As an AI Engineer, you'll design and develop AI systems, collaborating with teams to ensure the deployment of intelligent solutions across various industries and use cases.
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.
This role spans the full AI solution lifecycle: data preparation, model development, application integration, and ongoing evaluation. You will collaborate closely with architects, and domain experts to ensure the AI solutions you help build are intelligent, reliable, and aligned with client goals.
We work across industries and use cases, from early-stage prototypes to production-ready deployments, and we're continuously exploring new AI paradigms—including AI agents, agent orchestration layer, model chaining, and self-evaluating systems. If you’re excited by emerging AI technologies, fast-moving teams, and applied problem-solving, this is the role for you.
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
- 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
- Familiarity with orchestration standards or tools such as MCP or agent routing protocols 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
Top Skills
AWS
Aws Sagemaker
Azure
Azure Machine Learning
Docker
Fastapi
Flask
Google Ai/Ml
Openai Apis
Python
PyTorch
Scikit-Learn
TensorFlow
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