You will be taken to Huron Consulting’s own careers page to apply. Job ID JR-0016829.
Job description
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future.
Join our team as the expert you are now and create your future.
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
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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
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