AI Engineer

We are seeking an experienced AI/ML Engineer with expertise in both machine learning (ML) and Generative AI (GenAI) to join our Emerging Technology Practice. In this role, you will drive the development of cutting-edge AI models and solutions-from statistical modeling and predictive analytics to advanced generative and agentic applications.

• Design and develop AI-powered systems using both traditional ML and Generative AI techniques, including prompt engineering, fine-tuning, embeddings, and Retrieval-Augmented Generation (RAG) architectures
• Build intelligent applications and agentic systems that can perform tasks autonomously or interactively, using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar
• Architect and implement end-to-end RAG pipelines, including document ingestion, chunking strategies, embedding generation, vector indexing, hybrid search, and contextual response generation
• Develop modular, well-documented APIs and service components (e.g., using FastAPI or Flask) to enable model integration and consumption
• Design, build, and manage end-to-end AI pipelines, including data ingestion, transformation, validation, model training, inference, deployment, and knowledge retrieval workflows
• Leverage AWS and Azure AI/ML services (e.g., Bedrock, SageMaker, Azure OpenAI, Azure ML, Document Intelligence, vector databases, etc.) to accelerate development and deployment
• Implement observability, evaluation, and monitoring mechanisms to track model accuracy, drift, retrieval quality, grounding fidelity, reliability, and task-level reasoning
• Optimize RAG systems for latency, scalability, cost efficiency, and response quality in production environments
• Collaborate with software engineers, data scientists, solution architects, and business stakeholders to ensure seamless solution design and transition to production
• Support both rapid experimentation (POCs, pilots) and robust, scalable deployments, depending on the maturity of each use case
• Stay up to date with emerging trends in Generative AI, AI agents, orchestration frameworks, RAG evaluation techniques, and continuous improvement methodologies

• 4 to 6 years of hands-on experience in AI/ML development or intelligent application engineering
• Strong proficiency in Python and familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
• Hands-on experience designing and deploying RAG-based systems, including embeddings, vector databases (e.g., FAISS, Pinecone, Chroma, Azure AI Search), and retrieval optimization techniques
• Experience building APIs or backend services using FastAPI, Flask, or equivalent frameworks
• Exposure to agent frameworks (e.g., LangGraph, AutoGen) and multi-agent orchestration patterns
• Experience with orchestration standards or tools such as MCP or agent routing protocols is a plus
• Familiarity with cloud platforms (AWS, Azure) and containerization tools (Docker)
• Hands-on experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or Google AI/ML services
• Experience with MLOps pipelines, CI/CD for model delivery, RAG evaluation frameworks (e.g., RAGAS), or model monitoring is a plus
• Knowledge of AI system evaluation, observability, prompt performance testing, and grounding validation is a plus
• Ability to work on cross-functional teams, balance multiple projects, and communicate effectively with technical and non-technical audiences
• Cloud certifications in AI/ML services (Azure, AWS, or Google Cloud) are a plus
• Bachelor s degree in Computer Science, Engineering, Data Science, or a related field

Position Level Associate Country India