AI Software Engineer II

Quick Facts

• Role: AI Software Engineer II (SaaS + AI-native engineering)
• Focus: Maintain, Observe, Sustain product portfolio and shared platform services
• Collaboration: Cross-functional teams and globally distributed organization with UK overlap

Description

Own moderately complex work from requirement clarification through deployment and post-release validation. Deliver production-ready SaaS capabilities and customer-facing AI-powered experiences using AI-native/agentic SDLC practices. Build backend services, APIs, integrations, automated tests, quality gates, and event-driven architectures to support maintenance management, asset intelligence, monitoring, and compliance.

Responsibilities

• Independently deliver SaaS product features: integrations, APIs, workflow capabilities, automated tests, documentation, and deployment artifacts
• Execute the full SDLC using agentic workflows: requirement clarification, design, implementation, testing, validation, release preparation, and post-release support
• Build AI-powered customer experiences: intelligent workflows, automation, retrieval-augmented solutions, tool-enabled agents, and governed processes
• Improve AI-generated output quality via prompt engineering, context management, reusable templates, and automated validation workflows
• Design and maintain automated tests, quality gates, and validation processes that ensure production standards
• Develop backend services and platform capabilities for maintenance management, telemetry/monitoring, asset intelligence, and environmental compliance
• Build integrations with enterprise applications, third-party platforms, building systems, equipment monitoring systems, devices, sensors, and operational technologies
• Create scalable services to collect, process, and operationalize maintenance, telemetry, monitoring, and compliance data
• Implement event-driven architectures and scalable distributed processing for operational workflows and customer outcomes
• Collaborate with Product Management, Architecture, QA, DevOps, SRE, Security, Support, and Customer Success
• Contribute to architecture decisions; improve engineering workflows and mentor other engineers
• Create reusable prompts, templates, workflows, and harness improvements to increase team productivity

Requirements

• 3+ years of professional software engineering experience
• Proven ability to deliver production software in SaaS, cloud, or enterprise environments
• Strong experience with at least one modern technology stack and ability to adapt across languages, frameworks, and platforms
• Hands-on experience using AI-assisted development tools (e.g., GitHub Copilot and related tools)
• Experience designing and building APIs, backend services, microservices, or distributed systems
• Experience working with Microsoft Azure, AWS, or Google Cloud Platform
• Ability to decompose ambiguous requirements into actionable specifications, prompts, implementation plans, tests, and pull requests
• Experience designing/developing/maintaining automated tests and CI/CD pipelines
• Strong understanding of software quality, observability, secure coding practices, and production support
• Ability to review, debug, refactor, and validate AI-generated software
• Strong communication skills to explain technical decisions, tradeoffs, risks, and validation evidence
• Maintain at least 4 hours of daily overlap with UK business hours

Benefits

• Competitive base pay; Total Rewards package including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance, and paid/unpaid time away
• Work on AI-enabled applications, distributed systems, cloud-native services, telemetry processing, enterprise integrations, and large-scale SaaS/workflow automation