IN_Manager_Gen AI_Emerging Business_Advisory_PAN India

Job Description & Summary: We are looking for a skilled GenAI / Agentic AI Developer with strong Python expertise to design, develop, and deploy Generative AI and Agentic AI applications using both open-source frameworks and cloud-native AI services. The ideal candidate should be capable of modernizing existing applications into microservices-based architectures, building intelligent autonomous AI solutions, and making cost-effective AI decisions by leveraging custom ML models and Small Language Models (SLMs) where LLM usage is expensive . Job Position Title: IN_Manager_Gen AI_Emerging Business_Advisory_PAN India Responsibilities: Design and develop GenAI and Agentic AI applications using open-source and cloud-native tools Build autonomous AI agents capable of reasoning, planning, tool usage, and multi-step task execution Modernize legacy/monolithic applications into microservices-based architecture Implement RAG pipelines and knowledge-grounded AI systems Deploy and orchestrate AI workloads using cloud-native services (AWS / GCP / Azure) Develop APIs and microservices using Python (FastAPI / Django) Build and train custom ML models for use cases like demand forecasting, anomaly detection, and predictions where LLM operations are costly or overkill Evaluate and implement Small Language Models (SLMs) as cost-effective alternatives to LLMs for specific tasks Implement observability, guardrails, and evaluation frameworks for AI applications Make informed decisions on when to use LLMs vs. SLMs vs. traditional ML based on cost, latency, and accuracy trade-offs Mandatory skill sets: Area Skills Python & Backend Python, FastAPI / Django, async programming Generative AI LLMs (OpenAI, Anthropic, LLaMA, Gemini), LangChain, prompt engineering, RAG, vector databases (Pinecone, ChromaDB, FAISS), fine-tuning & model serving Agentic AI LangGraph, CrewAI, AutoGen, OpenAI Assistants API, agentic patterns, MCP, memory, reasoning & self-correction Custom ML Models Scikit-learn, XGBoost, Prophet, statsmodels for demand forecasting, time-series analysis, classification & regression; model training, evaluation & deployment SLMs (Small Language Models) Experience with Phi, Gemma, Mistral-small, TinyLLaMA or similar Cloud & AI Services AWS (Bedrock, SageMaker) / GCP (Vertex AI) / Azure (Azure OpenAI); Docker, Kubernetes, serverless architectures AI Observability LLM evaluation (RAGAS, LangSmith), guardrails ( Guardrails AI), cost & token optimization Preferred skill sets: ReactJS API Gateway, message brokers (Kafka, RabbitMQ) CI/CD Pipelines Knowledge graphs (Neo4j) MLOps / LLMOps practices Experience with edge deployment of SLMs Years of experience required: 10-15 Years Education qualification: <B.Tech> /MBA