Agentic AI , Gen AI with Azure PAAS -Professional

Agentic AI JD: Technology: Gen AI, Agentic AI Multi Agent Location: Pune Grades: G4 G5 Experience: 4 to 9 years Budget: G4 up to 17 LPA , G5 - up to 19L Jd: We are looking for candidates for a G4/G5 role based in Pune, with 5 7 years of relevant experience. The candidate must have hands-on exposure to Agentic AI and Multi-Agent Systems. Experience working in multi-cloud environments is required, with proficiency in at least two of the following platforms: Azure, AWS, Databricks, and GCP. Gen AI with Azure PAAS JD: Technology: Gen AI, Agentic AI Azure PAAS Location: Chennai, Bangalore, Pune Mumbai Grades: G4 G5 Experience: 4 to 9 years Budget: G4 up to 17 LPA , G5 - up to 19L Jd: We seek a Senior Full-Stack AI Engineer / Technical Lead to design and build enterprise-grade AI-enabled applications. The role demands strong hands-on experience in Generative AI, Azure PaaS, .NET Core, Python, SQL, and React or Angular. Core foundations include software engineering, cloud architecture, data structures, APIs, databases, distributed systems, security, and AI/ML concepts. You will build scalable backend services, intelligent workflows, robust data integrations, and intuitive user experiences. Solutions will leverage LLMs, prompt engineering, RAG, embeddings, vector search, agentic workflows, model evaluation, and guardrails. Deep Azure PaaS skills are required across managed services, serverless, API services, storage, databases, messaging, identity, and observability. You will implement secure cloud architecture and production-ready microservices and APIs. Write clean, modular, testable code in .NET Core and Python, with SQL for schema design, optimized queries, and performance tuning. Develop front-end apps, dashboards, forms, and AI-powered interactions using React or Angular. Integrate AI services with enterprise applications via REST APIs, microservices, event-driven patterns, and secure authentication. Drive POCs to production with focus on reliability, latency, cost, monitoring, logging, deployment automation, and supportability. Working knowledge in code reviews, CI/CD, version control, unit testing, documentation, DevOps, and operational readiness. Operate with a Forward Deployed Engineer mindset to work with client teams and convert ambiguous requirements into practical solutions. Proactively identify risks around data quality, ownership, integration, security, adoption, and support, and iterate quickly based on feedback. Communicate clearly with business users, architects and Stakeholders explaining GenAI and cloud concepts simply. Present trade-offs, mentor teams, review technical output, and maintain delivery momentum. Success requires ownership, accountability, resilience, and consultative problem solving across UI, API, database, cloud, and AI model layers. Build reusable components, accelerators, templates, and best-practice patterns aligned to secure, scalable, cost-effective business outcomes. Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .