Lead Data Scientist

Contact No. 9743254624

Full Stack AI Developer Engineer Location: Bangalore only Experience: 3 to 10 Years Role Overview We are looking for a Full Stack AI Developer Engineer to build and scale enterprise-grade AI and GenAI applications. The role blends full stack development, LLM GenAI implementation, and cloud-native engineering to deliver secure, production-ready AI solutions and reusable accelerators. Key Responsibilities 1. Design and develop end-to-end AIGenAI applications UI, backend, AI orchestration 2. Build and productionize LLM and RAG-based solutions 3. Implement prompt engineering, guardrails, and evaluation mechanisms 4. Develop scalable backend APIs and services 5. Build responsive frontend applications using modern frameworks 6. Deploy and manage solutions on cloud platforms Azure AWS GCP 7. Containerize and orchestrate workloads using Docker and Kubernetes 8. Integrate AI solutions with enterprise systems 9. Follow engineering best practices for security, CICD, monitoring, and performance 10. Contribute to AI accelerators, platforms, and IP creation 11. Support POCs, demos, and presales engagements when required Required Technical Skills 1. Strong hands-on experience in Python primary andor Node.js Java 2. Frontend development using React and modern JavaScript 3. Hands-on experience with LLMs, GenAI APIs, and RAG architectures 4. Experience with microservices, REST APIs, and distributed systems 5. Cloud experience on Azure AWS GCP 6. Working knowledge of Docker, Kubernetes, CICD pipelines 7. Experience with SQLNoSQL databases and vector stores Soft Skills 1. Strong problem-solving and analytical thinking 2. Ability to translate business requirements into technical AI solutions 3. Clear and effective communication with technical and non-technical stakeholders 4. Strong ownership mindset and ability to work independently 5. Collaborative team player with a product and enterprise mindset 6. Comfortable working in fast-paced, evolving AI environments Good to Have 1. Experience with agentic or multi-agent AI frameworks 2. Exposure to enterprise platforms ITSM, AIOps, FinOps, DevOps 3. Microsoft ecosystem exposure Azure OpenAI, Power Platform, Copilot 4. Experience building reusable platforms, frameworks, or SaaS products