AI Software Engineer II

Fortive•Austin, TX

About The Position

Accruent is seeking an AI Software Engineer II to join the VX Suite engineering organization, supporting the Maintain, Observe, and Sustain product portfolio. The role focuses on independently delivering production-ready SaaS capabilities and customer-facing AI experiences using AI-native engineering practices, agentic workflows, software factory capabilities, and cloud-native technologies. The engineer owns moderately complex work from requirement clarification through deployment and post-release validation, contributing to product delivery and improvements to engineering practices while maintaining quality, security, reliability, and customer trust. The role develops backend services, APIs, integrations, workflows, automated tests, and scalable data-processing capabilities for maintenance management, asset intelligence, operational monitoring, environmental compliance, and enterprise workflows. It also builds AI-powered experiences such as intelligent workflows, automation, retrieval-augmented solutions, and tool-enabled agents. The engineer collaborates with product and engineering partners, contributes to technical and architecture decisions, improves engineering workflows, and mentors AI Software Engineer I team members. This position is part of a globally distributed engineering organization with significant collaboration across North America and the United Kingdom. Candidates must maintain at least four hours of daily overlap with UK business hours, and flexibility in working hours is expected. The work spans Maintain capabilities such as work-order management and preventive maintenance; Observe capabilities such as real-time monitoring and predictive maintenance; Sustain capabilities such as environmental compliance and regulatory reporting; and shared platform services such as APIs, integrations, data pipelines, event-driven architecture, and reliability services.

Requirements

At least 3 years of professional software engineering experience.
Proven ability to deliver production software in SaaS, cloud, or enterprise software 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 such as GitHub Copilot, Copilot CLI, VS Code, Copilot Chat, Cursor, Claude Code, or similar technologies.
Experience designing and building APIs, backend services, microservices, or distributed systems.
Experience working with a cloud platform such as Microsoft Azure, AWS, or GCP.
Ability to decompose ambiguous requirements into actionable specifications, prompts, implementation plans, tests, and pull requests.
Experience designing, developing, and maintaining automated tests and CI/CD pipelines.
Strong understanding of software quality, observability, secure coding practices, and production support.
Demonstrated ability to review, debug, refactor, and validate AI-generated software.
Strong communication skills and ability to explain technical decisions, tradeoffs, risks, and validation evidence.
Ability to maintain at least four hours of daily overlap with UK business hours; flexibility in working hours is expected.

Nice To Haves

Experience with GitHub Copilot custom instructions, prompt files, custom agents, MCP servers, agent handoff workflows, or similar AI development capabilities.
Experience building customer-facing AI solutions, agentic workflows, retrieval-augmented applications, workflow automation solutions, or tool-integrated LLM applications.
Experience supporting facilities management, asset management, maintenance management, compliance management, or operational technology platforms.
Experience processing telemetry, event streams, equipment monitoring data, or IoT datasets.
Experience designing and implementing event-driven architectures using Kafka, RabbitMQ, Azure Service Bus, Event Hubs, or similar platforms.
Experience building scalable data ingestion and processing pipelines.
Experience integrating enterprise applications, industrial systems, building automation systems, sensors, devices, and third-party platforms.
Familiarity with BACnet, SNMP, Modbus, OPC UA, TCP/IP, or similar operational technologies.
Experience developing solutions that support predictive analytics, anomaly detection, intelligent automation, operational intelligence, or asset performance optimization.
Experience with Docker, Kubernetes, and containerized cloud-native applications.
Experience improving SDLC automation, developer productivity platforms, internal engineering tools, or software factory capabilities.
Familiarity with AI evaluation techniques, prompt testing, grounding strategies, hallucination mitigation, data privacy controls, and human-in-the-loop workflows.
Experience working in Linux environments and Bash scripting.
Experience working within globally distributed engineering organizations.

Responsibilities

Independently deliver SaaS product features, integrations, APIs, workflow capabilities, automated tests, documentation, and deployment artifacts using AI-native development practices.
Complete the software development lifecycle using agentic workflows, including requirement clarification, solution design, implementation, testing, validation, release preparation, and post-release support.
Build and enhance customer-facing AI-powered experiences, including intelligent workflows, automation capabilities, retrieval-augmented solutions, tool-enabled agents, and governed business processes.
Improve AI-generated output quality through prompt engineering, context management, reusable templates, repository guidance, and automated validation workflows.
Design and maintain automated tests, quality gates, and validation processes to ensure AI-generated code meets production standards.
Develop backend services, APIs, and platform capabilities supporting maintenance management, asset intelligence, operational monitoring, environmental compliance, and enterprise workflows.
Build integrations with enterprise applications, third-party platforms, building systems, equipment monitoring systems, devices, sensors, and operational technologies.
Design and maintain scalable services to collect, process, and operationalize maintenance, telemetry, monitoring, and compliance data.
Develop solutions that use operational and equipment data for intelligent automation, predictive insights, anomaly detection, and data-driven decision-making.
Design and implement event-driven architectures, distributed systems, and scalable data-processing solutions.
Partner with Product Management, Architecture, QA, DevOps, SRE, Security, Support, and Customer Success teams to deliver reliable customer-facing solutions.
Participate in technical design discussions and contribute to architecture decisions.
Analyze engineering workflows and identify opportunities to reduce friction, improve automation and quality, and accelerate delivery.
Mentor AI Software Engineer I team members on agentic development patterns, test-first approaches, validation practices, and engineering best practices.
Contribute reusable prompts, templates, workflows, and harness improvements that increase team productivity.
Collaborate across North America and the United Kingdom, maintaining at least four hours of daily overlap with UK business hours.