AI ML Developer

Job description

We are looking for a seasoned AI/ML professional to drive AI innovation in the Insurance domain, leveraging Generative AI and Agentic AI systems to transform underwriting, claims processing, fraud detection, and customer experience. This role requires a blend of deep technical expertise and domain understanding in BFSI/Insurance workflows. - -- Key Responsibilities · Design and deploy AI/ML models for insurance use cases such as: o Claims automation o Underwriting risk assessment o Fraud detection \& anomaly detection o Policy servicing and customer insights o Leakage Analysis · Build Generative AI solutions for: o Automated document processing (policy docs, claims, KYC) o Intelligent customer support (chatbots, virtual assistants) o Report and summary generation · Develop Agentic AI systems to: o Automate multi-step insurance workflows (e.g., claims lifecycle) o Orchestrate decision-making agents interacting with internal tools/APIs o Enable autonomous underwriting or claims triaging systems · Implement RAG pipelines for: o Policy document retrieval o Regulatory compliance assistance o Knowledge-based customer support · Work with structured and unstructured data: o Claims records, policy documents, call transcripts, images · Ensure regulatory compliance (IRDAI guidelines, data privacy, auditability) · Deploy scalable solutions using cloud and MLOps best practices - -- Required Skills \& Qualifications AI/ML Expertise · Strong background in Machine Learning, Deep Learning, NLP · Experience in: o Classification, regression, clustering, anomaly detection o Computer vision (for claims image assessment -- preferred) Generative AI · Hands-on experience with: o LLMs (GPT, Llama, etc.) o Prompt engineering and evaluation o Fine-tuning approaches (LoRA, PEFT) · Use cases in: o Document understanding (OCR LLM pipelines) o Conversational AI Agentic AI · Experience building: o Autonomous agents for workflow automation o Multi-agent collaboration systems · Familiarity with: o Planning, memory, and tool usage in agents o Frameworks like LangChain Agents, AutoGen, CrewAI Insurance / BFSI Domain Knowledge · Strong understanding of: o Insurance lifecycle (policy issuance → claims → settlement) o Claims processing workflows (FNOL, adjudication, payout) o Underwriting processes and risk scoring o Fraud detection techniques in insurance Data \& Tech Stack · Python, SQL · Frameworks: PyTorch / TensorFlow, Hugging Face · Vector DBs: FAISS, Pinecone, Weaviate · Cloud: AWS / Azure / GCP · Data Platform: Databricks · Tools: Docker, Kubernetes MLOps \& Productionization · Model deployment, monitoring, and lifecycle management · CI/CD pipelines for ML systems · Experience integrating AI with enterprise systems (APIs, core insurance platforms) - -- Preferred Qualifications · Experience working with insurance companies, TPAs, or InsurTech firms · Exposure to: o OCR tools (for claims/document digitization) o Knowledge graphs for policy relationships · Familiarity with regulatory frameworks in India or glob