AI Associate

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.

Responsibilities

• Design and develop AI-powered systems using both traditional ML and generative AI techniques, including prompt engineering, fine-tuning, and embeddings
• Build intelligent applications and agents that can perform tasks autonomously or interactively, using frameworks like LangGraph, AutoGen, CrewAI or similar
• Create modular, well-documented APIs and service components (e.g., using FastAPI or Flask) to enable model integration and consumption
• Develop and manage data pipelines, including data collection, transformation, and quality assurance to support model training
• Implement observability and evaluation mechanisms to monitor AI system behavior, including accuracy, drift, reliability, and task-level reasoning
• Collaborate with software engineers, data scientists, and solution architects to ensure seamless design, development, and transition to production
• Support rapid experimentation as well as robust deployment pipelines, depending on the maturity of each use case
• Stay informed on the latest trends in GenAI, AI agents, orchestration protocols, and evaluation frameworks to continuously evolve our capabilities

Preferred Qualifications

• Atleast 4 years of hands-on experience in AI/ML development or intelligent application engineering
• Proficiency in Python and familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
• Experience building APIs or backend services using FastAPI, Flask, or equivalent frameworks
• Exposure to agent frameworks (e.g., LangGraph, AutoGen) and vector databases
• Experience with orchestration standards or tools such as MCP or agent routing protocols is a plus
• Familiarity with cloud platforms (Azure, AWS) and containerization tools (Docker)
• Familiarity 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, or model monitoring is a plus
• Knowledge of AI system evaluation, observability, or prompt performance testing 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) is a plus
• Bachelor s degree in computer science, Engineering, Data Science, or a related field