AI Engineer
Huron Consulting Group1 day ago
Pune, India +2 moreMid Level / Senior
Responsibilities
- Design and develop AI-powered systems using traditional machine learning and generative AI techniques, including prompt engineering, fine-tuning, embeddings, and RAG architectures.
- Build intelligent applications and agentic systems using frameworks such as LangChain, LangGraph, AutoGen, and CrewAI.
- Architect and implement end-to-end RAG pipelines covering document ingestion, chunking, embedding generation, vector indexing, hybrid search, and contextual response generation.
- Develop modular APIs and backend service components using FastAPI, Flask, or equivalent frameworks.
- Design and manage AI pipelines for data ingestion, transformation, validation, model training, inference, deployment, and knowledge retrieval.
- Use AWS and Azure AI/ML services to accelerate solution development and deployment.
- Implement observability, evaluation, and monitoring for 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.
- Collaborate with software engineers, data scientists, solution architects, and business stakeholders to transition solutions into production.
- Support both rapid experimentation through proofs of concept and pilots and robust, scalable deployments.
Requirements
- 4 to 6 years of hands-on experience in AI/ML development or intelligent application engineering.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- Strong proficiency in Python and familiarity with scikit-learn, PyTorch, TensorFlow, and OpenAI APIs.
- Hands-on experience designing and deploying RAG systems with embeddings, vector databases, and retrieval optimization techniques.
- Experience building APIs or backend services with FastAPI, Flask, or equivalent frameworks.
- Exposure to agent frameworks such as LangGraph and AutoGen and to multi-agent orchestration patterns.
- Familiarity with AWS, Azure, Docker, and 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 such as RAGAS, or model monitoring is preferred.
- Knowledge of AI system evaluation, observability, prompt performance testing, and grounding validation is preferred.
- Experience with orchestration standards or tools such as MCP or agent routing protocols is a plus.
- Ability to work cross-functionally, manage multiple projects, and communicate with technical and non-technical audiences.
- Cloud certifications in Azure, AWS, or Google Cloud AI/ML services are a plus.
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About Huron Consulting Group
Huron Consulting Group is a global professional services firm that provides strategy, operations, digital, and technology consulting to healthcare, higher education, life sciences, and commercial organizations. Revenue comes from advisory and implementation engagements, including cloud transformations on platforms such as Workday, Salesforce, and Oracle, and software like the Huron Research Suite for universities. Founded in 2002 and headquartered in Chicago, it is a public company listed on NASDAQ.