Artificial Intelligence & Automation Engineer

Description

Sargent & Lundy is a leading consulting engineering firm specializing in the power and energy sectors. Since 1891, we have provided comprehensive engineering, design, and consulting services for both traditional and renewable power generation, grid modernization, nuclear power, and beyond. Our mission is to help clients achieve their energy goals effectively by leveraging advanced technologies and adopting sustainable practices. 

We are seeking an AI & Automation Developer to join our Enterprise Data & Analytics team. This role is central to our growing AI/Automation capability and will serve as a hands-on technical partner to business groups across the organization. The ideal candidate brings demonstrated experience in both artificial intelligence and process automation, with a proven ability to assess feasibility, design solutions, and deliver measurable outcomes that create efficiencies and solve real business problems. 

As an AI & Automation Developer, you will work directly with business stakeholders to understand their challenges, evaluate whether AI, automation, or a combination of both is the right approach, and then design and deliver end-to-end solutions. This is a growth-oriented role for those passionate about using AI and automation to drive impact in the power and energy sector. 

Key Responsibilities 

Business Engagement & Feasibility Assessment 

• Partner directly with business groups to identify pain points, inefficiencies, and opportunities for AI and automation solutions. 

• Conduct structured feasibility assessments for proposed initiatives, evaluating technical viability, data readiness, integration complexity, expected ROI, and organizational readiness. 

• Translate business problems into clearly defined technical requirements, solution approaches, and delivery plans. 

• Present findings, recommendations, and solution options to both technical and non-technical stakeholders, ensuring alignment on scope, value, and approach. 
• Contribute to the intake and prioritization process for AI/automation demand across business groups, helping shape the portfolio backlog. 

 

AI Solution Development 

• Research, design, and develop AI-driven solutions and software applications for internal and client-facing needs. 

• Develop and deploy natural language processing (NLP), computer vision, generative AI, and other AI capabilities as applicable to business use cases. 

• Implement retrieval-augmented generation (RAG) patterns, prompt engineering strategies, and AI agent architectures to deliver intelligent automation solutions. 

• Ensure robust, high-quality data for model training and software features by building validation checks and monitoring systems. 

• Document model lineage, decision processes, and software dependencies; continually validate performance against business objectives. 

 

Automation & Efficiency 

• Design and implement automation solutions using RPA tools, scripting, workflow platforms, and low-code/no-code technologies (e.g., Power Automate, UiPath, or similar). 

• Identify and automate repetitive business processes, boosting productivity and reliability across teams. 

• Develop integration solutions that connect enterprise systems, APIs, and data sources to enable end-to-end automated workflows. 

• Monitor, maintain, and optimize deployed automations to ensure sustained performance and reliability. 

 

Software Development & Code Quality 

• Develop production-grade code for automation, analytics, and user interfaces, ensuring scalability, reliability, and maintainability. 

• Use rigorous software development practices—clear source control (Git), code review cycles, effective documentation, modular code organization, and adherence to coding standards. 

• Implement robust automated testing (unit, integration, system tests) for both AI and broader software solutions, contributing to high code quality and continuous delivery. 

• Follow a disciplined software development lifecycle (SDLC): requirements analysis, design, development, testing, deployment, and maintenance. 

• Lead or participate in post-mortems to identify root causes of incidents and implement lessons learned in future releases. 

 

Collaborative Development & Cross-Functional Engagement 

• Work closely with engineers, analysts, and IT to identify business problems that can be solved through AI or enhanced by automation. 

• Collabor