AI/ML Team Lead – LLMs

We are looking for a Team Lead – AI/ML, Python, LLMs, and Azure Deployment who will be responsible for leading the design, development, and deployment of AI-powered agents and services within the Insurance AI platform. This individual will also play a crucial role in scaling our platform and ensuring that AI and ML models are efficiently deployed and managed on Azure infrastructure.

• AI/ML Development & Leadership: Lead a team of AI/ML engineers to develop, integrate, and scale AI-powered agents, using Python, LLMs (Large Language Models), and LangChain for process automation.
• Azure Cloud Deployment: Manage the deployment, scaling, and optimization of AI models and services within the Azure environment, ensuring high performance, scalability, and cost efficiency.
• LLM Integration: Oversee the design and implementation of LLMs for various insurance use cases (e.g., claims processing, bank reconciliation, submissions). Develop custom LLM models or fine-tune pre-existing models to improve platform performance.
• LangChain Implementation: Architect and deploy LangChain workflows to orchestrate complex automation tasks, ensuring seamless communication between AI agents and platform services.
• Model Optimization: Continuously monitor, tune, and optimize AI models, leveraging Azure AI tools to improve accuracy, response time, and operational efficiency.
• Collaboration with Engineering Teams: Work closely with software engineers, DevOps, and product teams to ensure seamless integration of AI components with the platform.
• AI/ML Pipelines: Develop and maintain robust AI/ML pipelines for model training, testing, validation, and deployment, leveraging Azure's AI and ML services (e.g., Azure Machine Learning, Azure AI Foundry).
• Continuous Improvement: Apply continuous learning practices by leveraging user feedback and performance data to refine AI models, agent behaviors, and overall platform performance.
• Documentation & Reporting: Lead the documentation of AI/ML models, deployment strategies, and best practices for the team and future AI/ML enhancements.
• Security & Compliance: Ensure all AI models and data comply with industry standards and regulations (e.g., GDPR, SOC2), especially in terms of data privacy and security for multi-tenant environments.

• Experience: 5 years of experience in AI/ML development, with a strong background in deploying large language models (LLMs) and orchestrating workflows using LangChain.
• Python Expertise: Proficient in Python, with hands-on experience in developing machine learning models, scripting, and integrating third-party libraries and services.
• Large Language Models (LLMs): In-depth experience with LLMs such as GPT, T5, or BERT, and their integration into production systems. Experience fine-tuning models for specific applications is a plus.
• LangChain Expertise: Proven experience using LangChain to design and deploy AI-driven workflows, managing interactions between multiple AI components, and orchestrating task automation.
• Azure Cloud Services: Expertise in deploying AI/ML models on Azure, including experience with Azure AI Foundry, Azure Machine Learning, Azure Databricks, and related Azure services for cloud-based machine learning.
• DevOps for AI: Knowledge of deploying and scaling AI services using containerization (Docker, Kubernetes) and managing the CI/CD pipelines for AI/ML models on Azure.
• Model Monitoring & Optimization: Experience with monitoring AI model performance, identifying bottlenecks, and optimizing for both speed and accuracy.
• Collaboration: Strong communication skills to work effectively across cross-functional teams, including product managers, software engineers, and infrastructure specialists.
• Problem-Solving: Strong analytical and problem-solving skills, particularly in debugging AI workflows and ensuring smooth integration with existing systems.
• Security & Compliance: Knowledge of security best practices for AI deployments, ensuring privacy and compliance with relevant regulations.

• AI/ML Certifications: Certifications in Azure AI, Azure Machine Learning, or other relevant AI/ML programs are a plus.
• Advanced Degree: A Bachelor's or Master's in Computer Science, Machine Learning, Data Science, or related fields is desirable.
• Experience in Insurance or FinTech: Knowledge of insurance or financial operations is a plus, particularly in areas like reconciliation, claims processing, and reporting.