelligent, autonomous solutions. This role focuses on building LLM-powered, agent-driven architectures that can reason, collaborate, and execute complex workflows across enterprise systems. You will work on cutting-edge Agentic AI frameworks, enabling systems that go beyond prediction to decision-making, orchestration, and autonomous execution. Key Responsibilities * Design and build multi-agent AI systems capable of planning, reasoning, and task execution * Develop applications using LLMs (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestration * Implement Agentic workflows (planner executor critic memory loops) * Build RAG (Retrieval-Augmented Generation) pipelines with vector databases for enterprise knowledge grounding * Develop tool-using agents that integrate with APIs, databases, and enterprise systems * Architect and deploy AI copilots and autonomous assistants for business workflows * Optimize LLM performance using fine-tuning, prompt chaining, and caching strategies * Implement short-term and long-term memory mechanisms (vector stores, knowledge graphs) * Design multi-agent collaboration protocols (hierarchical, swarm, role-based agents) * Deploy scalable solutions using MLOps + LLMOps practices (monitoring, evaluation, guardrails) * Ensure AI safety, governance, and responsible AI practices Required Skills & Qualifications * Bachelor’s/Master’s in Computer Science, AI, or related field * 3–8 years experience in AI/ML with strong focus on Generative AI * Strong Python development skills * Hands-on experience with: LLMs & GenAI frameworks: OpenAI, Hugging Face Transformers Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kernel RAG pipelines & vector DBs: FAISS, Pinecone, Weaviate * Experience building API-driven, tool-integrated AI agents * Strong understanding of: Prompt engineering & prompt optimization Chain-of-thought reasoning and tool augmentation Context management and token optimization * Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptable) * Knowledge of Docker, Kubernetes, CI/CD pipelines Preferred Qualifications * Experience building multi-agent orchestration systems with role-based coordination * Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree-of-Thought) * Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfoo) * Knowledge of graph-based reasoning / knowledge graphs * Building autonomous systems or copilots in enterprise environments * Domain experience in industrial, energy, or IoT environments Key Competencies * Systems thinking for designing autonomous AI architectures * Strong problem decomposition for agent task design * Ability to balance latency, cost, and accuracy in LLM systems * Communication with business stakeholders to translate workflows into agent pipelines * Innovation mindset with focus on applying agentic AI in production Tech Stack (Modern GenAI Stack) * Languages: Python * Frameworks: LangChain, CrewAI, AutoGen, Semantic Kernel * LLMs: OpenAI GPT, Azure OpenAI, Claude, Llama * Vector DB: Pinecone, Weaviate, FAISS * Orchestration: Airflow, Prefect * Deployment: Docker, Kubernetes * Cloud: Azure AI Studio / Azure ML (preferred) KPIs / Success Metrics * Autonomous task completion rate of agents * Reduction in manual workflows via AI automation * Latency and cost optimization of LLM pipelines * Accuracy and reliability of agent outputs * Adoption rate of AI copilots across teams