About the Role
We are looking for an experienced AI / ML Lead to define and execute the AI / ML strategy, with a strong focus on developing and deploying advanced models tailored to insurance use cases . You will lead the model lifecycle end-to-end, integrate GenAI / LLM solutions, and ensure governance and compliance in a regulated industry.
This is a founding-level opportunity to :
- Shape the foundation of a next-gen insurtech platform.
- Collaborate with a highly motivated team tackling real-world, high-impact challenges .
- Design elegant, scalable systems that set new benchmarks for the industry.
- Drive meaningful innovation in a space that is ripe for disruption .
Key Responsibilities
Define and drive the AI / ML strategy .Design and implement native model integration frameworks .Build scalable, objective-centric ML solutions for insurance applications (fraud detection, risk assessment, underwriting, claims automation).Lead end-to-end ML lifecycle management — data preprocessing, model training, deployment, monitoring, and optimization.Develop and fine-tune LLMs (GPT, Claude, LLaMA) with expertise in prompt engineering, RAG architectures, and evaluation frameworks .Integrate ML models with enterprise applications (Java / Spring) via REST APIs.Deploy and manage models in containerized environments (Kubernetes, Docker).Establish governance for responsible AI : bias detection, explainability (LIME / SHAP), fairness metrics, and regulatory compliance.Implement drift detection, automated monitoring, versioning, and A / B testing for continuous improvement.Required Skills & Experience
6+ years of hands-on experience in ML engineering and model lifecycle management.Strong expertise in Python development (FastAPI, TensorFlow, PyTorch, Scikit-learn, XGBoost).Proficiency in ML model deployment, versioning, A / B testing, and Kubernetes containerization .Hands-on experience with document processing, OCR, NLP pipelines, and vector databases .Proven ability to build and optimize LLMs and Generative AI solutions (fine-tuning, quantization, model optimization).Familiarity with RAG pipelines, prompt engineering, and GenAI evaluation techniques .Deep knowledge of model governance , including explainable AI, fairness metrics, and bias detection.Experience in integrating ML solutions with enterprise systems .Preferred Domain Expertise
Insurance industry experience in :Fraud detectionRisk assessmentUnderwriting modelsClaims automationAI regulatory complianceWhat’s in it for You
The chance to be part of a founding-level tech team .End-to-end ownership of AI / ML initiatives in a high-impact domain .Opportunities to work on cutting-edge Generative AI and ML solutions .A collaborative, high-growth environment where your work will create real-world impact .Competitive compensation and benefits.