Job Summary :

We are seeking a skilled Data Scientist / AI/ML Engineer with hands-on experience in building enterprise-grade AI and Generative AI solutions. The ideal candidate will have expertise in designing scalable AI applications, developing Retrieval-Augmented Generation (RAG) pipelines, integrating enterprise data sources, and deploying production-ready AI systems. You will work closely with cross-functional teams to transform business requirements into intelligent AI solutions.

Key Responsibilities :

- Design and develop modular AI solutions using LangChain, Semantic Kernel, or custom AI pipelines.

- Build AI-powered applications, APIs, and intelligent agents for enterprise use cases.

- Translate business requirements into scalable AI and machine learning solutions.

- Develop data ingestion pipelines and integrate structured and unstructured enterprise data sources.

- Design and implement RAG pipelines using embeddings, reranking, vector databases, and retrieval optimization techniques.

- Enforce structured outputs using Pydantic, function calling, and schema validation techniques.

- Containerize and deploy AI applications using Docker, CI/CD pipelines, and cloud platforms.

- Monitor model performance, system reliability, and continuously optimize AI solution quality.

- Collaborate with data scientists, engineers, and business stakeholders to deliver production-ready AI applications.

Required Skills :

- Strong proficiency in Python programming.

- Hands-on experience with LangChain, Semantic Kernel, OpenAI SDK, Transformers, LLaMA APIs, or similar AI frameworks.

- Experience building Retrieval-Augmented Generation (RAG) pipelines.

- Strong understanding of embeddings, vector databases, reranking, and prompt engineering.

- Experience developing AI agents, APIs, and enterprise AI applications.

- Knowledge of Pydantic, function calling, and structured output generation.

- Experience with Docker, containerization, and CI/CD pipelines.

- Familiarity with cloud platforms such as AWS, Azure, or GCP.

- Good understanding of REST APIs, data integration, and enterprise application architecture.

- Excellent analytical, problem-solving, and communication skills.

Preferred Skills :

- Experience with Vector Databases (Pinecone, Weaviate, FAISS, ChromaDB, Milvus, etc.).

- Knowledge of LLMOps, model monitoring, and AI observability.

- Experience with Git, Kubernetes, and DevOps practices.

- Familiarity with Azure OpenAI, AWS Bedrock, or Google Vertex AI.

- Exposure to Agentic AI, multi-agent frameworks, and enterprise AI deployments is an added advantage.