Expertise in generative AI frameworks and multiagent systems (AutoGen, CrewAI, Dify) combined with RAG pipelines built on LangChain, LlamaIndex, and vector databases (Pinecone, FAISS) to enable contextual AI applications.
Fullstack development proficiency with Java Spring Boot, React/Angular, and RESTful API design, enabling seamless integration of AI services into enterprise applications.
Cloudnative AI deployment experience on Google Cloud (Vertex AI) and AWS (Bedrock, SageMaker) with secure API management using Apigee X and CI/CD automation via GitHub, Jenkins, Docker, and Kubernetes
Good to Have
Familiarity with AIassisted development tools such as GitHub Copilot, Gemini Code Assist, Amazon Q, and Cursor to boost developer productivity and code quality.
Domain expertise in P&C insurance, healthcare automation, and ecommerce product catalog/search, allowing rapid translation of business needs into AI solutions.
Experience leading innovation programs, internal hackathons, and design sprints that foster adoption of emerging AI technologies across the enterprise.
Roles & Responsibilities
Serve as the solution architect for AI/ML initiatives, designing endtoend architectures that integrate generative AI models, multiagent frameworks (AutoGen, CrewAI, Dify) and microservice backends built with Java Spring Boot and React/Angular.
Lead rapid prototyping and innovation labs, orchestrating internal hackathons and proofofconcepts that leverage AI copilots (GitHub Copilot, Gemini, Amazon Q, Cursor) and prompt engineering to accelerate feature delivery.
Translate business objectives from domains such as P&C insurance, healthcare, and ecommerce into scalable AI solutions, employing RAG pipelines with LangChain, LlamaIndex, and vector databases (Pinecone, FAISS, Weaviate) for contextual retrieval.
Oversee the full AI delivery pipeline-from data ingestion and preprocessing using ETL and vectorization, through model training on LLMs (Hugging Face, Vertex AI, AWS Bedrock) to CI/CD deployment with GitHub, Jenkins, Docker and Kubernetes.
Implement and govern model lifecycle management, including monitoring, versioning, and automated testing using MLOps tools like MLflow, Kubeflow, and Vertex AI Pipelines, ensuring compliance with security and governance policies.
Secure APIs and services using Apigee X (OAuth 2.0, TLS) and enforce enterprisewide standards for data privacy, especially for healthcare dischargesummary generators and insurance policy automation.
Mentor and provide technical leadership to crossfunctional engineering and datascience teams, conducting code reviews, promptengineering workshops, and knowledgetransfer sessions on generative AI best practices.
Drive integration of AIassisted development tools (GitHub Copilot, Gemini Code Assist, Cursor) into the software development lifecycle to improve developer productivity and code quality.
Collaborate with product owners, compliance officers, and infrastructure teams to ensure AI solutions are scalable, highly available, and meet regulatory requirements across cloud platforms (Google Cloud, AWS).
Contribute to presales and solutioning activities, creating technical proposals, demos, and architecture diagrams that showcase AIfirst capabilities for enterprise clients.
