Senior AI Engineer

In this onsite role in Sacramento, CA, you will design, develop, and support AI-enabled workflows and automation solutions from discovery through deployment and operational adoption. The work includes building integrations, evaluating proofs of concept, and enabling secure, compliant production operations.

Responsibilities

• Design, develop, and support AI-enabled workflows and solutions, including automation and agentic solutions, by translating business requirements into scalable technical capabilities.
• Build integrations and workflows, implement governance and testing standards, and support successful deployment and operational adoption.
• Evaluate and build proofs of concept for AI-enabled workflows and solutions, including automation and agentic solutions.
• Design, configure, and implement AI and automation solutions such as agents, prompts, retrieval-augmented generation (RAG), and human-in-the-loop controls.
• Implement tools and integrations across stand-alone and RPA workflows using approved platforms while adhering to enterprise architecture, security, data-validation, and engineering standards.
• Lead enterprise AI and automation initiatives aligned with organizational objectives through the full solution lifecycle: 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.
• Create test strategies, evaluation datasets, and automated validation frameworks to support 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 to support operational adoption.
• Evaluate AI-enabled workflows and solutions, automation, and agentic technologies via technical proofs of value, and provide recommendations on 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 BSA regulations corresponding to job duties.

Requirements

• High School Diploma or GED required.
• Bachelor's Degree in a related field or equivalent years of experience required.
• 5-7 years of prior relevant experience required.
• Demonstrated experience in one or more of: traditional AI, machine learning (ML), generative AI, and agentic AI, including core concepts, hands-on development, implementation, and production deployment.
• Advanced knowledge of intelligent automation and robotic process automation (RPA) 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 (LLMs), prompt engineering, retrieval-augmented generation (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.

Preferred Certifications

• Microsoft Certified: Azure Solutions Architect Expert.
• Microsoft Certified: Agentic AI Business Solutions Architect Expert (AB-100 or equivalent).
• UiPath Automation Solution Architect Professional / Agentic Automation Professional.
• AWS Solutions Architect Professional and/or AWS Certified Generative AI Developer – Professional.

Technologies

• Python, SQL, APIs
• Microsoft Power Platform, Power Automate
• UiPath, Automation Anywhere
• Retrieval-augmented generation (RAG), LLMs
• Azure AI Services, Azure OpenAI, Copilot Studio
• AWS AI/ML, Google AI technologies
• RPA, DevOps, CI/CD
• E-Verify

Location and Schedule

• Sacramento, CA (onsite)
• 40 scheduled weekly hours

Compensation

• USD 112,185 - 179,496 per year