About the Role 

We are building a next-generation observability and cloud platform that is high-performance, cost-efficient, secure, and scalable across multi-region, multi-cloud clusters. You will lead the architecture and evolution of Roku’s observability and cloud infrastructure stack. This includes metrics, logs, traces, telemetry pipelines, service mesh, developer experience, and reliability of systems that power thousands of services and millions of devices. 

You will drive a vision where developers gain deep visibility with minimal overhead, onboarding is seamless, and insights are available in real time. Your work will directly help Roku scale efficiently while maintaining reliability, cost control, and performance. 

What You’ll Be Doing 

• Architect and lead Roku’s observability platform across metrics, logs, and traces; evolve data pipelines and storage layers optimized for high throughput, performance, and cost at Roku scale (TSDBs, Parquet, distributed processing). 

• Extend and harden open‑source observability systems; overhaul core components (e.g., storage layers, query paths) to improve performance, reliability, and usability at scale. 

• Implement features such as pre‑aggregation, down-sampling, and sampling to reduce load and accelerate queries across the platform. 

• Collaborate across platform, SRE, and product teams to migrate hundreds of workloads to our common platform; augment and automate CI/CD flows and onboarding. 

• Integrate security into infrastructure and platform services; ensure robust multi‑tenant, multi‑cluster, and multi‑cloud designs. 

• Contribute improvements back to open source and CNCF‑aligned projects; shape standards adoption (OpenTelemetry, OpenMetrics) across the company. 

• Mentor engineers; establish best practices for reliability, efficiency, and cost management across service mesh and observability domains. 

What You'll have  

• Extensive experience with  software engineering with a track record of architecting distributed systems or platforms at scale. 

• Strong hands‑on experience in Golang and one scripting language (e.g., Python or Shell). 

• Experience operating observability at pb-scale ingestion and hundreds of millions of series. 

• Expertise in observability platforms and tooling (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, ClickHouse) and standards (OpenTelemetry, OpenMetrics).  

• Deep experience building systems of scale and operating cloud infrastructure with Kubernetes; strong proficiency with service mesh technologies (Istio/Envoy), infrastructure‑as‑code (Terraform) and experience in multi‑cloud (AWS, GCP) 

• Demonstrated ability to evolve storage and query architectures for cost, scale, and latency (e.g., TSDB, Parquet, distributed processing). 

• Proven experience integrating security as part of infrastructure and platform development.   

• Exceptional cross‑functional communication; effective collaboration with both technical and non‑technical stakeholders. 

• Culture fit: independent thinker, pragmatic problem‑solver, low‑ego collaborator who moves fast and focuses on company success. 

• Experience integrating AI tools to improve processes and reduce toil. 
• Open‑source contributions in CNCF projects is preferred but not mandatory.  

#LI-PA1

About the Role

You will be a SME and technical leader in engineering Infrastructure, productivity and enterprise tooling, partnering with globally distributed Engineering, Product and Security teams and systems.

What You’ll Be Doing

Roku is seeking a world class engineer to be a true force multiplier by owning the strategy, architecture, and long-term execution of engineering infrastructure, enterprise tooling, and AI-assisted workflow automation. This architect/strategist role drives org-wide improvements in engineering productivity, delivery throughput, quality, security posture, and cost efficiency by building platforms, working practices and automation (including AI/LLM-enabled capabilities) that scale across geographies and time zones.

Key Responsibilities

AI-First Automation & Intelligent Tooling

• Define and lead an AI-first automation roadmap for Engineering Infrastructure and Enterprise Tooling (e.g., reducing waste, accelerating reviews, improving incident response, increasing release confidence).
• Architect and ship AI/LLM-enabled workflow automation across the SDLC (e.g. risk assessment, automated build, test and deployment, intelligent test selection, change-impact analysis, auto-triage of build/test failures).
• Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.

Dev Productivity & Enterprise Tooling (Global Scale)

• Set technical direction and standards for the globally used developer tools, including build systems. Source code management, branching/release strategy, and self-service support tools.
• Architect and evolve, CI/CD and build/test pipelines using Jenkins, Docker, and build systems (Bazel /BitBake/Yocto  preferred) to support multi-site engineering environments.
• Own and scale test and quality workflows leveraging test management systems (e.g., TestRail or equivalent), enabling consistent traceability, reporting, and release sign-off across distributed teams.
• Drive Jira workflow design and automation (templates, guardrails, integrations) to provide consistent cross-org visibility and execution.

Workflow Automation (Cross-Functional, Cross-Geo)

• Design and implement automation spanning Engineering, Product, Marketing, and Partners (e.g., launch readiness, certification/release checklists, partner onboarding, incident/change workflows).
• Replace manual coordination with durable automation and integrations that work reliably across regions/time zones.

Security, Cost, Performance, and Reliability (Distributed Systems)

• Embed secure-by-default controls into pipelines and tooling (access control, secrets handling, audit trails, policy enforcement), including for AI-enabled systems.
• Improve build/test performance and reliability (build times, test duration, flake reduction, pipeline stability) using measurable KPIs and operational rigor.
• Drive cost efficiencies across tooling/infrastructure (compute utilization, caching strategies, license rationalization including AI/runtime costs and ROI tracking.
• This is a highly visible role and you will report directly to a Vice President of Engineering. This requires a very strong technical leader with experience in the development of consumer electronics devices. The right person for this role will have ability to collaborate well with engineering and partner teams.
• Own cross-team architectures and standards; drive adoption through influence, clear technical judgment, and sustained multi-quarter execution.
• Lead design reviews, mentor senior engineers, and unblock the hardest technical problems across distributed teams and systems.
• Provide long-term stewardship via roadmaps, operational maturity (runbooks/SLOs), and incident/postmortem practices suitable for 24/7 global operations.
• Establish yourself as the person others bring their hardest problems to

We’re Excited If You Have

• Bachelor’s in Computer Science or Computer Engineering, or equivalent experience
• Prior experience at Staff, Principal, or Architect level
• Ownership in platform/infrastructure, developer productivity, CI/CD, build systems, or workflow automation, including work spanning globally distributed teams and systems.
• Strong, hands-on knowledge of:

• • Git (workflows, branching strategies, release management)
  • Jenkins (CI/CD pipeline design, scaling, reliability)
  • Docker containers (reproducible build/test execution)

Build systems ( itBake/Yocto preferred)

• Jira (workflow design/automation, cross-team visibility)
• Test management systems (e.g., TestRail or equivalent)
• Demonstrated experience delivering automation at scale, including building platforms/components used by multiple teams.
• Strong systems thinking across security, reliability, performance, and cost tradeoffs.
• Excellent written communication (architecture docs, decision records, operating procedures).
• Experience building AI-assisted developer tooling (e.g., CI insights, test intelligence, code review automation, release risk scoring, incident copilots).
• Experience implementing evaluation/monitoring for AI systems (quality metrics, drift, offline test sets, human feedback loops).
• Extensive experience with software development on embedded Linux,  multi-process architectures and IPC mechanisms
• Experience working in large cross functional teams and ability to influence teams that don't report to you
• Ability to see the big picture while focused on short-term objectives and deliverables
• Ability to multi-task and drive parallel projects and distributed teams with tight deadlines

#LI-NM1

About the Role

You will be a SME and technical leader in engineering Infrastructure, productivity and enterprise tooling, partnering with globally distributed Engineering, Product and Security teams and systems.

What You’ll Be Doing

Roku is seeking a world class engineer to be a true force multiplier by owning the strategy, architecture, and long-term execution of engineering infrastructure, enterprise tooling, and AI-assisted workflow automation. This architect/strategist role drives org-wide improvements in engineering productivity, delivery throughput, quality, security posture, and cost efficiency by building platforms, working practices and automation (including AI/LLM-enabled capabilities) that scale across geographies and time zones.

Key Responsibilities

AI-First Automation & Intelligent Tooling

• Define and lead an AI-first automation roadmap for Engineering Infrastructure and Enterprise Tooling (e.g., reducing waste, accelerating reviews, improving incident response, increasing release confidence).
• Architect and ship AI/LLM-enabled workflow automation across the SDLC (e.g. risk assessment, automated build, test and deployment, intelligent test selection, change-impact analysis, auto-triage of build/test failures).
• Establish policies and guardrails for AI usage in internal tools: data handling, prompt/response logging, model/provider selection, evaluation, fallback behaviors, and abuse prevention.

Dev Productivity & Enterprise Tooling (Global Scale)

• Set technical direction and standards for the globally used developer tools, including build systems. Source code management, branching/release strategy, and self-service support tools.
• Architect and evolve, CI/CD and build/test pipelines using Jenkins, Docker, and build systems (Bazel /BitBake/Yocto  preferred) to support multi-site engineering environments.
• Own and scale test and quality workflows leveraging test management systems (e.g., TestRail or equivalent), enabling consistent traceability, reporting, and release sign-off across distributed teams.
• Drive Jira workflow design and automation (templates, guardrails, integrations) to provide consistent cross-org visibility and execution.

Workflow Automation (Cross-Functional, Cross-Geo)

• Design and implement automation spanning Engineering, Product, Marketing, and Partners (e.g., launch readiness, certification/release checklists, partner onboarding, incident/change workflows).
• Replace manual coordination with durable automation and integrations that work reliably across regions/time zones.

Security, Cost, Performance, and Reliability (Distributed Systems)

• Embed secure-by-default controls into pipelines and tooling (access control, secrets handling, audit trails, policy enforcement), including for AI-enabled systems.
• Improve build/test performance and reliability (build times, test duration, flake reduction, pipeline stability) using measurable KPIs and operational rigor.
• Drive cost efficiencies across tooling/infrastructure (compute utilization, caching strategies, license rationalization including AI/runtime costs and ROI tracking.
• This is a highly visible role and you will report directly to a Vice President of Engineering. This requires a very strong technical leader with experience in the development of consumer electronics devices. The right person for this role will have ability to collaborate well with engineering and partner teams.
• Own cross-team architectures and standards; drive adoption through influence, clear technical judgment, and sustained multi-quarter execution.
• Lead design reviews, mentor senior engineers, and unblock the hardest technical problems across distributed teams and systems.
• Provide long-term stewardship via roadmaps, operational maturity (runbooks/SLOs), and incident/postmortem practices suitable for 24/7 global operations.
• Establish yourself as the person others bring their hardest problems to

We’re Excited If You Have

• Bachelor’s in Computer Science or Computer Engineering, or equivalent experience
• Prior experience at Staff, Principal, or Architect level
• Ownership in platform/infrastructure, developer productivity, CI/CD, build systems, or workflow automation, including work spanning globally distributed teams and systems.
• Strong, hands-on knowledge of:

• • Git (workflows, branching strategies, release management)
  • Jenkins (CI/CD pipeline design, scaling, reliability)
  • Docker containers (reproducible build/test execution)

Build systems ( itBake/Yocto preferred)

• Jira (workflow design/automation, cross-team visibility)
• Test management systems (e.g., TestRail or equivalent)
• Demonstrated experience delivering automation at scale, including building platforms/components used by multiple teams.
• Strong systems thinking across security, reliability, performance, and cost tradeoffs.
• Excellent written communication (architecture docs, decision records, operating procedures).
• Experience building AI-assisted developer tooling (e.g., CI insights, test intelligence, code review automation, release risk scoring, incident copilots).
• Experience implementing evaluation/monitoring for AI systems (quality metrics, drift, offline test sets, human feedback loops).
• Extensive experience with software development on embedded Linux,  multi-process architectures and IPC mechanisms
• Experience working in large cross functional teams and ability to influence teams that don't report to you
• Ability to see the big picture while focused on short-term objectives and deliverables
• Ability to multi-task and drive parallel projects and distributed teams with tight deadlines

#LI-NM1

Role Overview:

The Senior Director of Data Engineering & Services is a critical leadership role at Sony Interactive Entertainment (SIE), responsible for shaping and driving the data product strategy that powers intelligence across the company. This role focuses on designing, building, and scaling decision and AI-ready data assets that enable deeper, faster insights and drive data-informed decisions across Player, Creator, Publisher, and Enterprise experiences. It blends deep technical expertise with strong business knowledge, playing a key role in advancing SIE’s connected data ecosystem and enabling the next generation of intelligence and operational efficiency across the company.

You will oversee domain-focused data engineering organizations spanning Player Data, Partner Data, and Enterprise Enablement, driving a unified strategy for how SIE designs, builds, and scales its data products.

• In the Player Data domain, you will define how PlayStation’s player data ecosystem evolves—advancing unified attribution, identity and Player360, and trusted metrics that enable lifetime value modeling, next-best actions, causal measurement, and experimentation across player experiences.
• In the Partner Data domain, you will shape how PlayStation’s partner and creator ecosystem uses data through Partner360, secure data sharing, and self-serve analytics that provide insight into partner performance and lifecycle value—enabling insights that drive creator success, optimize publishing outcomes, and strengthen PlayStation as the preferred platform for partners.
• In the Enterprise Enablement domain, you will lead the strategy and execution of enterprise data capabilities that make SIE’s core functions—Finance, IT, Supply Chain, and HR—increasingly data-driven. Your leadership will ensure these functions operate with connected, governed, and intelligence-ready data, enabling better planning, forecasting, operational efficiency, and strategic decision-making.

What you'll be doing:

Strategic Leadership

• Define and drive the long-term data engineering strategy that powers SIE’s Connected Data Ecosystem — delivering trusted, high-impact data products aligned to strategic business priorities.
• Partner with business and product leaders to identify and deliver the most valuable data opportunities across Player, Creator, Publisher, and Enterprise domains.
• Ensure data engineering teams are building for insight velocity, reusability, and scalability, enabling faster and more informed decision-making across the organization.
• Develop a high-performance engineering culture built on quality, ownership, and continuous improvement across global data teams.

Data Engineering Excellence

• Lead the design, architecture, and execution of SIE’s connected data ecosystem, ensuring seamless integration across business domains and platforms.
• Deliver decision and AI-ready data pipelines and foundational datasets that power analytics, reporting, personalization, and operational intelligence.
• Establish and scale guidelines for data modeling, integration, processing, quality, lineage, and observability.
• Optimize for data usability, trust, and performance while managing cost efficiency and reliability at scale.
• Ensure all data engineering outputs meet enterprise standards for security, privacy, and compliance.

Multi-functional Collaboration

• Partner with Product, Analytics, and Business teams to understand data needs and translate them into scalable, high-quality solutions.
• Collaborate with AI/ML, BI, and Platform teams to ensure data assets are discoverable, governed, and integrated into analytical and operational tools.
• Work closely with Data Governance, Privacy, and Security teams to ensure responsible data use and compliance with regulatory frameworks.
• Drive adoption of data products by ensuring discoverability, documentation, and seamless integration into workflows and decision systems.

Innovation & Efficiency

• Lead initiatives to optimize data operations, improve pipeline efficiency, and reduce total cost of ownership across environments.
• Champion innovation in data engineering — advancing streaming, near-real-time, and event-driven architectures that improve agility and insight delivery.
• Partner with platform engineering to implement new capabilities that enhance data delivery and improve developer productivity.

What we're looking for:

Experience and Technical Expertise

• Proven experience building strong partnerships with product, business, and technology leaders to align on data strategy, accelerate delivery, and improve the strategic value of data across the organization.
• Extensive experience in data engineering or related fields, with deep expertise in designing, building, and scaling enterprise-grade data solutions that enable analytics and business intelligence.
• Proven track record of delivering high-quality, reusable, and trusted data assets that power decision-making across complex global organizations.
• Deep expertise in data architecture and modeling, with experience designing scalable ELT/ETL frameworks and distributed processing systems that support both batch and real-time workloads.
• Proven success in building and optimizing modern data platforms using technologies such as Databricks, Snowflake, and Kafka, with strong focus on data quality, lineage, observability, and reliability.
• Skilled in cloud-native data ecosystems (AWS, Azure, or GCP) and governance practices, ensuring performance, scalability, compliance, and trusted access through tools such as Alation and Collibra.
• Demonstrated ability to design and deliver domain-aligned data products
• Experience working across data privacy and regulatory frameworks, ensuring compliance while supporting global data operations.
• Proven leadership experience in building, mentoring, and growing high-performing global engineering teams, fostering a culture of inclusion, innovation, and accountability.
• Exceptional communicator and collaborator, capable of bridging technical depth and business impact.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Location: This role can be based at our office in Bothell, WA (US) or in Oxford, England (UK).
Travel: Twice per year
Job ID:  1452

The Role

As a Senior Software Engineer for Developer Tools, you will be a key contributor to the software that connects quantum developers to IonQ's hardware. You will focus on contributing to quantum compiler tools and features that our users and internal research teams depend on to run applications. You will build tooling to give users deep insights into how their circuits are optimized and create intuitive, user-friendly interfaces for hardware-specific compiler passes, such as quantum error mitigation and quantum error correction, and ensure our tools are robust and well-documented. You will work closely with our Compiler, QEC, and Applications teams to take new features through development, testing, documentation, packaging, and release, and use software engineering best practices to document, distribute, and use them in quantum software applications.

The Developer Tools team builds the critical software layer for the quantum ecosystem. In this role, you will help shape an ecosystem of tooling that turns high-level quantum circuits into optimized instructions for our quantum computers. Your work will directly impact the performance, reliability, and capabilities of quantum applications running on IonQ systems by focusing on the compiler's application-facing features and its connection to the hardware.

The compiler is where quantum algorithms meet quantum hardware. Your work sits at the heart of this critical transformation. The tools you build will define how developers interact with our systems, enabling them to extract maximum performance, trust the compilation process, and tailor optimization strategies for their specific use cases.

By focusing on compiler tools for applications, you empower developers to tackle real-world problems and push the boundaries of what's possible on quantum computers. You'll make advanced techniques accessible, from sophisticated error mitigation to hardware-aware compilation. This role offers a unique opportunity to work with world-class researchers and translate their innovations into production software that accelerates the path to quantum advantage for everyone.

Responsibilities:

• Design, build, and maintain compiler toolchains, optimization tools, and circuit transformation libraries for developer-facing applications.
• Work with the Compiler and Applications teams to package, test, and document new compilation features for both internal and external developers.
• Architect and implement interfaces for hardware-specific compilation features, giving developers deeper control and visibility.
• Integrate automated error mitigation, quantum error correction, and other advanced compilation strategies into our cloud platform and SDKs.
• Maintain comprehensive documentation, examples, and tutorials for compilation workflows.
• Support the testing and validation of compilation features across different IonQ backends and system configurations, and capabilities such as mid-circuit measurement and branching.
• Collaborate with the Applications Engineering team to understand and address customer needs related to compilation and circuit optimization.

Requirements:

• Bachelor's degree in Computer Science, Engineering, Physics, or a related field, or equivalent training, fellowship, or work experience.
• 6+ years of professional software engineering experience in team environments.
• Deep proficiency in Python, our primary language.
• Experience with quantum computing, with an understanding of quantum gates and circuits.
• Familiar with the fundamentals of quantum compilation, error mitigation and quantum error correction.
• Experience with software maintenance, user community stewardship and software engineering best practices.
• Experience working with research or academic concepts and integrating them into scientific software workflows.
• Familiarity with Agentic AI coding tools and techniques such as skills, docstring generation, code review, and software engineering best practices.
• A track record of creating clear, comprehensive technical documentation.
• Experience with automated testing, CI/CD pipelines, and scientific software validation.
• Strong collaboration skills, with experience working across research and engineering teams.

Preferred Qualifications:

• 8+ years of professional software experience.
• An advanced degree (PhD or Master's) in Physics, Computer Science, or a related field with a focus on quantum computing.
• A background in compiler development for either classical or quantum systems.
• An interest in or experience with hardware-level and hardware-specific compilation, such as pulse-level control or dynamic circuits.
• System-level programming experience with C++ or Rust for performance-critical code.
• Deep experience with quantum compilers, circuit optimization, or quantum error correction.
• Experience with quantum computing SDKs (Qiskit, Pennylane, Cirq).
• Understanding of trapped-ion quantum computing systems and their specific noise characteristics.
• Proficiency with or strong interest in open-source compiler tools like ucc and jeff
• Publications or significant contributions to quantum computing research or open-source projects.

The approximate base salary range for this position is $145,920 - $191,047 (USD). The total compensation package includes base, bonus, equity, and a range of benefit options found on our career site.

Available Locations: London (hybrid), the Netherlands (remote), Paris, or Munich

About the Role

Cloudflare’s Forward Deployed Engineers (FDEs) operate at the intersection of product engineering and customer impact.

As an FDE, you will be embedded within one of Cloudflare’s most strategic global customers, working side-by-side with their engineering teams to build and deploy solutions using Cloudflare’s platform. Unlike traditional Solutions Architects or consultants, you will write production code, shape technical architecture, and directly influence how Cloudflare products are used at massive scale.

You will operate as a technical extension of both organizations - helping the customer ship faster while surfacing real-world product insights back to Cloudflare engineering.

This role is ideal for engineers who want to:

• Stay deeply technical
• Work on real production systems
• Influence product direction
• Build long-term partnerships with world-class engineering teams

Responsibilities

• Deep Technical Embedding: Serve as the dedicated, long-term technical partner within a strategic customer’s engineering organization, operating as a trusted extension of their team.
• Production-Level Engineering: Design, build, and deploy production-ready code and configurations directly into customer infrastructure using the Cloudflare platform.
• Technical Accountability: Own the account's technical success across the entire Cloudflare portfolio. Serve as the primary technical point of contact, with other Cloudflare technical resources taking direction from your technical strategy for the account.
• Operational Integration: Participate in customer engineering rituals, including daily standups, design reviews, and real-time incident response.
• Platform Advocacy & Adoption: Identify opportunities to accelerate the adoption of Cloudflare services, unlocking new capabilities across the customer’s tech stack.
• Platform Breadth & Depth: Deep technical competence in building production applications on a modern stack, combined with the willingness and ability to go deep on all Cloudflare product areas. From Workers to security, networking, and observability.
• Feedback Loop & Product Influence: Surface real-world edge cases and product gaps directly to Cloudflare’s Product and Engineering teams to influence the developer platform roadmap.
• Strategic Relationship Management: Establish and maintain trusted technical relationships with senior leadership (Staff+ engineers, Directors, and VPs).
• On-Site Presence: Maintain a regular on-site presence at customer locations to foster deep collaboration and cultural alignment.

Requirements

• Proven Engineering Pedigree: 5+ years of professional software engineering experience. You are a builder at heart, with a track record of delivering production-grade systems, not just advising on them.
• Production Ownership & Operational Maturity: You have owned mission-critical services with real-world users. You understand the gravity of on-call rotations, the urgency of incident response, and the architectural rigor required to maintain "five nines" uptime.
• Active Practitioner: You are currently in the IDE. You have a "ship-first" mentality and maintain a high velocity, staying current with modern frameworks, languages, and deployment patterns.
• Full-Stack Architectural Depth: Broad technical fluency across the entire stack—from frontend performance and backend logic to database optimization and distributed infrastructure.
• AI-Native Development: You have integrated AI-augmented workflows (e.g., Windsurf, OpenCode) into your daily development cycle to accelerate prototyping and delivery.
• Systems Design & Strategic Thinking: Ability to decompose complex business requirements into scalable, resilient technical architectures. You can visualize the "big picture" without losing sight of the implementation details.
• Cloud Ecosystem Fluency: Deep experience with at least one major cloud provider (AWS, GCP, or Azure), including an understanding of serverless, networking, and security primitives.
• High Agency & Navigating Ambiguity: You are a self-starter who thrives in "zero-to-one" environments. You don't wait for a ticket; you identify the problem and own the solution from end-to-end.
• Executive Presence: Comfortable engaging in high-stakes technical and strategic discussions with VP-level stakeholders, with the ability to translate complex engineering trade-offs into business impact.
• Fluency in Hebrew and English

Nice to Have

• Direct experience building on Cloudflare Workers, or the broader Cloudflare Developer Platform.
• Previous experience at a fast-paced startup or in a customer-facing engineering role where you operated directly within a partner’s codebase.
• A visible public profile, including open-source contributions, technical blogging, or speaking engagements at industry conferences.

Staff Site Reliability Engineer

As a Staff SRE at Obsidian, you will define and drive the company-wide reliability vision for a complex, multi-tenant SaaS platform serving enterprise and financial customers. You will operate as a strategic partner to DevOps and Platform Engineering leadership, shaping a unified reliability strategy that scales across the organization.

Your core mandate: ensure Obsidian detects, diagnoses, and communicates system issues before customers are impacted—consistently and predictably.

This is a hands-on technical role that involves architecting and leading the implementation of systems that handle real-world complexity, including upstream SaaS dependencies, sparse and noisy signals, and mission-critical enterprise workloads.

Key Responsibilities

• Reliability Strategy & Architecture - Define and lead long-term reliability strategy across services. Establish end-to-end system visibility frameworks and guide architecture for observability, detection, and resilience.
• Cross-Org Leadership - Partner across teams to embed reliability, standardize SLI/SLOs, and serve as a technical escalation expert.
• Detection & Observability - Build intelligent detection systems (anomaly detection, connector health models) and enable self-service observability.
• Incident Management - Define and evolve a tiered incident communication strategy, improve response practices, and lead postmortems to strengthen reliability and customer trust.
• Execution - Contribute hands-on to system design, monitoring, and debugging across distributed systems and data pipelines.

Required Qualifications

• 5+ years in SRE, Production Engineering, or related roles
• 3+ years operating at a senior or technical leadership level (Staff or equivalent scope)
• Deep expertise in:
• AWS and/or GCP
• Kubernetes and Helm
• Observability stacks (Prometheus, Grafana, or equivalent)
• CI/CD systems (GitLab CI/CD, ArgoCD, etc.)
• Proven experience designing and scaling reliability systems for multi-tenant SaaS platforms
• Strong debugging and systems thinking across distributed microservices and legacy systems
• Demonstrated ability to lead initiatives that improve incident detection, response, and system resilience
• Hands-on engineering approach with a track record of building—not just configuring—reliability systems

Preferred Qualifications

• Experience in B2B SaaS serving enterprise or financial customers
• Familiarity with third-party SaaS connector architectures and ingestion patterns
• Experience building anomaly detection or intelligent alerting systems
• Experience designing customer-facing status pages and incident communication frameworks

Why This Role

• Drive org-wide reliability strategy
• Own and build new detection & observability systems
• Tackle complex distributed systems challenges
• Safeguard critical infrastructure for financial customers

What Success Looks Like

• Issues caught and resolved before customer impact
• Reliability is measurable and continuously improving
• Teams self-serve observability with scalable tools
• Clear, proactive incident communication builds trust
• Reliability becomes a competitive advantage

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

Nebius is looking for a Senior Technical Recruiter to strengthen our Talent Acquisition team and help us attract top technical talent. In this role, your primary focus will be on active sourcing and building strong pipelines of backend engineers, system engineers, and technology experts to support the company’s continuous growth.

Remote working, Based in the UK (London) OR Netherlands, working Hybrid from Amsterdam.

Your responsibilities will include:

• Technical Talent Sourcing: Proactively identify and engage engineers and other tech specialists through diverse channels (LinkedIn, GitHub, Boolean Search, professional communities, conferences, forums, networking, employee referrals).

• Pipeline Development: Build, maintain, and continuously refresh a pool of qualified engineers and developers for current and future hiring needs; provide funnel statistics to Hiring Managers (e.g., number of applicants, time to hire, etc.).

• Candidate Engagement: Craft personalized outreach and communication to spark interest and showcase opportunities at Nebius. Engage in pre-onboarding activities and contribute to HR projects.

• Screening: Conduct resume reviews and initial calls to assess candidates’ technical background, experience, and motivation.

• Collaboration with Hiring Managers: Partner with engineering leaders to deeply understand role requirements and design effective sourcing strategies.

• Market Research & Insights: Stay on top of industry trends, tech community activity, and competitor hiring practices. Identify the best companies to target for top-tier technical talent.

We expect you to have:

• 4+ years of experience in technical recruitment, specializing in Backend/General Tech such as (but not limited too): Software Engineers, Python Engineers, Platform Engineers, Cloud Platform Engineer, Site Reliability and Infrastructure Engineers, DevOps, Systems Engineers and Data Platform Engineers.

• Strong sourcing expertise and familiarity with tech talent pools, platforms, and communities.

• Deep understanding of tech subject areas, developers’ roles, technologies, and motivations, plus insight into which companies are the best sources of top candidates.

• Ability to manage multiple priorities and work in a fast-paced environment.

• Excellent follow-through, organizational, presentation, and communication skills (both written and verbal).

• Creative problem-solving skills with the ability to adapt quickly.

• Serverless AI has clear product-market fit with measurable activation and retention metrics improving quarter over quarter.
• Multi-node jobs and autoscaling endpoints are shipped and adopted by customers running production workloads.
• Cold start time is reduced from 1-3 minutes to under 60 seconds for common workloads through a combination of product and infrastructure improvements you drove.
• Developer experience (CLI, docs, error messages, onboarding flow) sets the standard that developers expect from a next-generation AI cloud.
• At least 3 product decisions you made are directly attributable to customer conversations or data analysis you conducted.

• Co-own the Serverless AI product roadmap — Jobs, Endpoints, and DevPods — taking primary ownership of specific product areas while collaborating closely with the other PM on shared priorities and cross-cutting decisions.
• Write detailed, technically precise PRDs that engineering teams can execute against. Our PRDs specify CLI syntax, API contracts, state machines, and billing models — not abstract feature descriptions.
• Make build/buy/defer decisions on capabilities like autoscaling, multi-node orchestration, HTTPS termination, secret injection, and health checking based on customer signal and strategic priorities.

• Understand the full workload lifecycle: container image pull → VM provisioning → GPU attachment → workload execution → cleanup — well enough to identify bottlenecks and propose solutions.
• Evaluate technical trade-offs in areas like container cold start optimization (image caching, snapshot restore, warm pools), GPU scheduling and bin-packing, and storage mount performance.
• Work directly with engineers on architecture decisions for distributed training support, endpoint autoscaling policies, and fault tolerance mechanisms.
• Stay current on the fast-moving serverless GPU infrastructure space — new inference frameworks (vLLM, TensorRT-LLM, SGLang), container runtimes, orchestration approaches — and translate trends into product direction.

• Run customer discovery and feedback sessions with ML engineers and platform teams at AI startups and enterprises. Turn qualitative insight into specific product actions.
• Analyze usage data, activation funnels, and churn patterns to identify where users get stuck and what features drive retention.
• Track market dynamics, emerging technologies, and industry trends to inform product strategy and ensure Nebius stays ahead of where the market is heading.
• Define and iterate on pricing, packaging, and tier strategy for Serverless AI.

• Own the technical content strategy: quickstart guides, tutorials, reference architectures, and example workloads that reduce time-to-first-job.
• Partner with marketing on developer-focused campaigns, webinars, and conference presence.
• Work with Solution Architects and Sales to qualify serverless-fit opportunities and support technical evaluations.

• You have built, shipped, and iterated on infrastructure or platform products used by developers or ML engineers. Not consumer apps. Not dashboards. Infrastructure.
• You understand containers at a practical level — Docker, image registries, container runtimes, resource limits, networking. You've debugged why a container won't start, why GPU isn't visible inside it, or why a mount isn't working.
• You have working knowledge of GPU computing for AI/ML: what GPU types exist and when to use them, how training and inference workloads differ in resource requirements, what vLLM / TensorRT-LLM / Triton are and why they matter.
• You can read a CLI reference and know if it's well-designed. You've shaped developer-facing APIs, CLIs, or SDKs.
• You have run real customer discovery — not surveys, but technical conversations with engineers where you learned something that changed your product direction.
• You have 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.

• Ability to whiteboard a workload lifecycle (submit → schedule → provision → execute → cleanup) and identify failure modes at each step.
• Understanding of autoscaling trade-offs: scale-to-zero vs. warm pools, scaling metrics (queue depth, latency, utilization), cold start implications.
• Familiarity with inference serving concepts: batching, model loading, quantization, KV-cache management, multi-model serving.
• Understanding of distributed training concepts: data parallelism, model parallelism, communication overhead, checkpointing.
• Ability to reason about pricing models: per-second vs. per-request vs. per-token, and how pricing interacts with product architecture.

• Experience at a serverless or GPU cloud company.
• Hands-on ML engineering background — you've trained models, deployed inference endpoints, or built ML pipelines yourself.
• Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve) and understanding of why many ML teams want to avoid it.
• Prior experience building a product from early stage to scale in a fast-growing market.
• Background in systems engineering, distributed systems, or site reliability engineering.

• You are more comfortable in a terminal than in a slide deck.
• You form strong opinions based on data and direct customer signal, and you update them when evidence changes.
• You are energized by building at pace — small team, fast-evolving product, big opportunity.
• You care about developer experience at the level of error messages, CLI flag naming, and documentation quality.
• You'd rather ship a smaller thing that works perfectly than a bigger thing that's mediocre.

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

One of the projects we’re working on within the JetBrains Innovation Hub is the AppGlass, a product for safe, AI-first debugging of production systems. It will help engineering teams investigate issues in real environments with a strong focus on safety, reliability, security, low overhead, and practical AI integration. That means it’s a mix of JVM tooling, program analysis, and AI at the core. Check out our demo and website to get a better sense of how it works.

About the role

We are looking for a Senior Software Engineer with strong enterprise JVM experience. This role is a good fit for someone proactive and excited by complex engineering challenges at the intersection of production systems, developer tools, and AI agents.

In this role, you will:

• Design, build, and lead the development of product features.
• Develop tooling and automation for AI-first engineering workflows.
• Work on enterprise integrations and deployment scenarios across Kubernetes and cloud environments.
• Improve reliability, testing, performance, and security for production use.

We’d like to have you on the team if you:

• Have extensive experience with Java, Kotlin, and JVM systems.
• Have worked on enterprise backend software, infrastructure, or developer tooling.
• Are comfortable with Kubernetes and cloud environments.
• Take ownership, communicate clearly, and move things forward without waiting for perfect specs.
• Enjoy using AI in development, while validating results with solid engineering discipline.

We’ll be especially thrilled if you:

• Have experience with debugging, instrumentation, or observability-related tools.
• Have experience with .NET or Python backend products.
• Care deeply about developer productivity and engineering quality.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-REMOTE 
#LI-KT1

Little more about the team:

The Solution Architecture team sits at the intersection of technology, customer advocacy, and revenue, working Honeycomb's most strategic opportunities. We partner with world-class engineering organizations to solve complex observability challenges and change how teams build and operate software. This is a team of hands-on technical leaders who want to shape major customer decisions, influence go-to-market strategy, and redefine what great technical selling looks like.

What you’ll do in the role:

• Own the technical strategy for complex sales opportunities, partnering closely with Account Executives and sales leadership to move deals forward.
• Lead discovery, solution design, and technical validation for customer environments with multiple stakeholders and competing requirements.
• Run complex evaluations and proofs of concept end-to-end, including success criteria, technical execution, risk identification, and debrief.
• Translate customer architectures into clear solution narratives that connect Honeycomb’s platform to engineering priorities and business outcomes.
• Deliver compelling demos, workshops, and technical presentations tailored to audiences ranging from practitioners to director-level stakeholders.
• Get hands-on when it matters: support instrumentation strategy, troubleshoot integration issues, and help customers prove value in real environments.
• Manage competitive evaluations and bake-offs with strong judgment, disciplined execution, and a clear point of view on Honeycomb’s differentiation.
• Identify technical and strategic risks across active deals and proactively adjust the evaluation approach when needed.
• Partner across Sales, Product, Field Engineering, Marketing, and DevRel to unblock deals and improve the overall go-to-market motion.
• Contribute reusable architectures, demo assets, and technical content that increase team effectiveness and scale best practices.
• Bring structured field insight back into the company to help inform product feedback, messaging, and technical strategy.
• Mentor more junior Solution Architects through collaboration, coaching, and shared learning.

What you’ll bring to the role:

• 5+ years of pre-sales, solution architecture, sales engineering, or customer-facing technical experience in B2B SaaS.
• Experience supporting complex technical sales cycles with multiple stakeholders, ideally in enterprise or commercial accounts with sophisticated engineering teams.
• Strong solutioning skills and the ability to turn ambiguous customer needs into clear technical approaches and evaluation plans.
• Deep working knowledge of observability, distributed systems, distributed tracing, and OpenTelemetry.
• Hands-on fluency with modern cloud environments, containers, Kubernetes, API-driven architectures, and at least one major cloud provider.
• Ability to troubleshoot instrumentation and integration issues across a range of languages, frameworks, and deployment patterns.
• Experience owning POCs or technical evaluations, including defining success criteria, managing risk, and driving toward measurable outcomes.
• Strong consultative communication skills, with the ability to tailor technical messaging across practitioners, architects, and director-level stakeholders.
• Credibility with developer, platform, SRE, and engineering-led audiences through both technical depth and business context.
• A clear point of view on Honeycomb’s value and differentiation in the observability landscape.
• Strong judgment, autonomy, and follow-through in fast-moving deal environments.
• A collaborative, low-ego working style with the ability to pull in cross-functional partners when the situation calls for it.
• A mentorship mindset and desire to make the team stronger through coaching, documentation, and reusable work.
• Familiarity with MEDDPICC or Command of the Message is a plus.
• Willingness to travel ~20% for customer engagements, field events, and internal collaboration.

Little more about the team:

The Solution Architecture team sits at the intersection of technology, customer advocacy, and revenue, working Honeycomb's most strategic opportunities. We partner with world-class engineering organizations to solve complex observability challenges and change how teams build and operate software. This is a team of hands-on technical leaders who want to shape major customer decisions, influence go-to-market strategy, and redefine what great technical selling looks like.

What you’ll do in the role:

• Own the technical strategy for complex sales opportunities, partnering closely with Account Executives and sales leadership to move deals forward.
• Lead discovery, solution design, and technical validation for customer environments with multiple stakeholders and competing requirements.
• Run complex evaluations and proofs of concept end-to-end, including success criteria, technical execution, risk identification, and debrief.
• Translate customer architectures into clear solution narratives that connect Honeycomb’s platform to engineering priorities and business outcomes.
• Deliver compelling demos, workshops, and technical presentations tailored to audiences ranging from practitioners to director-level stakeholders.
• Get hands-on when it matters: support instrumentation strategy, troubleshoot integration issues, and help customers prove value in real environments.
• Manage competitive evaluations and bake-offs with strong judgment, disciplined execution, and a clear point of view on Honeycomb’s differentiation.
• Identify technical and strategic risks across active deals and proactively adjust the evaluation approach when needed.
• Partner across Sales, Product, Field Engineering, Marketing, and DevRel to unblock deals and improve the overall go-to-market motion.
• Contribute reusable architectures, demo assets, and technical content that increase team effectiveness and scale best practices.
• Bring structured field insight back into the company to help inform product feedback, messaging, and technical strategy.
• Mentor more junior Solution Architects through collaboration, coaching, and shared learning.

What you’ll bring to the role:

• 5+ years of pre-sales, solution architecture, sales engineering, or customer-facing technical experience in B2B SaaS.
• Experience supporting complex technical sales cycles with multiple stakeholders, ideally in enterprise or commercial accounts with sophisticated engineering teams.
• Strong solutioning skills and the ability to turn ambiguous customer needs into clear technical approaches and evaluation plans.
• Deep working knowledge of observability, distributed systems, distributed tracing, and OpenTelemetry.
• Hands-on fluency with modern cloud environments, containers, Kubernetes, API-driven architectures, and at least one major cloud provider.
• Ability to troubleshoot instrumentation and integration issues across a range of languages, frameworks, and deployment patterns.
• Experience owning POCs or technical evaluations, including defining success criteria, managing risk, and driving toward measurable outcomes.
• Strong consultative communication skills, with the ability to tailor technical messaging across practitioners, architects, and director-level stakeholders.
• Credibility with developer, platform, SRE, and engineering-led audiences through both technical depth and business context.
• A clear point of view on Honeycomb’s value and differentiation in the observability landscape.
• Strong judgment, autonomy, and follow-through in fast-moving deal environments.
• A collaborative, low-ego working style with the ability to pull in cross-functional partners when the situation calls for it.
• A mentorship mindset and desire to make the team stronger through coaching, documentation, and reusable work.
• Familiarity with MEDDPICC or Command of the Message is a plus.
• Willingness to travel ~20% for customer engagements, field events, and internal collaboration.

As part of the Data Infrastructure team you will be supporting mission critical big data platforms, to ensure they are fully performant, reliable, available and secure. We call it data infrastructure engineering, also known as DataOps or Database Administration or SRE.

The role is a mixture of development of tooling and operational support for our platforms, two aspects that go hand-in-hand. It requires attention to detail and curiousity about how the systems work under the hood, and gives you a wide base of skills from low level system tuning to general coding. 

We manage four main storage platforms, namely:

• Apache Solr (~2.2 PB)
• Apache HBase (~450 TB)
• PostgreSQL (~15 TB)
• Kafka (~60 TB)

These platforms are all open source, written in Java, Scala or C, and we maintain in-house builds and patching of them. We use a variety of open-source and in-house developed tooling to manage these services, mostly written in Rust and Python, which run primarily on hundreds of servers in multiple data centres and in the cloud.

We maintain a balance between project work and operational/ad-hoc work for all members in the team, whether they are senior or recent graduates, and your day-to-day work will be a mix of these.

The exact project work will depend on your experience, but we will scope it out collectively to ensure it is both achievable and delivers benefit. Some example projects given to recent graduates are:

• Coding mapreduce jobs to validate data between two multi-TB+ hbase clusters (to run in hours rather than months)
• Building out a python code stack to transparently migrate production clients between clusters (without losing any data or requiring any downtime)
• Building and testing new HBase builds and deploying them live (without putting everyone in Brandwatch out of a job)
• Creating a platform for rolling out our data management systems using Apache Airflow (to stop people re-writing custom job management systems)
• Rolling out a DR solution for hadoop on AWS (while keeping the system performant and not bankrupting the company)

If you're joining the team as a graduate engineer we'll be focusing on developing your knowledge of the storage platforms, how to program against them and how to troubleshoot issues. The aim is that you'd be able to help with the staging support by 3-6 months, and join the rest of the team supporting the production systems in 12 months. You'll also be expected to take a full part in the life of the team and, as your experience grows, start designing the infrastructure we run.

This role is based in Brighton, UK, but working remotely will be possible once the initial 6-12 months of training is complete.

Who we are looking for

In house training for the storage systems and our tooling is a necessary part of this role, but we are looking for someone with a keen interest in large scale storage infrastructure.A successful candidate will be expected to have the following:

• An interest in how computer infrastructure actually works, and a passion for learning
• Interest, and ideally production experience, running storage systems, eg. as part of a selfhosted service, a home lab or as part of academic studies
• Experience with Linux systems administration, including experience of trouble shooting
• Fluency with one or more scripting languages, ideally Bash or Python
• Experience helping your peers
• Pride in the quality of your work
• Experience with any of the following will be beneficial:
  • Development experience, in Python, Java, Rust, C/C++ or Golang.
  • Upstream open-source contributions
  • Academic research in scalability, distributed systems or storage infrastructure
  • Kubernetes experience, ideally running or writing Operators Experience with Docker and with CI/CD pipelines

This is a remote opportunity and we would be interested in applicants living in UK time zones only at this time. 

Senior Software Engineer - Grafana Databases, Managed Services

The Opportunity: 

The Managed Services team is a newly formed squad within the Databases department. It owns and operates shared, production-critical infrastructure that powers Grafana Cloud’s next-generation database products (Mimir, Loki, and Tempo). Today, this includes operating 100+ WarpStream clusters across multiple cloud providers and regions, with continued growth anticipated for the future. WarpStream acts as the streaming backbone for ingestion and read/write decoupling across databases. It sits directly on the hot path for metrics, logs, and traces, handling high-throughput, multi-consumer workloads at massive scale.

In addition to streaming infrastructure, the team works closely with high-volume analytical and storage systems that power query-heavy and aggregation-heavy workloads, where latency, compression behavior, storage layout, and scaling characteristics matter deeply.

What You’ll Be Doing:

As a Senior Engineer on Managed Services, you will take ownership of running these systems in production. This involves:

• Operating and evolving 100+ multi-cloud streaming clusters and related database infrastructure
• Diagnosing and eliminating cross-layer failure modes (e.g., object storage latency, noisy neighbors, control-plane bottlenecks, query performance regressions, etc.)
• Designing safe upgrade and rollout strategies at scale
• Improving observability, automation, and operational ergonomics
• Partnering closely with database and platform teams to ensure safe scaling, partitioning, consumer fan-out, and query performance
• Working directly with distributed systems behavior, Kubernetes scheduling dynamics, storage engines, compression trade-offs, etc.
• Serving as a primary escalation point and on-call for relevant incidents
• Owning the relationship with all system vendors, including WarpStream Labs and others.
• As we are remote-first and our engineering organization is largely remote, we provide guidance and meet regularly using video calls, so an independent attitude and good communication skills are a must.

This role blends deep distributed systems work with the opportunity to influence how the team approaches reliability, scaling, and operational excellence.

We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always paired with strong code review and quality standards. You’ll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro).

Of course, there is an on-call component to this role and one that we take seriously. As a company, we hire globally (remote-first) to ensure our on-call remains healthy and aligned to approximately 12 daylight hours per day. You will work closely with counterparts in other regions to provide balanced coverage and shared ownership.

What Makes You a Great Fit:

• Regular 1:1s with your manager and close collaboration with teammates across regions
• Reviewing and defining SLOs for shared database infrastructure, proactively reducing error budgets through improvements to monitoring, automation, scaling strategies, and system design
• Improving the diagnosability of core streaming and database systems in production, where possible.
• Implementing solutions that ensure reliability, scalability, and performance of high-throughput, multi-cloud infrastructure
• Developing fault-tolerant patterns that account for distributed system realities such as storage latency, partition imbalance, noisy neighbors, and control-plane dependencies
• Planning and executing safe upgrades and rollouts across dozens of production clusters
• Collaborating with database and platform engineering leaders to influence architecture, roadmap priorities, and long-term strategy
• Participating in PR review and contributing to design documents, automation, tooling, and code improvements that reduce operational risk
• Sharing best practices and distributed systems knowledge with partner teams
• Participating in incident response, from investigation through resolution and post-incident reviews (PIR)

Requirements:

• 6+ years of engineering experience, including meaningful time in SRE, platform engineering, production engineering, infrastructure engineering, or distributed systems roles.
• Experience operating distributed systems in production (e.g., streaming systems, analytical databases, large-scale storage backends). Examples of these include Kafka, Redpanda, WarpStream, Postgres, ClickHouse, Snowflake, or Cassandra.
• Strong Kubernetes experience in AWS, GCP, or Azure, and familiarity with infrastructure-as-code tooling (Helm, Terraform, Jsonnet, etc.).
• Solid understanding of distributed systems design and large-scale system trade-offs.
• Proficiency in at least one programming language (Go preferred, but not required).
• Working knowledge of Linux internals, networking, cloud storage, and performance/scaling behavior.
• Experience participating in blameless incident response and writing high-quality post-incident reviews.
• Clear communicator who can collaborate across teams and work autonomously.
• Curious, pragmatic, action-oriented, and kind (this is important!)
  
  

Compensation & Rewards:

In the United Kingdom, the Base compensation range for this role is GBP 91,755 - GBP 110,106. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here.

All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.

This is a remote opportunity and we would be interested in applicants based in Spain, Sweden, Germany, the UK or Ireland at this time. 

The Opportunity

The Grafana Frontend group is responsible for the end to end user experience on Grafana the observability product and Grafana the platform used by many engineers to build plugins. Our squads are responsible for dashboards, data visualisation and manipulation, navigation across the ecosystem, sharing experience, content search,organisation and more.

DataPro

The DataPro squad develops tools that empower users to express their data. We serve as the bridge between data producers (Data Sources) and consumers (Data Visualizations), enhancing the capabilities of data sources in line with our "big tent" philosophy.

What we do:

Query experience & Data manipulation: We build and evolve the query experience as well as the engine and components behind the Grafana data transformations experience, which primarily includes Transformations and SQL Expressions.Community Engagement: we listen to the open-source community, we retrieve contributions, and turn feedback into real improvements.

• Operational Excellence: we own the performance, reliability, and maintainability of a system that runs at global scale. We value readability, maintainability and clarity of our code. 

How we work:

• No blame: We focus on learning and improving ourselves and our product.
• Better done than perfect: We iterate quickly and deliver value continuously.
• User-first: We design for real users solving real problems and we make data-driven decisions.

• Mentorship & Innovation: we grow together through knowledge sharing, mentorship, internal hackathons, and constant learning.

What You’ll Be Doing

As a Senior  Software Engineer at Grafana Labs, you will:

• Take an active role in influencing our roadmap and your own career objectives
• Drive projects from initial idea all the way to operations once it is in the hands of customers
• Be a part of your team’s on-call rotations and take ownership of the services you’re running
• Mentor and support other team members, participate in design discussions and collaborate with the team
• Learn new skills by gaining a deeper understanding of our cloud product and our customers and getting to know the codebase
• Contributing to and reviewing design documents for upcoming features

We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction.

We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always paired with strong code review and quality standards.

You’ll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro).

What Makes a Great Fit

• Strong engineering skills: Solid experience building production software systems. You’re a self-starter, capable of tackling complex engineering problems with minimal supervision. You treat writing tests as a core part of the development process, not an afterthought. You have experience with TypeScript and React, Jest and Playwright.
• Complex operational thinking: Can take on complex challenges and break them down into tight feedback loops: analyze, design, ship an MVP, gather data, then iterate.
• Proven initiative and pragmatism: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and define scope, breaking complex challenges down to achieve short feedback loops. 
• Collaborative attitude: You communicate effectively with peers, product managers, and designers. You’re open to feedback, and you bring a solutions-oriented mindset to the table.
• Enjoy learning, growing, and supporting others to do the same. 
• Appreciate efficiency and strive to identify and utilize the most effective tools for the task at hand. You naturally share your use of these tools with your team to maintain transparency and growth.

Bonus Points For

• Experience with open source software and/or commercial open source companies
• Been a user of Grafana and Prometheus in operational roles
• Familiarity with being on-call and performing operations/SRE tasks
• Have an active interest in observability (Metrics, Logs and Traces) and have experience with tools like Grafana, Prometheus, or other observability platforms.
• Have experience mentoring engineers in a collaborative but asynchronous environment, and see it as a meaningful
• Care about our community of users and contributors and are keen to be an active Grafana Community Contributor.

We understand that you may not have experience on all of the above. Please do apply even if you do not match some of the above criteria.

In United Kingdom, the compensation range for this role is GBP 91,755 - GBP 110,106. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.

Job Title: Reliability Engineer

Location: Smart parc, Spondon, Derby DE21 7HW

Shift: Suez Shift Pattern rotating days and nights, 0600-1800 and 1800-0600.

Let's Discuss What's On The Table For You:

• 70% off HelloFresh or Green Chef boxes 
• Free onsite parking (including ~90 EV spaces)
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Nursery support scheme (save up to 40% on your nursery fees)
• Earn up to £500 with our Referral Program
• Electric vehicle scheme
• Cycle to work scheme
• Group Life Assurance
• Company pension scheme
• Mental health first aiders and an employee assistance programme

Play a key part in supporting our Employee Resource Groups: FreshVets, Black Heritage Network, NEU Network (Neurodiversity), GET (Gender Equality Team) and FreshPride

About The Team:

As a Reliability Engineer, you will be responsible for ensuring the maintenance, repairs, and improvements of both automated and non-automated systems on-site. The Reliability Engineer will work to ensure maximum uptime and reliability of equipment while actively participating in both preventive and reactive maintenance tasks. This role will also support automation systems, including conveyance and facilities equipment.

What You Will Be Doing:

• Hands-On System Monitoring & Repair: Actively monitor, troubleshoot, and repair systems to provide a high level of equipment availability.
• Preventive Maintenance & Inspections: Perform routine maintenance on automation, robotics, and control panels.
• Troubleshooting & Escalation: Diagnose and address issues in out-of-service equipment; escalate complex issues as necessary.
• Documentation: Record all work in the Computerized Maintenance Management System (CMMS) and ticketing systems as appropriate.
• Contractor Collaboration: Work with contractors to ensure projects are completed to specification, addressing performance issues as needed.
• Project & Ad Hoc Engineering Tasks: Participate in cross-functional projects as required.
• Predictive & Preventative Maintenance: Engage in predictive maintenance activities to maintain machine uptime for operational needs.
• Training & Mentorship: Provide training and mentorship to Junior Engineers on reliability practices and techniques.
• Health & Safety Compliance: Adhere to and support food safety and health & safety standards.
• Root Cause Analysis: Participate in Root Cause Analysis (RCA) for continuous improvement.

Who You Are:

• Hold a degree in computer science, mechanical engineering, electrical engineering, or a related field would be advantageous. 
• Skilled in material handling, flow and capacity visualisation, and monitoring.
• Proficient in PLC-controlled automation and issue diagnosis in continuous production environments.
• Extensive experience with PLCs, HMIs, VFDs, including programming, troubleshooting, and maintenance.
• Advanced understanding of PLCs and automated processes.
• Analytical Skills: Strong problem-solving abilities for technical issues in automation systems.
• Project Management: Excellent organisational skills, with the ability to prioritise tasks, manage timelines, and deliver results within budget.

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

About The Team:

This role sits within the Facilities and Maintenance department and reports directly to the Senior Reliability Manager. It is responsible for coordinating and scheduling maintenance activities to ensure the smooth and efficient operation of our facilities. You’ll play a key role in minimising downtime, maximising equipment reliability, and optimising maintenance resources to support production operations.

Working closely with the Maintenance Manager, Senior Facilities Manager, and wider leadership team, you’ll help keep maintenance operations running seamlessly while acting as the site CMMS subject matter expert (SME).

What You Will Be Doing:

• Conduct audits and verify CMMS data accuracy—ensuring all equipment and assets are correctly recorded, identified, and up to date in the system.
• Work closely with maintenance, operations, and production teams to design and deliver effective maintenance plans, schedules, and procedures that keep everything running at its best.
• Take ownership of incoming work orders—reviewing, prioritising, and coordinating resources to ensure the right work gets done at the right time.
• Drive a proactive approach to maintenance by developing and managing preventive programmes, including inspections, servicing, and component replacement to reduce downtime and extend equipment life.
• Partner with inventory teams to ensure critical spare parts and consumables are always available—monitoring stock, managing reorders, and building strong supplier relationships.
• Turn data into action by analysing equipment performance (downtime, costs, history) to spot trends, produce insights, and recommend improvements that boost reliability and efficiency.
• Keep everything documented and organised, maintaining accurate records of maintenance activities, manuals, and logs for full traceability.
• Champion a strong safety culture by ensuring Food Safety and Health & Safety standards are consistently met—taking responsibility for your own safety, reporting incidents promptly, and raising concerns when needed.
• Apply practical problem-solving skills to day-to-day challenges, escalating to Maintenance Management when required to keep operations on track.
• Ensure full compliance with Standard Operating Procedures (SOPs) and work instructions, maintaining high operational standards at all times.
• Coordinate service and support functions effectively, helping to ensure smooth, uninterrupted operations across the site.

Who You Are:

• Strong CMMS experience with a track record of improving reliability and efficiency.
• Practical knowledge of material handling equipment and how to maintain it effectively.
• Experience planning and scheduling maintenance to keep operations running smoothly.
• Confident using MS Office or Google tools for day-to-day tasks and reporting.
• Able to read and understand technical drawings and schematics.
• Good understanding of food safety standards in a maintenance environment.
• Relevant electrical or mechanical training, or a technical degree.
• Experience with CMMS platforms such as FIIX, SAP, or IBM Maximo would be an advantage.

What you will get in return:

● 70% off HelloFresh or Green Chef boxes
● Company pension scheme
● Gym membership
● Bupa private medical insurance (including dental & family cover options)
● Mental health first aiders and an employee assistance programme
● Dog friendly office! (London site only)
● Nursery support scheme
● Cycle to work scheme
● Group Life Assurance

Location: Spondon, Derby, DE21 7HW

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Working schedule: Monday to Friday, 42 hour working week

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

Job Title: Multi Skilled Maintenance Engineer

Location: Smart parc, Spondon, Derby DE21 7HW

Shift: Suez Shift Pattern rotating days and nights, 0600-1800 and 1800-0600.

Let's Discuss What's On The Table For You:

• 70% off HelloFresh or Green Chef boxes 
• Free onsite parking (including ~90 EV spaces)
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Nursery support scheme (save up to 40% on your nursery fees)
• Earn up to £500 with our Referral Program
• Electric vehicle scheme
• Cycle to work scheme
• Group Life Assurance
• Company pension scheme
• Mental health first aiders and an employee assistance programme

Play a key part in supporting our Employee Resource Groups: FreshVets, Black Heritage Network, NEU Network (Neurodiversity), GET (Gender Equality Team) and FreshPride

About The Team:

As a Multi Skilled Engineer you will be the site Subject Matter Expert (SME) within the team, for all controls systems, maintenance engineering, sensors, PLCs, communication protocols, and automation for the site. You will work with the facilities and maintenance teams and colleagues to maintain and repair conveyance, automation and facilities equipment to support operations uptime and improve reliability of our systems. 

What You Will Be Doing:

• Work in a hands-on manner to actively monitor, fault find and repair systems in order to provide a high level of equipment availability to internal customers.
• Perform preventive maintenance and routine inspections on assigned automation, robotics and control panels. 
• Perform troubleshooting of assigned out of service equipment and correct issues, act as an escalation point for lower level technicians, and escalate to leadership and/or vendors as needed for additional troubleshooting.
• Document all work in the computerized maintenance management system (CMMS) and ticketing systems as appropriate.
• Mentor all maintenance personnel in developing appropriate skill sets and knowledge of equipment specializing in automation, controls and robotics.
• Lead root cause analysis of major downtime events.
• Act as a network resource for technical issues and lead network-wide root cause analysis.
• Develop maintenance personnel knowledge on intermediate to advanced automation, controls and robotics.
• Partner with engineering on commissioning of new controls systems.
• Audit vendor work to provide feedback to leadership on quality of work and SLA performance.
• Write and/or modify PMs to standardize across the network and increase effectiveness.

Who You Are:

• Qualified or Solid practical understanding in Mechatronics, Electrical & Electronic, Mechanical, or Manufacturing Engineering
• Experienced in Automation, Mechanical, or Maintenance Engineering, ideally within a manufacturing or production environment such as FMCG.
• Proficient in PLC-controlled systems and automated processes, including programming, troubleshooting, repair, and maintenance of PLCs, HMIs, VFDs, and related control systems.
• Comfortable interpreting technical manuals, engineering drawings, and schematics to support diagnostics and solutions.
• Skilled in both reactive and preventative maintenance, with a track record of handling second-line escalations and completing CMMS (Computerized Maintenance Management System) tasks.
• Adept in material handling systems, with exposure to flow analysis, capacity visualization, and process monitoring.
• A confident communicator and mentor, capable of coaching junior engineers and stepping in as proxy for senior automation engineers when required.
• Experienced in leading Root Cause Analysis, supporting CI (Continuous Improvement) initiatives, and familiar with DIQ and WMS systems.

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

Job Title: Automation Engineer

Location: Smart parc, Spondon, Derby DE21 7HW

Shift: Suez Shift Pattern rotating days and nights, 0600-1800 and 1800-0600.

Let's Discuss What's On The Table For You:

• 70% off HelloFresh or Green Chef boxes 
• Free onsite parking (including ~90 EV spaces)
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Nursery support scheme (save up to 40% on your nursery fees)
• Earn up to £500 with our Referral Program
• Electric vehicle scheme
• Cycle to work scheme
• Group Life Assurance
• Company pension scheme
• Mental health first aiders and an employee assistance programme

Play a key part in supporting our Employee Resource Groups: FreshVets, Black Heritage Network, NEU Network (Neurodiversity), GET (Gender Equality Team) and FreshPride

About The Team:

As an Automation Engineer you will be the site Subject Matter Expert (SME) within the team, for all controls systems, maintenance engineering, sensors, PLCs, communication protocols, and automation for the site. You will work with the facilities and maintenance teams and colleagues to maintain and repair conveyance, automation and facilities equipment to support operations uptime and improve reliability of our systems. 

What You Will Be Doing:

• Work in a hands-on manner to actively monitor, fault find and repair systems in order to provide a high level of equipment availability to internal customers.
• Perform preventive maintenance and routine inspections on assigned automation, robotics and control panels. 
• Perform troubleshooting of assigned out of service equipment and correct issues, act as an escalation point for lower level technicians, and escalate to leadership and/or vendors as needed for additional troubleshooting.
• Document all work in the computerized maintenance management system (CMMS) and ticketing systems as appropriate.
• Mentor all maintenance personnel in developing appropriate skill sets and knowledge of equipment specializing in automation, controls and robotics.
• Lead root cause analysis of major downtime events.
• Act as a network resource for technical issues and lead network-wide root cause analysis.
• Develop maintenance personnel knowledge on intermediate to advanced automation, controls and robotics.
• Partner with engineering on commissioning of new controls systems.
• Audit vendor work to provide feedback to leadership on quality of work and SLA performance.
• Write and/or modify PMs to standardize across the network and increase effectiveness.

Who You Are:

• Qualified or Solid practical understanding in Mechatronics, Electrical & Electronic, Mechanical, or Manufacturing Engineering
• Experienced in Automation, Mechanical, or Maintenance Engineering, ideally within a manufacturing or production environment such as FMCG.
• Proficient in PLC-controlled systems and automated processes, including programming, troubleshooting, repair, and maintenance of PLCs, HMIs, VFDs, and related control systems.
• Comfortable interpreting technical manuals, engineering drawings, and schematics to support diagnostics and solutions.
• Skilled in both reactive and preventative maintenance, with a track record of handling second-line escalations and completing CMMS (Computerized Maintenance Management System) tasks.
• Adept in material handling systems, with exposure to flow analysis, capacity visualization, and process monitoring.
• A confident communicator and mentor, capable of coaching junior engineers and stepping in as proxy for senior automation engineers when required.
• Experienced in leading Root Cause Analysis, supporting CI (Continuous Improvement) initiatives, and familiar with DIQ and WMS systems.

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

Job Title: Multi Skilled Engineer

Location: Smart parc, Spondon, Derby DE21 7HW

Shift: Suez Shift Pattern rotating days and nights, 0600-1800 and 1800-0600.

Let's Discuss What's On The Table For You:

• 70% off HelloFresh or Green Chef boxes 
• Free onsite parking (including ~90 EV spaces)
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Nursery support scheme (save up to 40% on your nursery fees)
• Earn up to £500 with our Referral Program
• Electric vehicle scheme
• Cycle to work scheme
• Group Life Assurance
• Company pension scheme
• Mental health first aiders and an employee assistance programme

Play a key part in supporting our Employee Resource Groups: FreshVets, Black Heritage Network, NEU Network (Neurodiversity), GET (Gender Equality Team) and FreshPride

About The Team:

As a Multi Skilled Engineer you will be the site Subject Matter Expert (SME) within the team, for all controls systems, maintenance engineering, sensors, PLCs, communication protocols, and automation for the site. You will work with the facilities and maintenance teams and colleagues to maintain and repair conveyance, automation and facilities equipment to support operations uptime and improve reliability of our systems. 

What You Will Be Doing:

• Work in a hands-on manner to actively monitor, fault find and repair systems in order to provide a high level of equipment availability to internal customers.
• Perform preventive maintenance and routine inspections on assigned automation, robotics and control panels. 
• Perform troubleshooting of assigned out of service equipment and correct issues, act as an escalation point for lower level technicians, and escalate to leadership and/or vendors as needed for additional troubleshooting.
• Document all work in the computerized maintenance management system (CMMS) and ticketing systems as appropriate.
• Mentor all maintenance personnel in developing appropriate skill sets and knowledge of equipment specializing in automation, controls and robotics.
• Lead root cause analysis of major downtime events.
• Act as a network resource for technical issues and lead network-wide root cause analysis.
• Develop maintenance personnel knowledge on intermediate to advanced automation, controls and robotics.
• Partner with engineering on commissioning of new controls systems.
• Audit vendor work to provide feedback to leadership on quality of work and SLA performance.
• Write and/or modify PMs to standardize across the network and increase effectiveness.

Who You Are:

• Qualified or Solid practical understanding in Mechatronics, Electrical & Electronic, Mechanical, or Manufacturing Engineering
• Experienced in Automation, Mechanical, or Maintenance Engineering, ideally within a manufacturing or production environment such as FMCG.
• Proficient in PLC-controlled systems and automated processes, including programming, troubleshooting, repair, and maintenance of PLCs, HMIs, VFDs, and related control systems.
• Comfortable interpreting technical manuals, engineering drawings, and schematics to support diagnostics and solutions.
• Skilled in both reactive and preventative maintenance, with a track record of handling second-line escalations and completing CMMS (Computerized Maintenance Management System) tasks.
• Adept in material handling systems, with exposure to flow analysis, capacity visualization, and process monitoring.
• A confident communicator and mentor, capable of coaching junior engineers and stepping in as proxy for senior automation engineers when required.
• Experienced in leading Root Cause Analysis, supporting CI (Continuous Improvement) initiatives, and familiar with DIQ and WMS systems.

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

Location: Home Based - with weekly travel to one of our three sites in Basingstoke (primary destination), Bristol (primary destination) and Banbury

About The Team:

The HelloFresh Delivery Network (HFDN) is a critical part of our UK growth strategy, improving customer experience while reducing cost to serve. As we expand the network, we are looking for a Regional Manager for the West, responsible for the performance, stability, and startup/scale-up of three delivery sites, including one small satellite location.This role sits at the heart of execution. You will own day to day regional performance across safety, service, and cost, while also playing a key role in expanding capability, embedding standards, and preparing sites for growth. The role requires a strong grounding in B2C home delivery operations, confidence managing multiple locations, and the ability to translate plans into consistent on-the-ground execution.

What You Will Be Doing:

• Own end-to-end performance across three HFDN sites in the West, ensuring consistent standards despite differences in scale and maturity
• Act as the senior operational lead for the region, accountable for service, cost,  safety, DSPs.
• Stabilise and scale new and smaller sites, ensuring they are operationally sound and aligned to HFDN ways of working
• Oversee final mile delivery operations, from box handover and van loading through to route execution
• Drive delivery accuracy, service reliability, and customer experience across all sites
• Work closely with planning and central teams to ensure routes are executable and efficiently delivered on the ground
• Work closely with central Logistics and HFDN development teams to embed new processes, tools, and standards
• Identify operational risks and improvement opportunities, using data to drive decisions
• Support future site launches and expansion activity in the region, acting as a key operational input
• Ensure high standards of health and safety and compliance across all sites
• Oversee cost control, invoice approval, and regional budget adherence
• Handle escalations relating to customer complaints, insurance claims, and delivery incidents

Who You Are:

• Proven experience leading multi-site logistics or home delivery operations, ideally within B2C, FMCG, or last-mile environments
• Comfortable owning regional performance rather than a single site
• Strong people leader with experience managing Drivers and site teams
• Confident operating in fast-changing environments, including new site launches or expansion phases
• Solid understanding of fleet operations, driver models, and final mile delivery challenges
• Data-driven, with the ability to balance cost, service, and safety
• Experienced in health and safety, incident management, and operational risk
• A demonstrable track record of reducing errors and improving operational performance at scale

What you will get in return:

• 70% off HelloFresh or Green Chef boxes
• Company pension scheme
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Mental health first aiders and an employee assistance programme
• Nursery support scheme
• Cycle to work scheme
• Group Life Assurance

Shifts: 6am to 3pm, Saturday to Wednesday, flexibility required

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Location: Home Based - with daily travel to one of our three sites in Basingstoke (primary destination), Bristol (primary destination) and Banbury

About The Team:

The HelloFresh Delivery Network (HFDN) is a critical part of our UK growth strategy, improving customer experience while reducing cost to serve. As we expand the network, we are looking for a Regional Manager for the West, responsible for the performance, stability, and startup/scale-up of three delivery sites, including one small satellite location.This role sits at the heart of execution. You will own day to day regional performance across safety, service, and cost, while also playing a key role in expanding capability, embedding standards, and preparing sites for growth. The role requires a strong grounding in B2C home delivery operations, confidence managing multiple locations, and the ability to translate plans into consistent on-the-ground execution.

What You Will Be Doing:

• Own end-to-end performance across three HFDN sites in the West, ensuring consistent standards despite differences in scale and maturity
• Act as the senior operational lead for the region, accountable for service, cost,  safety, DSPs.
• Stabilise and scale new and smaller sites, ensuring they are operationally sound and aligned to HFDN ways of working
• Oversee final mile delivery operations, from box handover and van loading through to route execution
• Drive delivery accuracy, service reliability, and customer experience across all sites
• Work closely with planning and central teams to ensure routes are executable and efficiently delivered on the ground
• Work closely with central Logistics and HFDN development teams to embed new processes, tools, and standards
• Identify operational risks and improvement opportunities, using data to drive decisions
• Support future site launches and expansion activity in the region, acting as a key operational input
• Ensure high standards of health and safety and compliance across all sites
• Oversee cost control, invoice approval, and regional budget adherence
• Handle escalations relating to customer complaints, insurance claims, and delivery incidents

Who You Are:

• Proven experience leading multi-site logistics or home delivery operations, ideally within B2C, FMCG, or last-mile environments
• Comfortable owning regional performance rather than a single site
• Strong people leader with experience managing Drivers and site teams
• Confident operating in fast-changing environments, including new site launches or expansion phases
• Solid understanding of fleet operations, driver models, and final mile delivery challenges
• Data-driven, with the ability to balance cost, service, and safety
• Experienced in health and safety, incident management, and operational risk
• A demonstrable track record of reducing errors and improving operational performance at scale

What you will get in return:

• 70% off HelloFresh or Green Chef boxes
• Company pension scheme
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Mental health first aiders and an employee assistance programme
• Dog friendly office! (London site only)
• Nursery support scheme
• Cycle to work scheme
• Group Life Assurance

Shifts: 6am to 3pm, Saturday to Wednesday, flexibility required

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

If you are currently a HelloFresh employee, please make sure you have discussed your application with your Line Manager.

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Location: Home Based - with weekly travel to one of our three sites in Basingstoke (primary destination), Bristol (primary destination) and Banbury

About The Team:

The HelloFresh Delivery Network (HFDN) is a critical part of our UK growth strategy, improving customer experience while reducing cost to serve. As we expand the network, we are looking for a Regional Manager for the West, responsible for the performance, stability, and startup/scale-up of three delivery sites, including one small satellite location.This role sits at the heart of execution. You will own day to day regional performance across safety, service, and cost, while also playing a key role in expanding capability, embedding standards, and preparing sites for growth. The role requires a strong grounding in B2C home delivery operations, confidence managing multiple locations, and the ability to translate plans into consistent on-the-ground execution.

What You Will Be Doing:

• Own end-to-end performance across three HFDN sites in the West, ensuring consistent standards despite differences in scale and maturity
• Act as the senior operational lead for the region, accountable for service, cost,  safety, DSPs.
• Stabilise and scale new and smaller sites, ensuring they are operationally sound and aligned to HFDN ways of working
• Oversee final mile delivery operations, from box handover and van loading through to route execution
• Drive delivery accuracy, service reliability, and customer experience across all sites
• Work closely with planning and central teams to ensure routes are executable and efficiently delivered on the ground
• Work closely with central Logistics and HFDN development teams to embed new processes, tools, and standards
• Identify operational risks and improvement opportunities, using data to drive decisions
• Support future site launches and expansion activity in the region, acting as a key operational input
• Ensure high standards of health and safety and compliance across all sites
• Oversee cost control, invoice approval, and regional budget adherence
• Handle escalations relating to customer complaints, insurance claims, and delivery incidents

Who You Are:

• Proven experience leading multi-site logistics or home delivery operations, ideally within B2C, FMCG, or last-mile environments
• Comfortable owning regional performance rather than a single site
• Strong people leader with experience managing Drivers and site teams
• Confident operating in fast-changing environments, including new site launches or expansion phases
• Solid understanding of fleet operations, driver models, and final mile delivery challenges
• Data-driven, with the ability to balance cost, service, and safety
• Experienced in health and safety, incident management, and operational risk
• A demonstrable track record of reducing errors and improving operational performance at scale

What you will get in return:

• 70% off HelloFresh or Green Chef boxes
• Company pension scheme
• Gym membership
• Bupa private medical insurance (including dental & family cover options)
• Mental health first aiders and an employee assistance programme
• Nursery support scheme
• Cycle to work scheme
• Group Life Assurance

Shifts: 6am to 3pm, Saturday to Wednesday, flexibility required

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks.

You are required to cooperate with HelloFresh in all health and safety matters. You are responsible for ensuring you take reasonable care of your own health, and safety as well as others who may be affected by the work activities you undertake. You must report incidents immediately and actively raise health and safety-related concerns to your Line Manager. As part of our commitment to maintaining a safe and secure environment, we will process Disclosure and Barring Service (DBS) checks to the successful individual. Failure to disclose relevant information at application or throughout the process could affect your employment with the company. 

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

About The Team:

We’re looking for a Senior Demand Planning Analyst who is as comfortable writing SQL as they are explaining a forecast miss to a Procurement Director. This is a hybrid role: part data engineer, part forecaster, part cross-functional operator.

You’ll own the demand signal that drives every operational decision at HelloFresh, from how much food we buy to how many staff we schedule and how many trucks we book. Your forecasts directly determine food waste, labour costs, and customer experience for millions of meals across Europe.

Our Demand Planning team is transitioning from a legacy operating model to a unified, automated, data-driven global function. You will bridge that gap — building the next-generation forecasting capabilities while keeping daily supply chain execution accurate and agile.

What You’ll Do

Build & Automate Forecasting Systems

• Write and maintain SQL queries daily to extract, validate, and transform demand data across cloud data platforms (e.g., Databricks, BigQuery, Snowflake).
• Develop and refine forecasting models in Python, applying statistical and machine learning techniques — from simple trend and seasonality models through to more advanced approaches as the function matures.
• Design dashboards and automated reporting using visualisation tools (e.g., Tableau, Power BI) that give stakeholders self-service access to demand insights.
• Work alongside forecast engineers to architect scalable pipelines, ensuring local market nuances are handled without breaking the unified codebase.
• Build “What-If” scenario simulations (e.g., “What if we run an aggressive promo in a key European market next week?”) to stress-test operational capacity and quantify supply chain risk.

Own the Demand Plan

• Generate and validate daily and weekly demand plans for European markets. You are the guardian of the Decision-Time forecast — the plan must be accurate at the exact moment Procurement and Production need to act.
• Monitor trends, seasonality, and promotional impacts. Proactively flag when the plan needs adjusting and communicate changes before they surprise the supply chain.
• Implement data validation and QA checks to ensure forecast reliability, with alerting for anomalies.

Drive Cross-Functional Alignment (S&OP)

• Drive cross-functional alignment and play a key role in the weekly S&OP planning cycle with Market Leadership, Logistics, Production, and Procurement — ensuring the forecast is shaped by stakeholder inputs and shifting the conversation from error reporting to risk management and strategic alignment.
• Partner with Marketing to ensure growth campaigns and promotions are reflected in the demand view before they hit the supply chain.
• When deviations occur, go beyond surface metrics: diagnose root causes, quantify impact, and deliver actionable insights that prevent recurrence.

What We Need

Required Technical Skills

• SQL: Fluent. You write complex queries daily — joins, window functions, CTEs — and are comfortable working in cloud data platforms (e.g., Databricks, BigQuery, Snowflake).
• Python: Good working knowledge. You can write and maintain scripts for data manipulation, forecasting, and analysis. You don’t need to be a software engineer, but you’re confident using Python to solve analytical problems.
• Visualisation: Experience building dashboards in tools such as Tableau or Power BI to make data accessible to non-technical stakeholders.
• Excel/Google Sheets: Advanced. Still essential for ad-hoc analysis and stakeholder communication, but not your primary tool.

Required Domain Experience

• 4+ years in Demand Planning, Supply Planning, or Supply Chain Analytics. E-commerce, food retail, or FMCG experience is strongly preferred — perishable/short shelf-life experience is a significant plus.
• Strong grasp of forecasting techniques: you understand bias, accuracy metrics (MAPE, WMAPE), trend decomposition, and how to evaluate model performance holistically.
• Experience forecasting in environments with limited historical data (newer markets, product launches) using proxy data and trend smoothing.
• Proven ability to manage demand and supply risks: proposing mitigations (buffers, caps, swaps) and communicating complex trade-offs to senior stakeholders.
• Comfortable with project tools like JIRA/Confluence for managing backlogs and improvement roadmaps.
• Strong communication skills: you can present forecast insights, explain variance drivers, and articulate trade-offs clearly to both technical and non-technical audiences, ensuring alignment across functions.

What you will get in return:

● 70% off HelloFresh or Green Chef boxes
● Company pension scheme
● Gym membership
● Bupa private medical insurance (including dental & family cover options)
● Electric vehicle scheme
● Mental health first aiders and an employee assistance programme
● Dog friendly office! (London site only)
● Nursery support scheme
● Cycle to work scheme
● Group Life Assurance

Location: The HelloFresh Farm, 60 Worship Street, EC2A 2EZ, London or any other international HelloFresh market

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Hybrid Working Policy
We offer a hybrid working policy for eligible roles, allowing flexibility to work from home and in the office. For more details on eligibility and how this applies to the role you're applying for, please consult with our recruiter.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks. 

About The Team:

At HelloFresh, we are changing the way people eat forever. We are looking for a Senior Demand Planner to join our Central Planning Team, driving strategic forecasting and technical innovation across the UK and International markets while acting as the operational heartbeat of selected European markets. Seeking a data-savvy pro with strong SQL skills to unlock insights and drive smart decisions!

You will play a pivotal role in our Operations, moving from fragmented local forecasting to a unified, automated, and data-driven global model. You will also own the demand signal that drives every operational decision - from how much food we buy (Procurement) to how many staff we schedule (Production) and how many trucks we book (Logistics).

The Mission:

The Demand Planning team is transitioning from a legacy operating model into a Predictive Intelligence function. Our vision is to evolve from reactive demand estimation to active supply chain shaping, leveraging data to anticipate market shifts, mitigate risk, and optimize operational costs.

You will bridge the gap between legacy operations and predictive intelligence. This role has a critical dual objective:

1. Strategic Architecture & Innovation: Driving the innovation required to architect the standardized forecasting tools, demand simulation frameworks, and future-state processes that will unlock scalable growth across International markets.
2. Operational Execution & Continuity: Ensuring flawless operational continuity for Ireland forecasting, protecting service levels and optimizing costs during this transition.

Ultimately, you will ensure that while we build the next generation of automated planning pipelines, our daily supply chain execution remains agile, accurate, and highly efficient.

What You Will Be Doing:

Strategic Improvement

• Drive Standardization: Establish a unified, model-driven demand planning architecture. You will manage the planning process to strictly limit manual overrides, ensure real-time communication with key stakeholders and proactively take actions to correct the forecast.
• Automated Ecosystem Transition: Drive the shift toward an automated pipeline. Work alongside forecast engineers to design robust solutions that support an efficient, scalable process, ensuring local nuances are handled without breaking the unified code base.
• Scenario Modeling & Innovation: Work with Data Science to refine our Confidence Range Forecasts and Scenario Simulations. Build "What-If" scenarios (e.g., “What if we run an aggressive promo in Ireland next week?”) to stress-test operational capacity and mitigate supply chain risk.

Cross-Functional Stakeholder Management (S&OP)

• Lead the S&OP Rhythm: Facilitate the weekly planning cycle with local stakeholders such as Market leadership, Logistics, Production and Procurement. You will shift the focus from simple error reporting to comprehensive risk management and strategic alignment.
• Commercial & Marketing Alignment: Partner with Marketing to align on customer conversions and retention. You will ensure that growth campaigns are accurately reflected in the Expected Demand view before they hit the supply chain.
• Deep Dive Diagnostics: When deviations occur, you will move beyond surface-level metrics. Your role is to explain the key drivers of the variance to provide actionable insights that prevent recurrence.

Operational Forecasting & Plan Ownership

• Drive the Transition to an Automated Ecosystem: Drive the shift toward an automated, robust ecosystem (using tools like Python, Databricks, and Streamlit as examples). You will not just use these tools; you will work alongside forecast engineers to design robust solutions that support an efficient, scalable process, ensuring local nuances are handled without breaking the unified code base. 
• Own the Number: Generate and validate daily and weekly demand plans for Ireland. You are the guardian of the Decision-Time forecast, ensuring the plan is accurate at the exact moment Procurement and Production need to act, without relying on rigid timelines but rather on operational readiness.
• Manage Trends & Operational Agility: Monitor changes in trends and the need for quick operational adaptations. You will incorporate performance metrics, not only to track stability but to implement stakeholder discipline, ensuring that changes are communicated promptly and the organization adapts efficiently.

Who You Are:

You are a hybrid: part analyst and planner, part diplomat, and part strategic change agent. You know a demand plan is useless if it simply reports numbers without driving action. You ensure every plan reconciles conflicting cross-functional needs, championing structural transformation through deep insights and a proactive understanding of error and risk.

Must-Haves:

• Experience: 4+ years in Demand Planning, Supply Planning, or Data Analytics, preferably in e-commerce, food retail, or FMCG (short shelf-life/perishable experience is a massive plus).
• Tech Stack: You are ready to leave spreadsheets behind. Proficiency in SQL is required. Experience with Python (pandas, forecasting libraries) and Visualization tools (Tableau/Streamlit) is strongly preferred as we transition to our automated pipelines. 
• Analytical Rigor: You possess strong analytical skills and a problem-solving, forward-looking mindset. You understand how to evaluate performance holistically and are proficient in forecasting techniques.
• Young Market Mindset: You are comfortable with ambiguity. You know how to forecast in environments with limited historical data (like our newer markets) by using proxy data and trend smoothing.
• Project Management & Delivery: You can plan and sequence initiatives across markets, handling ambiguity and frequent reprioritisation. You have a track record of prioritising and landing a roadmap of improvements.
• Risk & Change Management: You proactively anticipate demand and supply risks. You are experienced in proposing mitigations (buffers, caps, swaps) and communicating complex trade-offs to senior stakeholders to protect service and cost.
• Project & Data Tools: Advanced Excel/Google Sheets skills are essential. You are comfortable using JIRA/Confluence (or similar) for managing backlogs and requirements.
• Quality & Monitoring: Experience with data validation/QA frameworks, alerting systems, and SLA tracking to ensure forecast reliability.

Soft Skills:

• Influence: You can hold your ground with Senior Stakeholders (Head of Operations, Procurement Directors) when challenging their numbers or explaining a forecast miss.
• Clarity: You can translate complex statistical concepts (e.g., "algorithm bias") into business impact (e.g., "we need to buy 10% more chicken").
• Stakeholder Leadership: You possess strong stakeholder management skills, influencing across Marketing, Procurement, Finance, and Tech. You ensure alignment across diverse functions.

What you will get in return:

● 70% off HelloFresh or Green Chef boxes
● Company pension scheme
● Gym membership
● Bupa private medical insurance (including dental & family cover options)
● Electric vehicle scheme
● Mental health first aiders and an employee assistance programme
● Dog friendly office! (London site only)
● Nursery support scheme
● Cycle to work scheme
● Group Life Assurance

Location: The HelloFresh Farm, 60 Worship Street, EC2A 2EZ, London or any other international HelloFresh market

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Hybrid Working Policy
We offer a hybrid working policy for eligible roles, allowing flexibility to work from home and in the office. For more details on eligibility and how this applies to the role you're applying for, please consult with our recruiter.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks. 

At Ensono, our purpose is to be a relentless ally, disrupting the status quo and enabling our clients to Do Great Things. As a trusted technology adviser and managed services provider, we help clients navigate continuous change and embrace innovation.

We deliver world-class transformational services across hybrid cloud, infrastructure, mainframe, data, IdAM, and cloud-native solutions, simplifying complex business challenges and creating new pathways to success. Headquartered in the USA and backed by private equity, Ensono has a strong track record in the UK and Europe, with growth plans built on trusted partnerships and deep industry expertise.

About the role:

We’re looking for Site Reliability Engineering (SRE) to join our growing  team. We support a variety of data solutions that we’ve developed, and we are seeking individuals with data expertise to enhance our SRE team.
This role offers excellent career progression, as our division is in a state of growth—expanding both in-team size and client base. There are numerous opportunities to advance your career with us.

Key responsibilities:
• Act as a technical escalation point for unresolved data platform issues in the SRE Pod/s;
• Monitor, maintain, and troubleshoot databases/data warehouses and related infrastructure;
• Collaborate with the data engineering team to ensure efficient data flow and transformation;
• Develop and maintain accurate technical documentation in the form of operational runbooks;
• Perform standard pre-approved changes within the scope of our client’s Change Management Process (i.e. new users, etc.);
• Use Ensono’s helpdesk and work tracking systems to maintain logs of all support requests and incidents, and improve these processes, both technically and through stakeholder management.
• Participate in the process for, and proactively mitigate risks in a Security management process (Vulnerabilities in Code, Infrastructure, Dependencies) aligned to both Ensono’s and our Clients compliance objectives;
• Engaging with suppliers and 3rd parties for support, requests and opportunities, managing the relationship our clients get the best value for their service

What you will being to Ensono:
• IAC tooling (Terraform preferably, or ARM/bicep and CloudFront) Core CI/CD Tooling (Azure DevOps, GitHub Actions or Gitlab)
• Monitoring Tooling (DataDog, Splunk, NewRelic, Azure Monitor, AWS CloudWatch)
• Demonstrable experience in multiple core technology (Dotnet, Java, AI/Data Engineering, Golang)
• Troubleshooting issues and identifying systemic failings indicated by incidents/failures Implementing fixes and features
• Proposing solutions for reducing toil
• Implementing and refining automation for incident and service request resolution
• Providing leadership in the Incident resolution process, including creating and maintaining documentation, and leading Post-mortem analysis and mitigation planning.
• Designing and Reinforcing Service Requests and Change Management (both technically and through stakeholder management) processes, and improving existing processes.
• Develop and enhance the process for, and Proactively mitigate risks through Security management (Vulnerabilities in Code, Infrastructure, Dependencies)
• Lead discussion for multiple clients in client-facing meetings around the SRE process, identifying areas for increasing SRE footprint and identifying opportunities for small works and consultancy.
• Engaging with: Suppliers and 3rd parties for support, requests and opportunities
• Cross-sale and cross-pollination opportunities within the Ensono organisation
• Cloud provider (AWS, Azure, GCP) ‘DevOps Engineer’-level certification and CKAD certification highly beneficial, or required during probationary period.

What we can offer you:

We are a people-first business, which means people are at the heart of everything we do here. We offer our associates a safe environment where learning, knowledge sharing, and open communication is encouraged. Whether at one of the internal events, such as socials, competency meet-ups, hackathons or as part of one or more of our global Community Groups, such as Beautiful Brains (for the neurodiverse and curious), HERO (helping to education regarding orientation), E-Vets (Ensono veteran community) and many more we have strived to build a business where everyone feels welcomed, included, and valued

Our Benefits include:
• Competitive base with uncapped commission
• The ability to work from a range of flexible locations
• Prestigious sales and broader team recognition with Annual Presidents Club
• Starting with 27 days annual leave (plus bank holidays) – accruing to 30
• 1/2 day leave on your birthday
• Sabbatical options at 5 & 10 years' service
• 5 days study leave
• Generous company pension
• Private healthcare for you and your family
• Payroll giving
• Enhanced paternity and maternity leave
• Equity appreciation program incentive plan
• Life and income protection
• Additional perks such as discounted gym memberships, cycle scheme, EAP and more!

If this all sounds great, we’d love to hear from you!

So, what's the role all about?

Here at NICE Public Safety, we provide state of the art solutions for the Public Safety & Justice market, providing software as a service for multi-media evidence management and Emergency Contact Centres to a worldwide customer base.

We are currently expanding our Cloud Platform Engineering team to ensure we continue to offer exemplary service to our customers. This is a very hands-on role. You will be involved in ensuring our cloud platforms are observable, measurable, reliable, scalable, and maintainable. It’s likely that the successful candidate will have significant experience in a DevOps, SRE, Cloud Engineer, or Cloud Development role.

How will you make an impact? 

• Act as part of a team of SRE’s that act as the ‘gatekeepers’ of production and actively manage the work backlog and develop reliability improvements.
• Lead investigations into root cause outages, performance, and cost issues.
• Lead initiatives to develop the automation of low-value tasks balanced against project delivery demands.
• You will provide technical leadership and to wider Cloud Operations and Support teams along with providing oversight to the products and services they support.
• Collaborate with DevOps and engineering teams to establish and enforce SLOs, SLAs, and error budgets
• Develop and configure monitoring dashboards and alerts in tools like Grafana and Azure Monitor.
• Installation and configuration of Observability Platform including tools like Grafana, Prometheus, Azure Monitor, Open telemetry etc.
• Developing bicep modules for monitoring infrastructure and deploy it.
• Optimize system performance, cost, and security through regular reviews and tuning.

Do you have what it takes?

• Must have 6+ years of experience in Site Reliability Engineering
• Excellent technical, analytical and troubleshooting skills
• Experience and in-depth knowledge of databases and data handling (MS-SQL, Elasticsearch, YML, JSON, XML)
• Experience with Azure cloud
• Significant experience in programming or advanced scripting (Python, PowerShell, C# etc.)
• Experience with infrastructure/configuration as code and version control (ARM, BICEP, Git)
• Strong Experience managing monitoring, alerting and dashboarding platforms (Azure Monitor, Prometheus, Grafana, Elasticsearch)
• Demonstrable experience of supporting live cloud services and platforms
• Expert in developing queries for dashboards and alerting for microservices.
• Expertise in developing custom metrics for microservices
• Collaborate with DevOps and engineering teams to establish and enforce SLOs, SLAs, and error budgets.
• Production experience with Kubernetes and containerization (AKS)
• Exposure to Azure DevOps pipelines is desirable (CI/CD)
• Strong experience in infrastructure as a code, design and implementation strategies.
• Experience with AI (tools) to automate and accelerate is a plus.
• Efficient, effective, and respectful communication skills both with customers and within internal departments. Including,
  • Good listener, able to identify and validate assumptions.
  • Able to use effective questioning to confirm understanding of a customer problem and then provide help to solve it.
  • Methodical troubleshooting, technical skill and attention to detail used in diagnosing problems and reproducing issues in a local environment.
  • Multi-tasking and time-management to prioritise and switch between varied tasks.

• Significant experience in platform engineering, observability, and provisioning.
• Proven ability to develop and implement a strategic vision for platform services, observability, and provisioning.
• Strong understanding of cyber security principles, governance, and compliance frameworks.
• Strong understanding and experience of cloud platforms, containerisation, and microservices architecture.
• Broad background across information technology with the ability to communicate clearly with non-security technical SMEs at a comfortable level.
• Strong proficiency in technical scoping, architecture design, and integration of security tools and processes.
• Ability to translate business needs into scalable, user-centric cloud solutions.
• Excellent communication and collaboration skills, with a focus thought leadership and solution development.
• Experience in both operational and transformation roles or a clear working understanding of both perspectives.
• Knowledge of compliance with relevant frameworks, including ISO 27001, Cyber Essentials + or FEDRAMP

Tooling

• Kubernetes (Ideally AKS)
• Azure Devops Pipelines
• Elasticsearch and Cloud Observability Stacks
• IAC (Bicep/Terraform)
• Powershell / C#

Beneficial Certifications

• AZ 104
• AZ 305
• AZ 500
• AZ 700
• CKA

Requisition ID: 10820
Reporting into: Director, Engineering, 
Role Type: Individual Contributor

#LI-Hybrid 

THE ROLE

Pure Storage is seeking a Strategic Accounts Account Executive to accelerate growth of the Portworx platform across Strategic Telco accounts in EMEA. You will own a small number of named Telco customers and prospects, build and execute multi year account plans, and drive platform adoption with a focus on business outcomes such as resilience, risk reduction, faster application delivery, and operational efficiency.

You will work closely with cross functional teams across Pure and Portworx, including Systems Engineering, Customer Experience, Marketing, Partner teams, Product, and field leadership. This is a high impact individual contributor role with a strong emphasis on strategic planning, disciplined execution, and customer intimacy.

What You’ll Do

• Own and grow a portfolio of named Strategic Telco accounts, delivering against annual and multi year revenue targets.
• Build and execute account plans that map buying centres, application priorities, Kubernetes roadmaps, and transformation programmes.
• Develop executive relationships across CIO, CTO, CISO, Head of Infrastructure, Platform Engineering, SRE, and Application leaders.
• Lead complex sales cycles from discovery through close, including security, risk, procurement, architecture review, and legal processes common in Telco.
• Position Portworx around measurable outcomes: application resilience, ransomware recovery, data protection, regulatory compliance, cloud portability, and modernisation at scale.
• Orchestrate account teams and partner ecosystems, including GSIs, cloud providers, and regional partners, to drive pipeline creation and deal execution.
• Run a rigorous, value based sales process tailored to cloud native software, with accurate forecasting and strong hygiene in Salesforce and forecasting tools.
• Partner with Customer Experience to expand adoption post sale, identify expansion triggers, and build customer advocacy within the Telco community.
• Stay ahead of competitive dynamics in Kubernetes data services, backup and recovery, and container storage, using insights to sharpen strategy and messaging.
• Represent Portworx in customer meetings and relevant industry events, with a field first mindset.

What You’ll Bring

• Proven enterprise software sales experience, with a track record of closing and expanding high value, multi stakeholder deals in large organisations.
• Demonstrable experience selling into Telco, with an understanding of procurement, governance, risk, and security requirements.
• Strong grasp of cloud native concepts and the Kubernetes ecosystem, plus the ability to credibly engage architects and platform teams.
• Experience selling to both technical and executive stakeholders, translating technical capabilities into business value and risk outcomes.
• Disciplined pipeline generation, qualification, deal management, and forecasting, with strong operational habits in SFDC.
• Comfort working in a matrixed environment, influencing cross functional teams without direct authority.
• Strong communication and programme management skills, with clear account planning and stakeholder alignment.
• A customer first mindset and a bias for action, with resilience and curiosity.

Everpure’s (formerly Pure Storage) Cloud and Data Services team, is at the centre of our cloud native strategy. We help enterprises run, protect, and scale stateful applications on Kubernetes across hybrid and multi cloud environments. If you are excited by complex enterprise selling, technical value creation, and building long term executive relationships in UK-based Enterprise customers, this role is for you.

THE ROLE

Everpure is seeking a Cloud and Data Services Account Executive to accelerate growth of the Portworx and Everpure Cloud across UK-based Enterprise accounts in EMEA. You will own a number of named customers and prospects, build and execute multi year account plans, and drive platform adoption with a focus on business outcomes such as resilience, risk reduction, faster application delivery, and operational efficiency.

You will work closely with cross functional teams across Everpure and the Cloud and Data Services team, including Systems Engineering, Customer Experience, Marketing, Partner teams, Product, and field leadership. This is a high impact individual contributor role with a strong emphasis on strategic planning, disciplined execution, and customer intimacy.

WHAT YOU'LL DO

• Own and grow a portfolio of enterprise and commercial accounts, delivering against annual and multi year revenue targets.
• Build and execute account plans that map buying centres, application priorities, Kubernetes roadmaps, and transformation programmes.
• Develop executive relationships across CIO, CTO, CISO, Head of Infrastructure, Platform Engineering, SRE, and Application leaders.
• Lead complex sales cycles from discovery through close, including security, risk, procurement, architecture review, and legal processes common in Manufacturing and Automotive.
• Position Portworx around measurable outcomes: application resilience, ransomware recovery, data protection, regulatory compliance, cloud portability, and modernisation at scale.
• Orchestrate account teams and partner ecosystems, including GSIs, cloud providers, and regional partners, to drive pipeline creation and deal execution.
• Run a rigorous, value based sales process tailored to cloud native software, with accurate forecasting and strong hygiene in Salesforce and forecasting tools.
• Partner with Customer Experience to expand adoption post sale, identify expansion triggers, and build customer advocacy within the Manufacturing and Automotive community.
• Stay ahead of competitive dynamics in Kubernetes data services, backup and recovery, and container storage, using insights to sharpen strategy and messaging.
• Represent Portworx in customer meetings and relevant industry events, with a field first mindset.

WHAT YOU BRING

• Proven enterprise software sales experience, with a track record of closing and expanding high value, multi stakeholder deals in large organisations.
• Demonstrable experience selling into enterprise accounts, with an understanding of procurement, governance, risk, and security requirements.
• Strong grasp of cloud native concepts and the Kubernetes ecosystem, plus the ability to credibly engage architects and platform teams.
• Experience selling to both technical and executive stakeholders, translating technical capabilities into business value and risk outcomes.
• Disciplined pipeline generation, qualification, deal management, and forecasting, with strong operational habits in SFDC.
• Comfort working in a matrixed environment, influencing cross functional teams without direct authority.
• Strong communication and programme management skills, with clear account planning and stakeholder alignment.
• A customer first mindset and a bias for action, with resilience and curiosity.

#LI-REMOTE, #LI-ONSITE

The Problems You'll Solve

At Carta, our employees set out on a mission to unlock the power of equity ownership for more people in more places. We believe that the problems we solve today unlock the opportunities of tomorrow. 

As a Senior Machine Learning Engineer II at Carta, you'll spend your time building agentic systems to power new products, automate complex document workflows, and accelerate Carta's business. You will also work closely with the SRE team to develop Carta's infrastructure around LLM integration and agentic processes. Example responsibilities will include:

• Develop agentic systems to classify, extract and review data from complex financial and legal documents.
• Develop agentic systems for document acquisition and management.
• Partner with product managers, engineers, designers, and business teams to incorporate agentic and LLM-powered products and user-flows.
• Own, coordinate, and solve complex, cross-functional problems that extend beyond the traditional boundaries of machine learning.

The Team You'll Work With

At Carta, our Machine Learning team is on a mission to power data products and automation through cutting-edge techniques. We work closely with Carta's core business units and product teams to develop LLM-powered and agentic systems for document intelligence, fund administration, legal tech, customer onboarding and more. This role is foundational to our team, where you'll work with one of the world's most valuable datasets and document repositories. Our systems directly enable revenue growth and operational efficiency for the company.

Our team consists of specialized Machine Learning scientists and engineers, collaborating with product analytics and data engineering experts. We foster a culture of partnership, working closely with teams across Carta to solve impactful problems. We strongly believe that being helpful accelerates results, and we support one another to achieve success at Carta.

The Impact You'll Have

You will own significant projects that directly align with the company's strategic initiatives in agentic systems, AI adoption and document intelligence. Your contributions will empower leaders across the organization to deliver innovative products, optimize operational efficiency, and make well-informed product decisions. Additionally, you will have the opportunity to develop foundational infrastructure for our team and establish best practices for integrating our agentic and LLM-powered systems into production environments. Your work will not only impact Carta's current machine learning capabilities but also pave the way for future engineers, enabling them to build upon your efforts seamlessly.

About You

Candidates must have a strong foundation in machine learning and software development, be proficient in Python, and have an analytical mindset. You have a strong bias towards simplicity, are excited by “zero to one” projects, and can efficiently communicate findings to leadership. Example traits that we value:

• 8+ years of industry experience solving complex data problems with descriptive and predictive statistical models
• Proficiency with AI-assisted software development, multi-agent development, skills & AI integration into development processes
• Experience with large language models (LLMs) and their applications in document intelligence
• Experience using LLMs and agentic frameworks such as Agno, Anthropic’s Agent SDK, Strands Agents SDK, A2A, LangChain or similar
• Experience with LLM observability and evals platforms such as Braintrust, Weights&Biases, LangFuse or similar
• Strong written and verbal communication skills
• A collaborative attitude and a helpful personality
• Experience building durable workflows in e.g. Temporal

The role

As a Cloud Site Reliability Engineer at Wayve, you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).

This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.

This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.

Key responsibilities

Reliability & Platform Ownership

• Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
• Define and operationalise SLOs, SLIs, and error budgets across platform services.
• Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
• Partner with ML, platform, and software teams to establish clear production readiness standards.
  
  

Incident Response & On-Call

• Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
• Lead incident triage, escalation, communications, and root cause analysis.
• Translate post-incident learning into durable architectural or automation improvements.
• Continuously reduce alert noise and recurring operational burden.
  
  

Observability & Operational Excellence

• Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
• Build dashboards that reflect real user-centric platform health (not just infrastructure metrics).
  Improve deployment safety through better change management, validation, and rollback mechanisms.
  
  

Automation & Tooling

• Build automation for cluster operations, training workflows, remediation, and scaling tasks.
• Implement self-healing patterns and resilient recovery workflows.
• Harden CI/CD and release processes to improve deployment safety and velocity.
• Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.

About you

In order to set you up for success as a Cloud Site Reliability Engineer at Wayve, we’re looking for the following skills and experience.

Essential skills

• Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
• Strong Kubernetes experience, including operating production clusters.
• Hands-on experience running production workloads in AWS, GCP, or Azure.
• Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
• Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
• Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
• Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
• Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
• Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.

Desirable skills

• Experience operating GPU-backed environments or large-scale ML infrastructure.
• Experience running model training or inference pipelines in production (MLOps).
• Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
• Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
• Experience as an early or founding SRE hire establishing processes from scratch.
• Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.

This is a full-time role based in our office in London (2 days a week in the office).  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

The role

This is a rare opportunity to be a founding Staff SRE shaping the reliability of large-scale AI systems and GPU compute infrastructure from the ground up.

As a Staff Cloud Site Reliability Engineer at Wayve, you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).

This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.

This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.

Key responsibilities

Reliability & Platform Ownership

• Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
• Define and operationalise SLOs, SLIs, and error budgets across platform services.
• Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
• Partner with ML, platform, and software teams to establish clear production readiness standards.
  
  

Incident Response & On-Call

• Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
• Lead incident triage, escalation, communications, and root cause analysis.
• Translate post-incident learning into durable architectural or automation improvements.
• Continuously reduce alert noise and recurring operational burden.
  
  

Observability & Operational Excellence

• Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
• Build dashboards that reflect real user-centric platform health (not just infrastructure metrics).
  Improve deployment safety through better change management, validation, and rollback mechanisms.
  
  

Automation & Tooling

• Build automation for cluster operations, training workflows, remediation, and scaling tasks.
• Implement self-healing patterns and resilient recovery workflows.
• Harden CI/CD and release processes to improve deployment safety and velocity.
• Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.

About you

In order to set you up for success as a Cloud Site Reliability Engineer at Wayve, we’re looking for the following skills and experience.

Essential skills

• Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
• Experience operating GPU-backed environments or large-scale ML infrastructure.
• Experience running model training or inference pipelines in production (MLOps).
• Strong Kubernetes experience, including operating production clusters.
• Hands-on experience running production workloads in AWS, GCP, or Azure.
• Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
• Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
• Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
• Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
• Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
• Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.

Desirable skills

• Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
• Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
• Experience as an early or founding SRE hire establishing processes from scratch.
• Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.

This is a full-time role based in our office in London (2 days a week in the office).  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

We are Datadog's in-house product experts. The technical solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. We share our technical and product expertise with customers through demos, presentations, technical evaluations, and ongoing support. Technical solutions is a growing global team that collaborates constantly to share knowledge and continuously advance our technical skillset.

The Logs family of products represents a strategic evolution in how organizations manage and analyze logs at scale while meeting stringent data residency, compliance, and cost requirements. The Product Solutions Architect (PSA) will work closely with Datadog customers, Logs Product team, and the CloudPrem product team to architect, implement best practices, and drive adoption of the log management suite.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Serve as the Product Expert on Logs, CloudPrem, and Observability Pipelines
• Offer guidance on architecture choices, data collection, and best practices to large Enterprise customers as they adopt these Datadog services across the organization at scale
• Design and validate hands-on, production-ready architectures spanning cloud infrastructure, Kubernetes platforms, and customer-managed environments
• Actively identify opportunities to simplify, optimize, and standardize deployment patterns, reducing operational complexity for customers through architectural guidance and best practices.
• Be a Trusted Advisor to Product Management by providing high quality feedback based on your field experience working closely with our Support, Partners, and Customers
• Capture repeat customer use cases and solutions and in turn publish Reference Architectures, automation patterns, and Implementation Guides for Datadog prospect and customer consumption
• Build world class training material, solutions briefs, blogs, and documentation to the wider Datadog field technical teams over the latest product features and capabilities
• Collaborate with other teams at Datadog including Marketing, Sales, Community, Documentation, and Evangelism to ensure the success of the Log Management product family
• Exercise the products you represent by building hands-on proof of concepts, small scale deployments  to validate solutions and reproduce customer environments
• Engage deeply with customers, feeling their operational pain points and driving solutions that measurably improve reliability, scalability, and day-to-day operations

Who You Are:

• Someone with strong hands-on experience with tools such as Kubernetes, including cluster architecture, networking, storage, and operational best practices.
• Someone with strong knowledge of cloud infrastructure fundamentals, including networking, compute, storage, and distributed system design.
• Someone familiar with Security, Governance, and Compliance requirements for industry verticals
• Someone who can dive deep into our Codebase, SDKs, and GitHub workflows to understand, debug, and influence product behavior
• Experience with languages like Python and/or Rust, and file formats such as JSON and YAML
• A self-starter, tech-savvy professional, who is comfortable working with bleeding edge technology and processes, even if it hasn’t been well defined
• A deep learner and a Subject Matter Expert today that has built advocacy and knowledge across multiple teams with the knowledge you possess 
• Fluent in understanding the observability market domain, competition, technological shifts, and customer needs
• Someone who values getting things done, taking ownership from problem definition through implementation and outcome
• Highly detail-oriented, especially when working on architectures, documentation, and customer-facing solutions
• A person who possesses exceptional listening and consultative skills, for both internal and external audiences
• Experienced working with customers in high pressure situations where the solution is sometimes not obvious - caring about customer pain and motivated to solve hard problems on their behalf
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train, or air up to 40% of the time 

Bonus Points:

• Successful track record with 5+ years experience working as an Architect or Consultant 
• Experience using Datadog and/or other observability tools in an SRE or DevOps capacity
• Have recent experience deploying solutions in production environments at scale
• Strong knowledge or experience with Splunk, Elastic, Opensearch, SumoLogic, Vector, Cribl, Quickwit

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

Datadog is committed to open source. It starts with our Agent, tracers, libraries, and SDKs all being open source. But it goes so much further. From open standards to open collaboration, it’s a core part of who we are and what we do. As part of the Open Source Program Office (OSPO), you will be focusing on building tools, documentation, policies, etc. that improve how our engineers interact with Open Source projects (our own and third-party projects), as well as representing Datadog in Open Source communities. 

What You’ll Do: 

• Build and maintain tools that ease building and releasing Open Source software at Datadog
• Build and maintain tools that ease ingesting Open Source software at Datadog
• Create developer facing documentation and training materials around contributing to open source and maintaining open source projects
• Interface with open source communities to understand problems and trends in the market
• Create tools to automatically analyze and report on Open Source repositories trends and statistics
• Interface with Datadog Open Source Partners candidates and recipients to select new projects for the program and ensure that the program stays useful
• Research and write content for the Datadog Open Source Hub
• Contribute to the product through feedback (bugs or product enhancements suggestions), documentation, or code

Who You Are: 

• Approximately 3+ years of experience as a software developer, SRE, or other practitioner.
• You are fluent in reading and writing one or more languages, e.g. Python, JavaScript, Java, Go, C#, Rust, and so on.
• You love building tools that make other engineers more productive.
• You have empathy, collaboration, and communication skills to cultivate strong relationships across various teams in the organization.
• Bonus: You are (or have been) an active member of an open source community.
• Bonus: You are familiar with different Open Source licenses and Contributor License Agreements 

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.  

Benefits and Growth: 

• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• Intradepartmental mentor and buddy program for in-house networking
• An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
• Access to Inclusion Talks, our Internal panel discussions
• Free, global mental health benefits for employees and dependents age 6+
• Competitive global benefits

 Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Remote

CHAOS Industries is redefining modern defense with omniscient systems purpose-built for today’s realities. Designed and built by top U.S. military veterans and Silicon Valley innovators, CHAOS Industries’ products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. In a world where technological threats move at unprecedented speed, CHAOS Industries delivers advanced sensing and detection solutions that give the ultimate advantage: time.

CHAOS Industries was founded in 2022 and has raised $1B in total funding from leading investors including 8VC, Accel, and NEA. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, and London. For more information, please visit www.chaosinc.com.

Role Overview:

Technical Operations Engineers sit at the intersection of technology and real-world mission environments. You’ll ensure CHAOS systems operate flawlessly in the field — integrating hardware and software, diagnosing complex system issues, and delivering rapid fixes and improvements.

This role is ideal for someone who thrives in dynamic, hands-on settings — comfortable with Linux terminals, network traces, and hardware wiring as much as Python scripts and dashboards. You’ll be embedded with customers, integrating CHAOS systems into existing infrastructure, and ensuring reliability under real-world conditions.

Responsibilities:

• Integrate CHAOS software, sensors, and RF devices with customer systems — both physically (networking, power, and hardware bring-up) and via software interfaces (data pipelines, APIs).
• Debug complex edge issues spanning hardware, software, and networking layers.
• Develop scripts, diagnostics, and automation tools to improve reliability and observability.
• Capture operational feedback and collaborate with internal engineering teams to drive product improvements.
• Document system configurations, troubleshooting steps, and lessons learned for both internal and customer audiences.
• Travel (typically up to 50%) to customer and test sites for deployments, troubleshooting, and mission support.

Minimum Requirements:

• Strong technical foundation with a degree in Engineering, Computer Science, Physics, or related field — or equivalent hands-on experience.
• Deep familiarity with Linux environments; comfortable with SSH, networking tools, and system-level debugging.
• Strong problem-solving instincts — able to work independently and under pressure in the field.
• Understanding of networking protocols, hardware interfaces, and distributed system concepts.
• Experience integrating or maintaining hardware or sensor systems.
• Proficiency in at least one scripting or programming language (Python, Bash, or similar).
• Willingness and enthusiasm for travel and on-site technical work.

Preferred Requirements:

• Experience in systems integration, field engineering, or technical operations for complex deployments.
• Background in defense, aerospace, or other mission-critical environments.
• Familiarity with telemetry, data integration, or IoT-style architectures.
• Understanding of RF systems, SDRs, or radar technologies (highly valued but not required).
• Experience with cloud and edge computing environments (Docker, Azure, AWS, etc.).
• Excellent communication and documentation skills — able to bridge technical and operational perspectives with clarity and composure.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 5% pension match, life insurance, Cycle to Work Scheme, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 200 employees and counting across 5 global offices

#LI-onsite

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices, including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-AM1

Joining Collibra’s Platform Infrastructure Engineering team

Collibra's Platform Infrastructure Engineering team is responsible for the essential cloud foundation underpinning all Collibra products, reporting directly to the Senior Manager, Platform Infrastructure Engineering. Your work is vital to evolving our multi-cloud platform infrastructure strategy. You will optimize our use of Kubernetes, IaC (Terraform/Helm), and Golang automation to ensure maximum operational efficiency and resilience for Collibra. We are a geographically diverse team guided by our value of Embracing and Driving Change, which translates into a team that never settles long for good enough, offering you a dynamic environment to advance your technical skills and make a tangible difference.

This is a remote role based in UK or Europe.

Staff Platform Engineers at Collibra are responsible for

• Lead the design and evolution of the cloud platform across AWS and GCP (Kubernetes, networking, and core infrastructure) in order to enable product teams to build, deploy, and operate services with speed, consistency, and minimal friction
• Build and standardize platform capabilities (CI/CD, observability, service templates, and golden paths) in order to reduce cognitive load and accelerate developer productivity across the organization
• Develop and operate shared data platform services (operators in Go, Kafka, Neo4j, and related infrastructure) in order to provide scalable, reliable, and self-service data capabilities for product and analytics teams
• Partner with product engineering, security, and SRE teams in order to drive adoption of platform best practices and ensure secure, compliant, and resilient architectures across AWS and GCP
• Mentor other engineers, champion technical excellence, and drive cloud cost optimization through automation.

You have

• Production experience managing infrastructure on a major cloud platform (AWS or GCP).
• Hands-on experience operating Kubernetes and service mesh technologies (preferably Istio).
• Strong understanding of cloud networking concepts (VPCs, routing, load balancing, WAFs, network policies).
• Proven experience with Infrastructure as Code (Terraform) and software development in Golang.
• Experience managing or supporting the underlying infrastructure for stateful applications (e.g., databases like GraphDB, kafka) on cloud platforms.
• Familiarity with cloud security principles (IAM, security groups).
• A bachelor’s degree or equivalent working experience.

You are

• Critical thinker who skillfully analyzes complex distributed systems, including intricate network flows.
• A proactive learner, curious about evolving technologies in cloud, container orchestration, and service mesh.
• Open-minded and approach problems from an assumption of positive intent and demonstrate emotional intelligence.
• Able to communicate complex technical concepts clearly to diverse audiences and identify opportunities for simplification and automation.
• Able to work with a high degree of care and independence.

Measures of Success

• Within your first month: you will Integrate with the team, understand our architecture, and make your first platform contribution.
• Within your third month: Build strong familiarity with the platform, team workflows, and shared services in order to begin contributing to well-defined platform improvements with guidance
• Within your sixth month: Independently deliver production-ready improvements to the internal developer platform and shared services in order to demonstrate ownership, sound technical judgment, and alignment with organizational standards

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices, including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

About the role:

We’re seeking a talented Senior Security Engineer with hands-on experience deploying, managing, and operating modern Vulnerability Management platforms. In this role, you’ll work alongside technical product managers and engineers across the company to maintain Samsara’s Vulnerability Management infrastructure and de-risk software vulnerabilities to better protect our customers.

We seek someone who is passionate about leveraging automation to enhance efficiency, is enthusiastic about working with infrastructure-as-code, and has a wealth of experience collaborating with teams to reduce software vulnerabilities. Your contributions will be critical to shaping our overall security and compliance strategy. At Samsara, we value working backwards from winning as an operating principle. Your ability to define success and work with cross-functional stakeholders by working backwards to reach that success is pivotal. 

You should apply if:

• You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.
• You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, and countless opportunities to experiment and master your craft in a hyper-growth environment.
• You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.
• You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-caliber team that will encourage you to do your best. 

In this role, you will: 

• Lead and own ongoing operation and maintenance of Samsara’s vulnerability management program, ensuring consistent execution of processes.
• Assist in managing vulnerability scanning tools and help refine detection capabilities to improve accuracy and reduce false positives.
• Work closely with the Vulnerability Technical Program Manager to generate and distribute monthly and quarterly compliance reports.
• Collaborate with engineering teams to track and support the remediation of identified vulnerabilities, providing guidance on best practices.
• Assist in analyzing and triaging vulnerabilities, escalating critical issues to senior security engineers or Security Operations as needed.
• Participate in security incident investigations related to high-profile vulnerabilities, helping gather data and assess potential impact on Samsara infrastructure.
• Contribute to documentation and process improvements to streamline vulnerability management workflows.
• Champion Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) in daily work.
• Be regularly on call to support

Minimum requirements for the role:

• 6+ years of relevant experience with demonstrated impact for security engineering and vulnerability management in an enterprise environment. 
• Significant experience with vulnerability management tooling, in particular modern toolsets such as Wiz, or Semgrep.
• Deep subject matter expertise with security engineering best practices for subjects such as CVSS, EPSS. 
• Strong familiarity with common security vulnerabilities and the ability to judge their severity and impact on the business.
• Excellent development background with experience in Python or GoLang.
• Strong DevOps, DevSecOps, or SRE background with experience in AWS cloud services, and Terraform
• Experience using security automation platforms such as Tines and serverless frameworks such as AWS Lambda.
• Deep understanding of Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), or Software Composition Analysis (SCA) 

An ideal candidate also has:

• Practical experience managing vulnerabilities within a FedRAMP-certified environment.
• Experience integrating vulnerability management into modern CI/CD pipelines with a “shift-left” mentality.

An overview of this role

As the first Engineering Manager embedded the Upstream Studios organization at GitLab, you'll lead a focused team of Engineers responsible for two foundational surfaces: the Pajamas Design System, which powers the coherence of the entire GitLab product, and docs.gitlab.com, the documentation platform serving millions of GitLab users and contributors worldwide. 

This is a rare opportunity to define what engineering leadership looks like inside a design organization. You’ll report to the Chief Design Officer and partner closely with Product Design, Technical Writing, Localization, Marketing, Product Management, and Engineering leaders across GitLab. Critically, the design system is a contribution-based, company-wide platform that engineers across the entire organization depend on and actively participate in. Building those partnerships and making it easier for engineers everywhere to contribute to Pajamas will be central to your success. 

You’ll be a hands-on technical leader and people manager in equal measure: guiding architecture decisions, shaping contribution workflows, and helping a small, high-impact team do some of the most leveraged work at GitLab.

What you'll do

• Lead, mentor,and grow a high-performing team of engineers, working across the Pajamas Design System and the GitLab documentation site.
• Define and build the engineering practice within Upstream Studios–this is a new function and you’ll have real influence over how it takes shape.
• Guide architecture and technical decisions for the design system (components, tokens, patterns) and the docs site (performance, reliability, infrastructure, localization).
• Help others across the organization understand the strategic value of a well-maintained design system and documentation platform.
• Advocates for engineering quality: technical debt, accessibility standards, customer issues, security, and platform reliability.
• Collaborate with Product Design and Technical Writing to translate design and content needs into scalable technical solutions

What you'll bring

• Experience leading infrastructure, platform, or development teams, with a track record of building high-performing, values-aligned teams.
• Deep expertise in design systems–including design tokens, component architecture, accessibility standards, and contribution models.
• Excellent technical background, including professional experience with Git, docs-as-code, Hugo, accessibility and building and maintaining a design system.
• Experience of building and supporting multi-lingual sites and localization workflows at scale.
• Professional experience with JavaScript (Vue.js) and familiarity with Elasticsearch, Ruby/Go, AI tools, and continuous integration and continuous deployment (CI/CD) practices.
• Strong expertise in running and scaling large, consumer-grade platforms, with a focus on reliability, security, performance, and scalability.
• Proficiency in the English language, both written and verbal, sufficient for success in a remote and largely asynchronous work environment.
• Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organizational problems and propose thorough iterative solutions.
• Experience with performance and optimization problems and a demonstrated ability to both diagnose and prevent these problems
• Comfort working in a highly agile, intensely iterative software development process.
• Passion for open source and developer tools, with a commitment to GitLab's values, inclusive culture, and high-performance expectations.

About the team

Upstream Studios is the full-stack experience organization for GitLab. We imagine it, we design it, we document it, we ship it—partnering across product, engineering, and marketing to deliver a continuous deployment of quality.

We integrate research, design, frontend engineering, documentation, and brand into a unified delivery pipeline, shaping how customers experience GitLab from first impression to final deployment. For more information on how we work, see the Upstream Studios section of the GitLab Handbook.

How You'll Make an Impact: 

As a Senior DevOps Engineer at Cloudbeds, your goal is to constantly improve and scale our SaaS platform to deliver an exceptional experience to hoteliers and their guests worldwide. You'll own the creation, monitoring, automation, and support of our cloud infrastructure and delivery pipelines — enabling product teams to ship high-quality software with speed and confidence. Working within a bottom-up culture that values healthy debate and collaborative problem-solving, you'll have real influence over architecture decisions and the opportunity to shape how we scale infrastructure for one of the fastest-growing hospitality technology platforms in the world.

Our Infrastructure Team: 

Our Infrastructure team is made up of engineers who take genuine pride in their craft, owning projects end-to-end and holding themselves to a high bar. We're passionate about technology and constantly pushing to improve our stack, not just maintain it. If you thrive in an environment where attention to detail matters, great communication is a given, and you're comfortable challenging the status quo to make things better, you'll feel right at home here.

What You Bring to the Team:

• Architect, improve, and scale Cloudbeds' cloud infrastructure on AWS, with a focus on reliability, security, and performance
• Build and evolve our Kubernetes (EKS) platform, driving adoption of containerization best practices across engineering teams
• Automate infrastructure provisioning and configuration using infrastructure-as-code tools like Terraform
• Design, build, and maintain CI/CD pipelines (GitHub Actions, ArgoCD) that enable fast, reliable software delivery
• Partner with product and engineering teams to drive projects to production, sharing DevOps expertise and ensuring strong environment configuration from the infrastructure side
• Maintain and improve monitoring, logging, and alerting systems to ensure platform health and rapid incident response
• Participate in on-call rotation to support production environment stability.

What Sets You Up for Success:

• 5+ years of experience as a DevOps Engineer working hands-on with AWS (networking, compute, storage, databases, queues, cache, permissions).
• 5+ years of strong Kubernetes and Docker experience, including implementing and scaling EKS platforms at production scale.
• Deep expertise with Terraform for infrastructure-as-code and configuration management.
• Proven experience building and supporting CI/CD pipelines using GitHub Actions and ArgoCD.
• Strong knowledge of monitoring and observability tools such as Datadog, Prometheus, Loki, or AWS CloudWatch.
• Working knowledge of web application servers (NGINX, Ingress controllers), databases (MySQL, PostgreSQL, Aurora), caching (Redis, Memcached), and queue technologies (SQS).
• Ability to write Bash and/or Python scripts to automate operational tasks.
• Strong Linux system administration skills and solid networking fundamentals.
• Excellent written and verbal English communication skills; comfortable working asynchronously across a globally distributed remote team.

#LI-REMOTE #LI-IK1