• Architect, scale, and optimise our distributed scanning infrastructure, ensuring high throughput, low latency, and reliable operation at global scale. • Advance DevOps performance and delivery excellence, continuously improving: Deployment frequency, Change lead time, Change failure rate, Mean time to recovery. • Solve complex scaling challenges across compute, data pipelines, networking, and orchestration, including: Evolving from single-region to multi-region/global architecture, Increasing data processing throughput across workflow pipelines, Improving overall system availability, observability, and fault tolerance. • Collaborate closely with Product, Security, and Engineering teams to ensure platform capabilities meet evolving business and customer needs. • Champion engineering best practices, including infrastructure-as-code, automation-by-default, high-quality operational documentation, and secure-by-design principles. • Drive continuous improvement, helping shape a culture of operational maturity, reliability, and engineering excellence.

Role Description The Lead Platform Engineer is a senior, hands-on technical leader responsible for the direction, reliability, and continued evolution of Accuity's internal engineering platform. The role enables software engineering and data science teams to deploy and operate production workloads in Microsoft Azure through reliable, repeatable, secure, and increasingly self-service capabilities. This position owns the shared infrastructure and delivery pathways that support application teams while preserving clear accountability for application behavior, quality, and production ownership within those teams. The Lead Platform Engineer establishes the platform roadmap, mentors engineers and Software Development Engineers in Test (SDETs), defines technical standards, and contributes directly to high-impact platform design and implementation. Responsibilities - Platform Strategy and Technical Leadership: - Define and maintain a focused platform roadmap based on recurring delivery, reliability, and operational challenges experienced by software engineering and data science teams. - Establish technical priorities, engineering standards, architectural direction, and sustainable ownership practices for platform capabilities. - Provide hands-on technical leadership and mentorship to platform engineers, SDETs, and other engineers contributing to platform initiatives. - Evaluate which capabilities should be centralized within the shared platform and which should remain owned by application or data science teams. - Lead technical design discussions, review critical changes, and guide decisions involving platform architecture, reliability, security, scalability, and maintainability. - Promote a pragmatic, service-oriented platform model that creates leverage for engineering teams without introducing unnecessary approval gates or operational dependencies. - Cloud Platform Engineering: - Build, maintain, and improve Accuity's Azure-based internal developer platform. - Develop and support infrastructure-as-code solutions for repeatable, secure, and consistent environment provisioning. - Own shared platform capabilities related to configuration, secrets management, cloud identity, network connectivity, CI/CD, deployment automation, and operational tooling. - Design platform services and workflows that reduce manual effort, minimize configuration drift, and improve deployment consistency. - Ensure platform capabilities are resilient, supportable, appropriately governed, and aligned with organizational security and compliance requirements. - Environment and Release Enablement: - Own the lifecycle and consistency of development, test, staging, and production environments. - Manage shared standards and capabilities for provisioning, configuration, access, drift management, deployment promotion, rollback, and environment support. - Create supported, documented, self-service deployment pathways that enable software engineers to release and operate the applications they own with reduced manual platform intervention. - Partner with software engineering teams to improve release reliability while maintaining application-level quality and release accountability within those teams. - Identify recurring delivery activities and convert them into reusable, automated, and maintainable platform capabilities. - AI and Data Science Infrastructure: - Provide and maintain the Microsoft Foundry and Azure infrastructure used to deploy production AI workloads. - Support repeatable provisioning, access controls, network configuration, capacity management, monitoring, promotion, and rollback for AI-related environments. - Partner with Data Science to understand infrastructure and deployment requirements while maintaining clear boundaries between platform responsibilities and ownership of models, evaluations, and data science outcomes. - Help establish secure, scalable, and operationally supportable patterns for deploying AI capabilities in production. - Quality, Observability, and Reliability: - Guide SDETs toward reusable automated validation and test infrastructure that integrates with the shared delivery platform. - Maintain clear ownership boundaries so that application quality and release decisions remain with the appropriate software teams. - Provide shared deployment and operational telemetry that enables teams to monitor the health of their services and troubleshoot production issues. - Diagnose complex platform, infrastructure, deployment, and environment issues. - Improve reliability through automation, standardization, observability, root-cause analysis, and sustainable remediation. - Support incident response and recovery activities for platform-owned systems and shared delivery capabilities. - Documentation and Operational Excellence: - Create and maintain technical documentation for platform-owned systems, processes, standards, runbooks, and architecture decisions. - Ensure documentation in Confluence and other approved repositories remains current, accurate, accessible, and usable by the broader engineering organization. - Define operational procedures and support models for platform capabilities. - Measure platform adoption, reliability, and business impact using practical indicators such as deployment lead time, change failure rate, recovery time, developer feedback, service adoption, and cloud cost. - Use metrics and stakeholder feedback to prioritize platform improvements and demonstrate measurable value. - Cross-Functional Collaboration: - Partner with software engineering, data science, quality engineering, security, compliance, and technology leadership to align platform capabilities with business and technical needs. - Communicate platform standards, priorities, architectural decisions, risks, and tradeoffs clearly across a fully remote organization. - Build trusted relationships with engineering teams and use recurring delivery challenges to inform platform priorities. - Support shared planning and decision-making while reinforcing clear accountability across platform, application, and data science teams. - Other Duties as Assigned: - Perform other duties and participate in additional projects as assigned to support departmental and organizational objectives. Qualifications - Bachelor’s degree in computer science, software engineering, information systems, or a related technical field preferred. - Equivalent professional experience, technical training, or a combination of education and relevant experience may be considered. - Relevant Microsoft Azure certifications are preferred. Requirements - 7+ years of experience in software, cloud, infrastructure, DevOps, SRE, or platform engineering, including hands-on production systems experience. - Demonstrated experience designing, deploying, and operating workloads in Microsoft Azure. - Experience building reusable platform capabilities, including infrastructure as code, CI/CD, deployment automation, observability, access management, and environment provisioning. - Demonstrated ability to provide technical leadership, mentor engineers, and define clear ownership boundaries across platform, application, and data science teams. - Experience with AI deployment infrastructure, automated testing frameworks, healthcare technology, or regulated environments strongly preferred. Benefits

Role Description We're hiring a Backend Engineer to make Enode's EV platform more reliable, observable, and efficient. As a Mid Level Backend Engineer on the Platform Connect team at Enode, you'll focus on improving the reliability, observability, and scalability of Enode's connectivity layer. This is the part of our API that aggregates integrations with EV chargers, vehicles, and OEM platforms into one cohesive and reliable product for our customers. This is not an infrastructure or DevOps role. The Platform Connect team owns the product level platform that powers connectivity at Enode, maintaining and extending the layer that links our users to energy devices through consistent, high quality integrations. You'll work on both new integrations and platform improvements: - Fixing bugs, building automations, improving monitoring and alerting, and helping make our API more robust as we scale to support more OEMs and partners. Our tech stack centers around a TypeScript based codebase combined with React, Node, AWS, Docker, and PostgreSQL, structured via CDK/CloudFormation. Qualifications - You have experience writing maintainable, testable backend code, ideally in an environment with a lot of API or integration work. - You're excited about platform engineering in the product sense. Building the connectivity layer that powers integrations, not managing infrastructure or CI/CD pipelines. - You enjoy both building new integrations and making existing systems more reliable and observable. - You're systematic in debugging issues and improving the tools and processes that prevent them from recurring. - You're proficient in JavaScript/TypeScript (or eager to learn TypeScript) and comfortable working in a distributed systems environment. - You communicate clearly, collaborate proactively, and contribute positively to team discussions. - You're curious, respectful, and growth oriented, someone who values teamwork, ownership, and continuous improvement. Requirements - You see AI as a strategic lever for engineering work, not just a productivity add on. AI is a real part of how we work as engineers at Enode. We expect you to be comfortable using it day to day, understanding where it helps and where it falls short, and starting to think about your work in terms of what AI can take on. If you're not fully there yet, you're genuinely eager to get there. Benefits - Opportunity to join and impact an early-stage climate tech startup with global aspirations as we scale. - A mission-driven, fun and caring environment with high drive and ambition. - Competitive compensation, including a very attractive employee option program - you’re part of our journey. - Access to best in class AI tooling, we think the ceiling on what a small team can do has fundamentally shifted, and we want you to feel that. - Remote-first in Europe, with the option of attending an office in Oslo or receiving a co-working pass on demand. - Three annual off-sites to connect with the team in exciting & fun places. - Flexible, human-first culture. - Stipend for setting up your home office.

Role Description We are seeking a highly skilled AEP Engineer to support, optimize, and scale our Adobe Experience Platform (AEP) and Real-Time CDP implementation. This role owns data collection architecture, platform performance, data quality, and governance across our digital ecosystem. The ideal candidate has strong hands-on experience with AEP configuration, Customer Journey Analytics (B2B), Adobe Web SDK, and AEP Data Collection. This role ensures reliable data flow, accurate reporting, and scalable solutions, while partnering across Adobe Experience Cloud tools (AEM, Journey Optimizer, Marketo Engage) to enable end-to-end customer insights and activation. Responsibilities - Own and support enterprise AEP and Real-Time CDP implementations, ensuring scalability, stability, and performance - Design and manage end-to-end data collection using Adobe Web SDK, Edge Network, and datastreams - Architect and govern XDM schemas, datasets, identity namespaces, and merge policies for accurate profile stitching - Develop and maintain tagging via AEP Data Collection across multi-domain environments - Build and manage Data Connections and Data Views in Customer Journey Analytics (CJA) - Monitor and resolve data ingestion, identity, and cross-platform discrepancies (AEP, Analytics, CJA, downstream systems) - Implement data quality frameworks, validation processes, and Query Service checks - Define and enforce event-driven data layer standards (ACDL/EDDL) - Enable audience segmentation and integrate datasets into CJA for cross-channel insights - Manage consent and privacy frameworks (GDPR, CCPA), including OneTrust integration - Partner with stakeholders to translate business needs into scalable technical solutions and support governance/documentation Qualifications - 5+ years in digital analytics implementation and data collection architecture - Strong hands-on experience with: - Adobe Experience Platform (AEP) - AEP Data Collection (Adobe Launch) - Adobe Web SDK - Experience with Real-Time CDP and Customer Journey Analytics (CJA) - Proficiency in JavaScript, HTML, and CSS for web instrumentation - Experience with XDM schema design, data modeling, and event-based tracking - Deep understanding of data layer architecture and governance - Familiarity with Agile methodologies and SDLC - Strong communication and cross-functional collaboration skills Preferred Qualifications - Experience with AEP Edge Network and server-side event forwarding - Expertise in identity resolution and profile stitching within CDP - Knowledge of Adobe Analytics constructs (eVars, props, events, classifications) - Experience integrating AEP with APIs and downstream systems - Experience with Adobe Journey Optimizer and Marketo Engage integrations - Exposure to global/multi-region data collection strategies - Experience with Python or automation for data validation - Familiarity with other tag management tools (GTM, Tealium) - Experience supporting enterprise MarTech ecosystems Core Skill Areas - AEP Architecture & Data Modeling - XDM schema design, identity resolution, merge policies - Datastream, Edge Network, and ingestion pipeline management - Ensuring scalable, high-performing AEP environments - Data Collection & Instrumentation - Adobe Web SDK and AEP Data Collection expertise - Event-driven data layer design (ACDL/EDDL) - Advanced JavaScript-based tracking across multi-domain environments - Troubleshooting cross-platform data inconsistencies - Analytics, Data Quality & Governance - Building CJA Data Connections and Data Views - Data validation via Query Service and monitoring frameworks - Managing ingestion issues and reporting discrepancies - Enforcing privacy and compliance (GDPR, CCPA, OneTrust) - Translating business needs into analytics-ready data Job Type & Location This is a Permanent position based out of Redlands, CA. Pay and Benefits - The pay range for this position is $120,000.00 - $160,000.00/yr. - MEDICAL: We cover primary health premiums for you and your eligible dependents. - DENTAL: Dental premiums for you and your eligible dependents are 100 percent paid. - VISION: Vision coverage at no cost to you; eligible dependents can be added for a small monthly premium. - PAID TIME OFF: Time for you to recharge and reenergize, including vacation and holiday pay. - 401(K) AND CONTRIBUTION MATCHING: Savings and contribution-matching plan to help you prepare for retirement. - PROFIT SHARING: Option of sharing profits with employees every year. - GROWTH: Numerous educational resources, including training opportunities and scholarships. - CAREER DEVELOPMENT: Support for growth and success in your career. - WELLNESS: Employee assistance program offering free resources related to various personal matters. Workplace Type This is a fully remote position. Application Deadline This position is anticipated to close on Jul 31, 2026.