GenAI Engineering Manager

At Avanade, we see how the power of Dynamics 365 shapes the future of businesses every day. By combining our unmatched Microsoft knowledge with our creative approach to innovation and strong industry knowledge, we create a lot of opportunities for Microsoft, our clients, and for you. Avanade has countless paths for you to pursue. One of them is sure to lead to your unique version of success.

Artificial Intelligence Engineering involves the development of real-life predictive and intelligent solutions to be embedded in the business processes of our customers. The main focus of GenAI Engineering is the design, development and deployment of GenAI solutions that meet functional and technical programming standards. GenAI Engineers are, expected to analyze and scope client’s requirements, propose and design the solution, estimate the effort to deliver the solution and articulate that design and its value to the customer. GenAI Engineers will understand various programming languages, analytics platforms, GenAI frameworks and APIs which they will use to design complex applications.

Together we do what matters.

Key Responsibilities:

• Understand the business problem to be solved including the people, processes and systems impacted
• Have a view of the limitations of traditional technologies and areas of application for GenAI technologies
• Convert the high-level business requirements into functional and non-functional requirements to support the design phase
• Identify and select appropriate technologies for solving problems and formulate GenAI solution blueprints for development
• Determine the relevant software tools to fill the functional and non-functional requirements of the solution as defined by the client and technical team
• Estimate the effort required to execute the build of the designed solution
• Prototype applications applying formulated GenAI designs and verify the problem/solution fit working with data scientists in a collaborative mode
• Build of GenAI Platform and GenAI Product software components working alongside infrastructure engineers, data scientists and other team members
• Engineer solutions for new system roll-outs, enhancements, and maintenance of existing applications
• Deliver solutions that meet programming standards. Develop system specifications, create test plans and conduct project and issue management for assigned scope of work
• Understand various programming languages, analytics platforms, GenAI frameworks and APIs to design complex applications
• Develop, fine-tune, and deploy Generative AI models for real-world applications
• Design, build, and optimize APIs to integrate AI models into production environments
• Containerize applications using Docker for efficient deployment and scalability
• Work with various databases (SQL/NoSQL) to store and manage model inputs/outputs efficiently
• Collaborate with cross-functional teams to define AI-driven features and solutions
• Ensure scalability, reliability, and performance of AI-powered systems
• Conduct research and experimentation to stay ahead of emerging AI trends
• Implement LLMOps best practices, including model monitoring and continuous integration.

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• Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face
• Hands-on experience with Generative AI models, including LLMs, GANs, VAEs, or Diffusion Models
• Background in NLP, OCR or multimodal AI applications
• Experience with API development using FastAPI, Flask, or Django
• Knowledge of Docker and containerized deployments
• Familiarity with databases like PostgreSQL, MongoDB, or CosmosDB
• Experience with cloud platforms (Azure, AWS, or GCP) for AI model deployment
• Strong understanding of software engineering principles and best practices
• Ability to work in agile environments and collaborate with cross-functional teams
• Agentic Frameworks, including AutoGen, Semantic Kernel, LangGraph or Crew AI
• Preferred certification in Azure AI Engineering Associate
• Experience in developing cloud applications running on Microsoft Azure (preferred), Google Cloud Platform or Amazon Web Service
• Minimum 8 years of experience in building of GenAI solutions (using the above technologies) or in prompt engineering
• Experience with team, client and project management.

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