AI Software Engineer II

Accruent; United Kingdom; On-site; GBP 70,000 - 110,000; Full time

Job summary

Accruent is seeking an AI Software Engineer II to join the VX Suite engineering organization, supporting the Maintain, Observe, and Sustain product portfolio. You will deliver production-ready SaaS features and customer-facing AI experiences using AI-native engineering practices.

You will work across the full SDLC, leveraging agentic workflows and cloud-native technologies to build scalable solutions that help customers manage assets, monitor equipment, and automate maintenance workflows.

Qualifications

• 3+ years of professional software engineering experience.
• Proven ability to deliver production software in SaaS, cloud, or enterprise software environments.
• Experience with API, backend services, microservices, or distributed systems.
• Experience with cloud platforms (Azure, AWS, or GCP).
• Ability to decompose ambiguous requirements into actionable specs and tests.
• Experience designing, developing, and maintaining automated tests and CI/CD pipelines.
• Strong understanding of software quality, observability, secure coding, and production support.
• Experience reviewing, debugging, refactoring, and validating AI-generated software.
• Excellent communication to explain technical decisions and risks.

Responsibilities

• Independently deliver SaaS product features, integrations, APIs, workflows, automated tests, documentation, and deployment artifacts using AI-native development practices.
• Complete the full software development lifecycle (SDLC) 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 effective prompt engineering, context management, reusable templates, repository guidance, and automated validation workflows.
• Design and maintain automated tests, quality gates, and validation processes that 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 that collect, process, and operationalize large volumes of maintenance, telemetry, monitoring, and compliance data.
• Develop solutions that leverage operational and equipment data to support intelligent automation, predictive insights, anomaly detection, and data-driven decision-making.
• Design and implement event-driven architectures, distributed systems, and scalable data processing solutions to support operational workflows and customer outcomes.
• 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, increase 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.

Skills

Software engineering

APIs & backend

Cloud platforms

AI-assisted tools

SDLC & CI/CD

Distributed systems

Observability & security

Tools

GitHub Copilot

Copilot CLI

VS Code

Copilot Chat

Cursor

Claude Code

Job description

Accruent is seeking an AI Software Engineer II to join the VX Suite engineering organization, supporting the Maintain, Observe, and Sustain product portfolio.

This role is ideal for an experienced software engineer who can independently deliver production-ready SaaS capabilities and customer-facing AI experiences using modern AI-native engineering practices. You will leverage approved AI development tools, agentic workflows, software factory capabilities, and cloud-native technologies to build, test, deploy, and support scalable solutions that help customers manage assets, monitor equipment, automate operational workflows, and maintain regulatory compliance.

As an AI Software Engineer II, you will own moderately complex work from requirement clarification through deployment and post-release validation. You will contribute to both product delivery and continuous improvement of engineering practices, helping the organization accelerate software delivery while maintaining quality, security, reliability, and customer trust.

What You’ll Do

AI-Native Software Development

• Independently deliver SaaS product features, integrations, APIs, workflow capabilities, automated tests, documentation, and deployment artifacts using AI-native development practices.


• Complete the full software development lifecycle (SDLC) 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 effective prompt engineering, context management, reusable templates, repository guidance, and automated validation workflows.


• Design and maintain automated tests, quality gates, and validation processes that ensure AI-generated code meets production standards.

Maintain, Observe, Sustain Product Development

• 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 that collect, process, and operationalize large volumes of maintenance, telemetry, monitoring, and compliance data.


• Develop solutions that leverage operational and equipment data to support intelligent automation, predictive insights, anomaly detection, and data-driven decision-making.


• Design and implement event-driven architectures, distributed systems, and scalable data processing solutions to support operational workflows and customer outcomes.

Collaboration & Engineering Excellence

• 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, increase 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.

Required Qualifications

• 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 the 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 cloud platforms 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 the ability to explain technical decisions, tradeoffs, risks, and validation evidence.

Preferred Qualifications

• 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 technologies such as 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 protocols and technologies such as 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.

What You’ll Work On

Maintain

• Work order management


• Preventive maintenance workflows


• Asset lifecycle management


• Vendor and contractor integrations


• Operational reporting and analytics

Observe

• Real-time monitoring and alerting


• Equipment telemetry ingestion and processing


• Predictive maintenance capabilities


• Asset intelligence solutions


• Energy management and operational insights


• Automated maintenance triggers based on equipment conditions

Sustain

• Environmental compliance workflows


• Refrigerant management and tracking


• Regulatory reporting solutions


• Sustainability initiatives


• Operational compliance processes

Shared Platform Services

• Scalable APIs and backend services


• Enterprise and third-party integrations


• Data ingestion and processing pipelines


• Event-driven architecture


• Operational intelligence capabilities


• Monitoring, observability, and reliability services

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