As an AI Engineer III you will have the opportunity to build, deploy, and support AI-enabled solutions that improve business processes. This role will work closely with AI architects, data teams, application teams, and business stakeholders to deliver secure, scalable, and production-ready AI capabilities. The AI Engineer III will help develop machine learning, generative AI, and automation solutions using Microsoft and enterprise technologies while supporting each solution from development through deployment, monitoring, support, and continuous improvement.
So, what will you be doing as an AI Engineer III?- Design, build, test, deploy, and maintain machine learning, generative AI, and AI-enabled application solutions for business use cases.
- Develop LLM-powered applications such as copilots, chatbots, knowledge assistants, summarization tools, agents, and workflow automation solutions.
- Implement retrieval-augmented generation patterns, including document ingestion, chunking, embeddings, vector search, retrieval logic, response grounding, and evaluation methods.
- Build and maintain data pipelines, APIs, services, connectors, and integrations that embed AI capabilities into enterprise applications and business processes.
- Develop prompt and context engineering approaches, structured outputs, tool or function calling patterns, guardrails, and content filtering for generative AI solutions.
- Use Microsoft and enterprise platforms such as Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning, Microsoft Fabric, Power Platform, Microsoft 365, and Dynamics 365 for development, orchestration, deployment, and integration.
- Apply secure development, responsible AI, sensitive data handling, access control, prompt injection protection, and enterprise data governance practices.
- Implement MLOps and LLMOps practices, including version control, automated testing, CI/CD, deployment pipelines, monitoring, rollback processes, and production troubleshooting.
- Collaborate with AI architects, data scientists, data engineers, analysts, DevOps teams, application teams, and business stakeholders to deliver supportable AI solutions.
- Monitor deployed AI services for quality, reliability, usage, cost, performance, errors, drift, security events, business value, and continuous improvement opportunities.
To be successful in this role, you'll need:- 5+ years of experience in software development, data engineering, cloud engineering, or related technical roles.
- 1 to 2 years of hands-on experience building solutions with generative AI, large language models, copilots, agents, automation, or AI-enabled applications.
- Working knowledge of retrieval-augmented generation, embeddings, vector search, prompt and context engineering, structured outputs, and LLM evaluation concepts.
- Experience using cloud-based AI, machine learning, search, data, or application development platforms to build, integrate, deploy, and support AI-enabled solutions.
- Proficiency in Python and experience with common AI, data, and application development libraries, frameworks, APIs, and SDKs.
- Experience with Git, automated testing, CI/CD practices, cloud deployment, logging, monitoring, and production troubleshooting.
- Strong understanding of machine learning fundamentals, data structures, model evaluation, software engineering practices, secure development, data privacy, access controls, responsible AI, and enterprise data governance.
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Technology, or related field.
Things we consider a plus:- Experience building production AI applications using Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning, Microsoft Fabric, Power Platform, Microsoft 365, Copilot Studio, or Dynamics 365 integrations.
- Experience developing APIs, connectors, microservices, or application integrations using Python, C#, REST APIs, or related technologies.
- Experience with containers, cloud deployment patterns, observability, monitoring, and production incident support.
- Ability to optimize AI solutions for reliability, performance, scalability, cost, maintainability, user adoption, and responsible use.
What to Do NextNow that you've had a chance to learn more about us, what are you waiting for! Apply today and allow us the opportunity to learn more about you and the value you can bring to our team. Once you apply, be sure to create a profile, and sign up for job alerts, so you can be the first to know when new opportunities become available.
