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