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.