Enterprise Technology Solutions Engineer (AI & Automation)

Linea Energy is a renewable energy company developing, building, and operating clean energy projects across the Americas. The Enterprise Technology Solutions Engineer will design, build, and deploy AI-driven automations, custom internal applications, enterprise integrations, and GIS-enabled solutions while supporting technology operations, administration, and security.

Responsibilities:

• Key individual within company responsible for enterprise software architecture and solutions
• AI Automation and Agentic Workflows: Design, build, and operate AI-powered automations and agent-based workflows (using LLM APIs, Model Context Protocol (MCP) servers, and workflow platforms) that connect to the systems where work already happens, such as Sitetracker/Salesforce, SharePoint and Microsoft 365, Notion, financial and data-room platforms, and document repositories. Prioritize automations by business impact and measure hours saved, accuracy, and adoption
• Application Development: Design, build, and maintain custom internal tools and applications using Python and JavaScript that put AI automations in the hands of development, legal, GIS, finance, and execution teams
• AI-Assisted Development: Leverage modern AI-assisted coding tools (e.g., Claude Code, Copilot, Cursor) to rapidly prototype, iterate, and deliver production-quality software, applying appropriate testing, code review, and deployment discipline to AI-generated code
• Cross-Functional Collaboration: Partner with stakeholders across the organization to identify high-value automation opportunities, map current workflows, gather requirements, and translate business needs into technical solutions. Train and support employees in adopting AI tools and automated workflows
• Enterprise Integration: Build and maintain integrations between internal systems of record, cloud services, and third-party platforms using APIs, webhooks, and MCP connectors to streamline data flows and reduce manual processes, with attention to reliability, monitoring, and error handling
• GIS and Spatial Applications: Develop or enhance GIS-enabled applications, spatial data pipelines, and automated spatial analyses to support energy project siting, analysis, and reporting
• Code Quality and Version Control: Maintain clean, well-documented codebases using Git, participate in code reviews, and follow best practices for collaborative development, including testing and evaluation of AI-driven workflows
• AI Governance and Data Protection: Help define and enforce policies for responsible AI use, including approved tools and models, data classification, handling of confidential project, financial, and counterparty information, prompt-injection and data-leakage safeguards, human-in-the-loop review for high-risk automations, and logging and auditability of automated actions
• Cloud Infrastructure: Deploy and manage applications, automations, and services within Azure cloud environments, including VMs, app services, functions, and data storage, along with access control, cost monitoring (including AI/LLM usage costs), backups, and patching
• Technology Operations and Administration: Serve as a technical resource for select IT operations, help manage the IT consultant, and support escalated end-user technical issues
• Security and Access Management: Apply and help maintain security best practices, including multi-factor authentication, least-privilege access, periodic access reviews, and secure handling of credentials and secrets across applications and cloud resources
• Documentation and Vendor Coordination: Document systems, automations, configurations, and support procedures, and coordinate with third-party IT providers, AI and software vendors on evaluation, licensing, renewals, and issue resolution