<p>Role Overview</p> <p>We are seeking an experienced AI Technical Lead to design, build, and scale AI systems with a strong focus on Generative AI, Agentic AI architectures, and robust software engineering best practices. This role involves driving end-to-end AI solution development-from model selection and fine tuning to system design, deployment, and operationalization.</p> <p>You will lead technical strategy, mentor engineering teams, and work closely with product, architecture, and business stakeholders to deliver AI-driven capabilities across the enterprise.</p> <p>Key Responsibilities</p> <ol> <li>AI Engineering & Solution Delivery </li></ol> <ul> <li>Lead the design and development of Generative AI solutions using LLMs, multimodal models, and diffusion models. </li><li>Build and maintain Agentic AI systems, including autonomous agents, tools integration, reasoning frameworks, and multi-agent workflows. </li><li>Develop production-grade AI components using strong engineering principles: modularity, maintainability, observability, and testing. </li><li>Optimize models for performance, latency, and cost using techniques like quantization, distillation, and retrieval augmentation. </li></ul> <ol start="2"> <li>Software Design </li></ol> <ul> <li>Design scalable, secure, and compliant AI solutions aligned with enterprise engineering standards. </li><li>Ensure adherence to best practices in software development, version control, CI/CD, containerization, and LLMOps/MLOps. </li></ul> <ol start="3"> <li>GenAI & Agentic AI Focus </li></ol> <ul> <li>Lead development of applications using LLMs (OpenAI, Azure OpenAI, Anthropic, Llama, etc.). </li><li>Build RAG pipelines, vector-based retrieval systems, and knowledge grounding solutions. </li><li>Create autonomous and semi-autonomous AI agents capable of task execution, planning, and reasoning. </li><li>Drive experimentation with new GenAI techniques-prompt engineering, tool use, function calling, fine-tuning, and model fine-tuning. </li><li>Evaluate emerging frameworks: LangChain, Semantic Kernel, AutoGen, etc. </li></ul> <ol start="4"> <li>Leadership & Collaboration </li></ol> <ul> <li>Lead a team of AI engineers and developers; provide mentoring, coaching, and technical guidance. </li><li>Translate business requirements into technical actionable engineering plans. </li><li>Partner with product teams to define AI capabilities, roadmaps, and delivery milestones. </li><li>Evangelize AI best practices and contribute to AI governance, ethics, and responsible AI frameworks. </li></ul> <p>Required Qualifications</p> <ul> <li>10+ years of software engineering experience; 3+ years in applied AI/ML engineering. </li><li>Strong proficiency in Python, AI frameworks (PyTorch, TensorFlow), and API-driven development. </li><li>Hands-on expertise with GenAI, LLM orchestration frameworks, RAG pipelines, and vector databases (Pinecone, FAISS, Azure AI Search). </li><li>Experience developing Agentic AI using tools/functions integration, planning agents, workflows, or multi agent systems. </li><li>Deep understanding of cloud platforms: Preferably Azure, including ML Ops and containerization (Docker, Kubernetes). </li><li>Solid understanding of system design, distributed computing, microservices, and API architecture. </li></ul> <p>Preferred Skills</p> <ul> <li>Experience fine tuning LLMs. </li><li>Knowledge of multimodal models (vision, speech, text). </li><li>Familiarity with Azure OpenAI, OpenAI, Anthropic Claude, and open source models (Llama, Mistral, Gemma). </li><li>Practical knowledge of model evaluation metrics, safety guardrails, prompt optimization, and responsible AI. </li><li>Background in Insurance is a plus. </li></ul> <p>Soft Skills</p> <ul> <li>Excellent communication skills. </li><li>Strong leadership abilities with experience managing technical teams. </li><li>A problem-solving mindset with a focus on innovation, quality, and delivery. </li><li>Ability to work in dynamic, cross-functional environments. </li></ul> <p>Salary Range: $110,000 to $130,000 per year</p>