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Responsibilities: • Design, develop, and maintain Full Stack [AI‑native] web applications, APIs, and backend services, including Retrieval‑Augmented Generation (RAG) solutions. • Develop Java‑based backend services and microservices (Spring Boot) to support AI workflows, orchestration, and enterprise integrations. • Develop Python (FastAPI) based backend microservices to support generative AI integrations. • Utilize Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Cloud Storage) to build, fine‑tune, and deploy AI‑native applications. • Utilize Microsoft Azure services (e.g., Azure Machine Learning, Azure OpenAI Service, Azure Synapse Analytics / Azure Data Explorer, Azure Blob Storage) to build, train, and deploy AI‑native applications. • Collaborate with data scientists, product managers, architects, and automation teams to translate business requirements into scalable technical solutions. • Fine‑tune and evaluate models for use‑case‑specific needs across cloud platforms. • Strong foundations in Prompt Engineering, RAG pipelines and Agent frameworks such as LangChain/LangGraph and Google ADK, and related orchestration frameworks. • Develop modular, scalable architectures for AI‑powered web applications and APIs. • Integrate LLMs with enterprise systems, databases, and external services. • Implement vector databases for semantic search and build connectors for structured and unstructured data ingestion. • Follow Agile/Scrum practices and document technical designs, workflows, and best practices.Work closely with automation teams, architects, and product owners to deliver end-to-end AI solutions. • Document workflows and best practices for AI integration.

Qualifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. • 5+ years of experience in AI engineering, backend development, or full-stack development. • Strong proficiency in Java (mandatory) for backend development, with hands-on experience using Spring Boot. • Strong proficiency in Python for AI/ML development and orchestration. • Proficiency in JavaScript/TypeScript and modern frontend frameworks (Angular/React). • Hands-on experience with LangChain, ADK, and agent orchestration frameworks. • Experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) and prompt engineering. • Hands-on experience with GCP and Azure services for AI/ML workloads and application deployment. • Experience with FastAPI/Django, Spring Boot, and ML libraries (TensorFlow, PyTorch, scikit-learn). • Familiarity with vector databases (Pinecone, Weaviate, FAISS). • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines. • Familiarity with ML algorithms, deep learning, and enterprise system integration. • Excellent communication skills and ability to work in Agile environments.