Artificial Intelligence Engineer

About Policybazaar.com –

Welcome to Policybazaar's official LinkedIn page. We believe in insurance for all, and we drive it through unbiased information and time-efficient processes for all Indian customers. As India's largest insurance brokers, we consider it our responsibility to be every Indian customer's one-stop portal for protection against death, disease and disability -- as well as for mindful investment planning. We understand customers anxiety about claim settlement, so we offer 24x7 online support, on-ground support, as well and even host special claim samadhan events where stuck claims can be reopened and resolved instantly. Our mission, in keeping with IRDAI's inspiring vision, is Har Family Hogi Insured by 2047.

Group Companies – Paisabazaar.com, QuickFixCars, Policybazaar.ae, Zphin Visit policybazaar.com to know more about us.

Full Stack Developer : AI Engineering Projects

Tech Stack: Python, Node.js, React.js, MongoDB, ADK / Vertex AI, AWS Bedrock

Experience Required: 3–6 years of relevant full stack development experience, with exposure to AI/LLM-based application development preferred.

About the Role:

We are looking for a Full Stack Developer with strong experience in Python, Node.js, React.js, and MongoDB, primarily responsible for developing and delivering AI engineering projects. The role involves building scalable web applications, backend APIs, AI-powered workflows, and agentic solutions using frameworks such as Google ADK / Vertex AI and AWS Bedrock.

Key Responsibilities:

• Develop and maintain full-stack applications using Python, Node.js, React.js, and MongoDB.
• Work on AI engineering projects, including AI assistants, automation workflows, chatbots, and agent-based systems.
• Build and integrate solutions using agentic frameworks such as Google ADK / Vertex AI and AWS Bedrock.
• Develop backend services, APIs, and middleware to connect AI models with internal platforms and business systems.
• Create responsive frontend interfaces using React.js for AI tools, dashboards, and user-facing applications.
• Design and manage MongoDB collections, queries, indexing, and data models for application and AI workflow needs.
• Integrate LLMs, retrieval systems, tools, APIs, and external services into production-ready AI applications.
• Work on prompt engineering, tool calling, RAG-based workflows, model orchestration, and AI response optimization.
• Debug, monitor, and improve AI application performance, accuracy, latency, and reliability.
• Collaborate with product, business, QA, DevOps, and data teams to understand requirements and deliver high-quality solutions.
• Write clean, scalable, secure, and maintainable code following engineering best practices.
• Participate in code reviews, sprint planning, technical design discussions, and production support.

Required Skills:

• Strong hands-on experience in Python and backend frameworks such as FastAPI, Flask, or Django.
• Good experience with Node.js and Express.js for backend API development.
• Strong frontend development experience using React.js, JavaScript, HTML, CSS, and reusable components.
• Hands-on experience with MongoDB, including schema design, aggregation, indexing, and performance tuning.
• Understanding of REST APIs, authentication, authorization, error handling, and secure API development.
• Experience working with LLMs, AI APIs, chatbots, RAG, or agentic workflows.
• Knowledge of Google Vertex AI, ADK, AWS Bedrock, LangChain, CrewAI, Semantic Kernel, or similar AI frameworks.
• Good understanding of prompt engineering, AI tool integration, function calling, and workflow automation.
• Experience with Git, debugging tools, logs, deployment processes, and basic DevOps practices.
• Strong problem-solving skills and ability to work independently on complex AI engineering use cases.

Good to Have:

• Experience with MCP servers, AI agents, multi-agent workflows, or enterprise chatbot platforms.
• Knowledge of vector databases such as Pinecone, Weaviate, Milvus, MongoDB Vector Search, or FAISS.
• Exposure to cloud services on GCP or AWS.
• Experience with Docker, CI/CD pipelines, Redis, queues, microservices, and monitoring tools.
• Understanding of model evaluation, guardrails, hallucination control, and AI safety practices.
• Experience building internal productivity tools, customer support bots, sales assistants, or automation platforms.

Education:

B.Tech/B.E./MCA/BCA or equivalent degree in Computer Science, IT, or related field.