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We're looking for a Researcher who thrives on exploring the technical frontier and translating complex insights into real-world impact. This is a hands-on role, combining deep research with prototyping and cross-team collaboration, with the goal of driving innovation in Kubernetes internals, cloud infrastructure, and performance optimization.

Conduct deep research into Kubernetes internals, scheduling, autoscaling, and container resource usage.
Explore cutting-edge strategies for cloud resource optimization, cost efficiency, and performance engineering.
Design and deliver hands-on POCs, simulations, and benchmarks to validate new approaches.
Work closely with product and engineering teams to translate research findings into features and enhancements.
Stay at the forefront of the cloud-native and FinOps ecosystems, surfacing trends and opportunities.
Contribute to technical blogs, white papers, and internal knowledge sharing.

we are looking for a Service Systems Engineer.
As a Service Systems Engineer (SSE), you will be responsible for ensuring that the CT Detector Module System (DMS) is designed for efficient installation, maintenance, troubleshooting, and repair throughout its entire lifecycle. In this role, you will collaborate closely with DMS systems engineering, development, service, manufacturing, quality, and field teams to drive serviceability and operational excellence. You will translate customer and field insights into service concepts, requirements, and design enhancements, leveraging service and reliability data to improve system availability, safety, and maintainability. In addition, you will work cross-functionally with other CT teams to manage scanner-level interfaces and dependencies that impact DMS service performance.
Your role:
Develop service concepts and features based on customer, field engineer and service organization needs.
Translate service needs into requirements, service CTQs and design inputs.
Assess serviceability for installation, calibration, troubleshooting, repair, preventive maintenance, and replacement of serviceable items.
Participate in architecture and trade-off studies to ensure service needs are considered in design decisions.
Review DMS designs to confirm they meet service requirements, including relevant hardware, software, electrical, mechanical and thermal aspects.
Contribute to service-related verification activities, including defining service scenarios and evaluating service procedures and tools.
Work with customers, field engineers, and engineering teams to investigate and resolve DMS-related field issues.
Analyze field feedback, maintenance data, reliability trends and service performance
Translate findings into recommendations for hardware, software and service improvements.
Support failure analysis and risk assessment activities, including DFMEA.
Prepare and maintain service documentation, including service procedures, troubleshooting guidance and technical information for field tams.
Share service knowledge with relevant teams and support field engineers as needed.
Coordinate with scanner-level teams on interfaces and integration topics that affect DMS service.

We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.

We are seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

We are looking for a highly motivated and technically curious QA Engineer to join our Backend Infrastructure team on a 1-year fixed term contract. In this role, you will validate large-scale enterprise backend systems used in healthcare environments, ensuring quality, reliability, performance, and operational stability
Your role:
Design and execute functional, integration, system, regression, and end-to-end manual tests for backend infrastructure components and complex distributed systems.
Validate installation, upgrade, migration, configuration, backup, recovery, and deployment workflows across single-server, clustered, distributed, and cloud-based environments.
Work closely with software engineers, DevOps, automation teams, and product stakeholders to investigate failures, improve testing strategies, verify fixes, and contribute to reliable software releases.
Investigate Windows, IIS, networking, database, and service-level issues by analysing logs, diagnostics, system behaviour, and infrastructure dependencies.
Participate in reliability improvement initiatives, design reviews, and post-incident investigations to strengthen overall product quality throughout the development lifecycle.

department. You will be responsible for gathering, analyzing, and reviewing system-level and sub-system requirements, coordinating system partitioning and total system integration using systems engineering practices.
Your role:
Contribute to system architecture, design, and integration of a complex CT subsystem.
Perform hands-on lab work, including system bring-up, debugging and root-cause analysis.
Own and maintain system-level documentation (requirements, specifications, interfaces, design rationales).
Support verification and integration activities across multiple CT platforms.
Lead technical topics and collaborate closely with HW, SW, Mechanics, Physics, Manufacturing, Quality, and Service teams.
Support field and production issue investigations and lifecycle improvements.

we are looking for a Senior Mechanical Engineer.
In this role, you will lead all mechanical aspects of the product in R&D projects, taking it from concept to full scale development while working with multidisciplinary teams that include system engineering, physics, electronics, software, project managers, and others. You will serve as a technical focal point for mechanical design decisions, balancing performance, manufacturability, reliability, and cost.
Your role:
Lead the mechanical design including 3D models, drawings, prototype manufacturing, and production transfer.
Provide solutions that optimize performance, service, manufacturability, and cost.
Perform required analysis, testing, troubleshooting, and documentation.
Work with local and global teams inside and outside Philips to answer design, service, and production challenges.
Own mechanical risk identification, mitigation plans, and design reviews
Operate in a multidisciplinary environment under conflicting constraints of performance, reliability, cost, and development schedule.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across our platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose our capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how we evolve from AI-enhanced internal tools to customer-facing AI products.

We are seeking an experienced Technical Lead - Hardware Engineering to lead the technical development of advanced electronic systems and manage external hardware design contractors throughout the product lifecycle. The role is responsible for defining the hardware architecture, supervising outsourced development, ensuring engineering quality, and supporting projects from concept through production.
Key Responsibilities
Define hardware architecture and technical requirements. Lead and manage external hardware design contractors. Review and approve schematics, PCB layouts, and design documentation. Oversee High-Speed PCB design, SI/PI, DFM, and design reviews. Lead prototype bring-up, debugging, validation, and production support. Collaborate with system, FPGA, Firmware, Software, Mechanical, Manufacturing, and Quality teams. Drive technical problem solving and continuous improvement.

What You'll Be Doing
Engage with customers to ensure their success.
Partner with the sales team to drive the customer journey, build technical wins, and grow champions.
Develop a deep understanding of customers' goals and objectives, and articulate how our offering addresses their needs.
Create and own value-based relationships at all levels within customer organizations.
Actively participate in all phases of planning and execution, from initial discovery to the technical win.
Develop and maintain deep product expertise to demonstrate the value of us in sales meetings and at events such as meetups and conferences.
Advise the sales team on effective ways to position our product.
Onboard, educate, and enable partners, and support them through sales cycles.
Continuously develop your sales and technical skills through self-driven learning and our professional development opportunities.