Lead Full Stack AI Engineer

Role Overview :

We are seeking a hands-on Lead Full Stack AI Engineer to lead the design and development of AI-enabled enterprise applications for our AI-powered product. The role combines full-stack engineering, intuitive user experience development, and the integration of AI intelligence services and agent capabilities into scalable application workflows.

You will own technical delivery across the frontend and backend, build analytical and conversational experiences, and guide engineering teams in delivering reliable, high-quality software.

Key Responsibilities :

• Lead end-to-end application development, translating business and user needs into maintainable frontend, backend, and integration solutions.

• Build high-density analytical interfaces, including control towers, alerts, dashboards, and drill-down experiences.

• Develop intuitive investigation journeys, evidence views, recommendations, and action workflows.

• Build conversational AI experiences and embed AI capabilities into enterprise applications.

• Integrate application experiences with intelligence services, AI/ML services, large language models (LLMs), and AI agents through reliable APIs.

• Design and implement agentic workflows, including multi-agent orchestration, retrieval-augmented generation (RAG), and vector-based retrieval.

• Implement guardrails and observability for AI workflows, including validation, traceability, monitoring, and error handling.

• Drive engineering quality, scalability, and performance through sound architecture, code reviews, and testing.

• Provide technical leadership and mentor engineers; collaborate with product, design, data, and AI teams.

Tech Stack & Requirements :

• Strong hands-on experience building enterprise SaaS applications (frontend, backend, and system integration).

• Proficiency in Python and designing maintainable backend services.

• Practical expertise in agentic frameworks, multi-agent systems, RAG, and vector databases.

• Experience implementing AI guardrails and observability.

• Working knowledge of AWS, Snowflake, MLOps, and LLMOps practices.

• Proven ability to lead technical delivery and mentor teams.

Preferred Domain Experience :

• Experience in the life sciences / Healthcare domain is preferred.