Senior AI Engineer
About The Position
The Senior AI Engineer designs, develops, and supports AI-enabled workflows, automation, and agentic solutions, translating business requirements into scalable technical capabilities. The role builds integrations and workflows, implements governance and testing standards, and supports successful deployment and operational adoption. The engineer evaluates AI-enabled workflows and technologies, develops proofs of concept, and designs and implements solutions using agents, prompts, retrieval-augmented generation (RAG), human-in-the-loop controls, tools, and integrations across stand-alone and RPA workflows. Solutions must follow approved platforms and enterprise architecture, security, data-validation, and engineering standards. The position leads automation initiatives through the full solution lifecycle, from discovery and requirements gathering through design, development, testing, deployment, and ongoing support. It develops production-ready code, configurations, technical documentation, reusable components, evaluation datasets, and automated validation frameworks. The engineer also establishes monitoring and operational support processes, supports pilots and production readiness, and mentors less-experienced team members. The role requires a high school diploma or GED and a bachelor’s degree in a related field or equivalent years of experience, plus 5–7 years of relevant experience. Preferred certifications include Microsoft Azure Solutions Architect Expert, Microsoft Agentic AI Business Solutions Architect Expert (AB-100 or equivalent), UiPath Automation Solution Architect Professional or Agentic Automation Professional, and AWS Solutions Architect Professional and/or AWS Certified Generative AI Developer – Professional.
Requirements
- High school diploma or GED.
- Bachelor’s degree in a related field or equivalent years of experience.
- 5–7 years of prior relevant experience.
- Demonstrated experience in one or more of traditional AI, machine learning, generative AI, or agentic AI, including core concepts, hands-on development, implementation, and production deployment.
- Advanced knowledge of intelligent automation and robotic process automation platforms.
- Experience with Microsoft Power Platform, Power Automate, UiPath, Automation Anywhere, or similar workflow automation, low-code, and agent framework technologies.
- Knowledge of generative AI, large language models, prompt engineering, RAG, tool calling, agent workflows, and AI-enabled workflow design.
- Experience with AI platforms such as Azure AI Services, Azure OpenAI, Copilot Studio, AWS AI/ML, or Google AI technologies.
- Proficiency in Python, SQL, APIs, authentication, data integration, enterprise applications, and systems integration methodologies.
- Understanding of cloud computing technologies and enterprise architecture principles.
- Knowledge of the software development lifecycle, testing methodologies, version control, DevOps, CI/CD, and release management.
- Understanding of logging, observability, incident management, and production support practices.
- Experience evaluating AI solutions for accuracy, reliability, latency, and failure modes.
- Working knowledge of secure AI patterns, including data access, least privilege, and tool-use controls.
Nice To Haves
- Microsoft Certified: Azure Solutions Architect Expert.
- Microsoft Certified: Agentic AI Business Solutions Architect Expert (AB-100 or equivalent).
- UiPath Automation Solution Architect Professional or Agentic Automation Professional.
- AWS Solutions Architect Professional and/or AWS Certified Generative AI Developer – Professional.
Responsibilities
- Evaluate and build proofs of concept for AI-enabled workflows, automation, and agentic solutions, translating business requirements into scalable technical capabilities.
- Design, configure, and implement AI and automation solutions, including agents, prompts, RAG, human-in-the-loop controls, tools, and integrations across stand-alone and RPA workflows.
- Develop and maintain the enterprise AI and automation roadmap aligned with organizational objectives.
- Lead automation initiatives through discovery, requirements gathering, design, development, testing, deployment, and ongoing support.
- Document reusable components, implementation patterns, and lessons learned.
- Develop and maintain production-ready code, configurations, and technical documentation using established engineering, version control, peer review, and change management practices.
- Develop test strategies, evaluation datasets, and automated validation frameworks for accuracy, reliability, performance, resilience, and responsible use.
- Implement approved AI and automation security, data access, identity, and governance controls in partnership with Architecture, Information Security, and Data teams.
- Establish monitoring, logging, alerting, and operational support processes, including dashboards, runbooks, incident procedures, and production support activities.
- Support pilots, production readiness reviews, deployments, and post-release validation.
- Evaluate AI-enabled workflows, automation, and agentic technologies through technical proofs of value and recommend platform, vendor, and solution approaches.
- Mentor less-experienced team members, participate in technical reviews, and promote engineering best practices.
- Perform other duties as assigned.
- Comply with regulatory compliance and assigned training requirements, including applicable BSA regulations.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
