The Role: Platform Engineering Manager (Cloud Foundations)

Location: London / Hybrid (2 days per week in office) 

Reporting to: Head of Technology Operations

The Role 

 Rightmove’s Cloud Foundations team delivers the secure, reliable, scalable and cost‑optimised platform foundations used by hundreds of engineers and dozens of mission‑critical services. As we ensure safe, low friction delivery of core services and operate at scale, the Engineering Manager will lead a team providing cloud platforms and infrastructure, cloud security, governance, automation, and operational excellence.  

This position blends people leadership, cloud operations, platform engineering, security governance, and FinOps. The successful candidate brings deep operational experience in product‑led technology companies and understands how to run cloud foundations as a modern internal platform. 

Key Outcomes for This Role 

Strategy, Delivery and Execution 

• Through working with your team, key stakeholders, and the platform product manager, we provide a cloud platform strategy and roadmap that aligns to Rightmove business goals and our internal customer’s needs.  

• The team provides accurate estimates and realistic plans. 

• The platform roadmap, initiatives/projects, and OKRs are well managed and delivered in line with expectations. 

People Leadership & Team Development 

• Through coaching and mentoring engineers, setting clear, achievable development goals and provides actionable feedback, they improve skills, confidence, and impact. 

• Individual growth plans align with team objectives and organisational priorities. 

• Engineers are supported to designing and delivering scalable, secure, resilient platform services without micromanagement. 

• Achievements are recognised and rewarded, performance issues are addressed early and fairly.  

• There is an inclusive, psychologically safe environment; with leadership tailored to individual strengths and motivations. 

Platform Engineering, Operations & Reliability 

• Cloud platform and key services are reliable, incident detection and resolution are smooth due to proactive monitoring, well‑maintained alerts/logs, and complete observability coverage. 

• Platform resilience and DR planning/testing strategy is defined and operational, working across the business with validated requirements and outcomes. 

• Backup, restore and resilience mechanisms are regularly tested, ensuring the platform can recover predictably. 

• Incident management processes are consistently followed, including timely post‑incident reviews (PIRs) and completion of follow‑up actions. 

• On‑call is well staffed, sustainably operated, and fosters a healthy on‑call culture. 

• Automation (AI‑driven or traditional) delivers increased speed, reduced toil, and enhanced reliability. 

• Support requests are triaged and responded to promptly, with prioritisation based on upstream impact. 

• Capacity and cloud spend are effectively managed—no incidents caused by under‑provisioning, and costs are controlled by avoiding unnecessary over‑provisioning. 

• Finops culture is embedded with tooling and process across product development teams 

• Vendor relationships are managed, supplier due diligence is completed on time, contract costs and SLAs are negotiated as needed. 

• Continuous improvement culture is embedded: teams regularly evaluate performance, reliability and cost efficiency, feeding learnings back into the platform. 

Governance, Guardrails & Security 

• Infrastructure‑as‑Code, Policy‑as‑Code and automated guardrails accelerate delivery while strengthening governance and consistency across the platform. 

• Secure software delivery practices and policies are followed, vulnerabilities are managed within SLAs, Platform configuration standards are maintained (CIS Benchmarks). 

• Cloud security policies, governance standards and privacy controls consistent with predefined roles, least‑privilege IAM patterns and role-based access practices are implemented and followed 

• The organisation meets regulatory, contractual and audit obligations, maintaining documentation, policies and process evidence for compliance reviews 

• Secure cloud configurations, WAF policies, bot protection, and cloud‑native security tooling are maintained. 

• Architecture diagrams for network and key components are maintained for audit, security, knowledge sharing purposes. 

What you’ll bring  

• Proven experience in cloud operations and platform engineering management, overseeing cloud infrastructure and platforms, monitoring, reliability, and service delivery in production environments. 

• Previous hands‑on experience running large cloud-based website environments with GKE, service mesh, load balancers, CDN/WAF, Kafka, Elasticsearch. 

• Strong understanding of cloud services including networking, compute, storage, containerisation, security and IAM. 

• Experience with IAC, python, Go, CI/CD, Terraform, Kubernetes, modern ops tooling and DevOps workflows. 

• Demonstrated experience implementing security controls, IAM policies, and cloud governance frameworks.  

• Familiarity with platform engineering concepts including developer platforms, reusable platform components and enabling internal product teams. 

• Experience improving operational processes and developing documented procedures (monitoring, DR, incident response, upgrade processes). 

• Strong leadership, team management, collaboration and communication skills, aligned with expectations for managing technical cloud teams.  

• Experience designing scalable, reliable cloud platform architectures, consistent with Cloud  

The Role: Engineering Manager (AI Enablement)
Location: London office / Hybrid (2 days per week in the office)
Reporting to: Head of Technology Operations

The Role:

Our AI Enablement team accelerates how product and engineering teams deliver value by enabling safe, effective, high‑quality adoption of AI‑native tools, practices and agentic workflows. We partner across the organisation to reduce friction, enhance developer productivity, and drive governed AI integration at scale. 

We're looking for a leader with a builder's DNA who approaches the role like a founding team member would. You're obsessed with building the best agentic operating system for product teams and proving it works by making teams wildly more efficient whilst not compromising quality. You’re a collaborator, relationship builder, and a key person of influence. 

As the Engineering Manager for this team, you will lead a small, high‑impact group that builds and operationalises internal AI capabilities, partners with teams to remove adoption friction, and ensures governed, scalable use of AI. This role will remain close to the technology and the engineers, pairing on hard problems, contributing to design and automation, and delivering the platform, services, workflows and practices that scale AI‑assisted delivery across the organisation. 

This is a highly cross‑functional role requiring strong technical fluency, exceptional communication, relationship building and influencing skills, as well a deep expertise of how AI tooling, platforms and systems deliver value in the product development lifecycle. 

Key outcomes for this role:

Delivery & Execution 

• Lead a team of engineers building and deploying highly performant, reliable AI agents and workflows for internal users. These are scalable systems handling hundreds of thousands of prompts in production. You'll ensure technical excellence, operational reliability, and high impact. You'll be hands-on: meet internal customers, read PRs, build integrations, jump into issues when needed. 
• Surface what's breaking, what's missing, and what would unlock more value. Translate technical concepts for non‑technical stakeholders and keep communication tight. 
• Anticipate and remove blockers; lead incident response and follow‑ups so lessons are embedded; continuously improve ways of working for predictability.  

Technical Stewardship  

• Ensure the team can successfully navigate the Rightmove governance, security, and reliability requirements in order to deliver fit for purpose architecture, systems and standards. Ensure design reviews consult all relevant stakeholders; champion quality, observability, performance and cost efficiency. 
• Stay close to the implementation to maintain technical credibility: pair on complex problems, contribute to design docs and automation/scripts/skills, and periodically contribute code where appropriate. 
• Shape internal AI platform patterns (e.g., AI‑assisted planning, design, generation/review, test generation and validation, documentation automation, log/metric analysis, incident assistance, SSDLC agents) and guide safe adoption across teams. 

People Leadership & Team Development 

• Rally your team through ambiguity, setbacks, and tough stakeholder asks. Push for clarity, focus, and high energy in every sprint. Drive urgency without burning people out.  
• Coach and mentor engineers who want to grow fast and build great things; run effective 1:1s, set clear growth goals, recognise achievements and address performance early and fairly. 
• Create an inclusive, psychologically safe environment; tailor leadership to individual strengths and motivations.  

Governance, Safety & Scalability 

• Partner with security, compliance, data and architecture to ensure governed, safe AI adoption; translate emerging risks and constraints into product and engineering decisions that scale.  

What you'll bring: 

• Experience leading engineering teams that build and scale end-to-end production systems. 

• Deep understanding of the current AI tooling and agentic workflow landscape and how they are being used to deliver value in the product development lifecycle. 

• Hands on experience with AI models, tools and frameworks: agent orchestration, prompt engineering, RAG pipelines, evaluation frameworks, LangChain, Codex, Claude, Gemini, observability tools and best practices. 

• A leadership style that blends high standards with empathy, fostering both speed and quality. 

• Proven ability to work closely with customers and translate business needs into technical deliverables. 

• You measure success by customer outcomes, not just features shipped.
  
  
•  Excellent communication skills across technical and non-technical audiences. 
  
  
• Strong technical problem-solving skills and ability to guide teams through ambiguous, fast-changing environments.
  

Even better if you have:

• Experience building or deploying agentic AI systems and/or AI tooling in production at scale 

The Role: Technical Product Manager (AI Enablement)
Location: London office / Hybrid (2 days per week in the office)
Reporting to: Head of Technology Operations

The Role

Our AI Enablement team accelerates how product and engineering teams deliver value by enabling safe, effective, high‑quality adoption of AI‑native tools, practices and agentic workflows. We partner across the organisation to reduce friction, enhance developer productivity, and drive governed AI integration at scale. 

As the Technical Product Manager for the AI Enablement team, you will help shape how product development teams adopt AI responsibly and effectively; establishing platforms and enabling agentic workflows with patterns, frameworks, and enablement practices that scale across engineering and product development to increase productivity and quality. 

This is a highly cross‑functional role requiring strong technical fluency, exceptional stakeholder alignment skills, and a deep understanding of the product lifecycle and software engineering workflows. 

Key outcomes for this role:

Customer-Centric AI Enablement

• Internal engineering and product teams experience limited friction in the adoption of production-grade AI tools, agents and workflows that directly address the bottlenecks, friction, and inefficiencies in the product development lifecycle.  

Accelerated Time-to-Value

• Teams deliver software faster and more efficiently through AI‑enhanced product development, testing, documentation, and operational workflows. 
• High‑impact use cases are identified, validated, and rolled out systematically across teams.
   

Clear Business Alignment & Visibility

• AI enablement initiatives and the roadmap are tied directly to engineering productivity, business value streams, and strategic priorities.
• Communication of impact, tradeoffs, and adoption progress is transparent and visible to stakeholders.
   

Data-Driven Decision Making 

• Clear AI enablement metrics (adoption, velocity improvements, model performance, workflow usage) drive prioritisation and planning.
• Teams focus on the highest‑value problems through insight‑led prioritisation. 

Key Responsibilities:

Internal Customer Insights

• Maintain an understanding of engineering, product, QA, security, and operations teams’ AI needs, friction points, and opportunities.
• Use structured research, platform telemetry, surveys, and direct engagement to guide prioritisation.  

AI Platform & Capability Decision

• Working with Technology Leadership shape the internal AI platform strategy: capabilities, use cases, patterns, and adoption pathways.
• Define “what good looks like” for AI‑native and agentic workflows such as:  

*AI‑assisted generation and review 

*Test generation and validation 

*Documentation automation 

*Log/metric analysis and incident assistance 

*Internal AI agents supporting SSDLC tasks 

Product Roadmaps & Delivery

• Own and maintain a clear AI enablement roadmap that balances customer needs, capability maturity, governance, and organisational priorities. 

• Ensure tradeoffs and recommendations are well‑articulated with supporting data. 

• Ensure the successful end-to-end delivery of the roadmap.  

Governance, Safety & Scalability

• Partner with security, compliance, data, and architecture teams to ensure all AI adoption is safe, governed, and scalable. 
• Translate emerging risks and constraints into product decisions and prioritization frameworks.
   

Enablement & Adoption

• Create clear documentation, playbooks, and training materials for AI tooling and workflows. 

• Partner with engineering teams to pilot new AI capabilities, capture learnings, and scale successful patterns across product development. 

• Champion AI best practices and ensure enablement efforts are measurable, repeatable, and continuously improving. 

• Measure adoption, efficiency, quality, and report progress at key stakeholder forums. 

We're looking for someone who

• Has experience managing technical products (developer tools, ML/AI systems, automation platforms, and multi‑agent systems). 

• Understands the software development lifecycle, DevOps/SRE practices, and the realities of engineering and product delivery workflows. 

• Has strong empathy for engineers and enjoys spending time with users to deeply understand workflows and bottlenecks. 

• Can translate complex technical opportunities into clear business value and narrative. 

• Is highly structured, self‑directed, and capable of aligning diverse stakeholders. 

• Enjoys experimentation and can balance rapid iteration with risk‑aware governance. 

The Role: Engineering Manager (Site Reliability)

Location: Reporting to: London / Hybrid (2 days per week in office)

Reporting to: Head of Technology Operations

The Role

The Platform and Reliability Engineering Teams are responsible for the services that underpin the Rightmove website and enable all of our product development teams to ship functionality rapidly and safely. We strive to deliver annual availability of at least 99.99% (less than 5 mins downtime a month).  

The Site Reliability Engineering Manager’s role is to ensure operational excellence, drive observability and reliability at scale, and own the incident management processes and tools. 

This position blends people leadership, full stack reliability engineering, service management, influencing without authority. The successful candidate brings strong technical experience in reliability engineering, monitoring, alerting and observability for product‑led technology companies combined with strong customer empathy and communication skills. 

Monitoring, Alerting, and Observability 

• Product teams have high reliability confidence, incident detection and resolution are smooth due to proactive monitoring, well‑maintained alerts/logs and high levels of observability coverage. 
• Clear reliability expectations between platform, security, product & business. Prioritisation based on reliability risk and real data.  

Incident Management 

• Consistency and standardisation of incident management resulting fast incident detection and resolution
• Maintaining a culture of accountability, transparency, collaboration & learning
• Good data quality, insights & decision‑making with strong feedback loops to all relevant stakeholders 

Reliability Engineering 

• Clear reliability patterns and standards drive strong reliability and fewer cascading failures. E.g. probes, graceful termination/degradation, timeouts, retries, backoff, jitter, circuit breakers, bulkheads. 
• Shared understanding how our system fails, where any weak points are with prioritised improvement plans in place. 

Delivery and Execution 

• Own and manage reliability roadmap and metrics, initiatives/projects, and OKR delivery in line with expectations.
• Align reliability strategy and delivery plans with business goals, partnering with technical product manager, DX, CF, DBA, security, product and data teams. 

People Leadership & Team Development 

• Supports team with objectives and growth plans to improve skills, confidence, and impact aligned with business objectives
• Guides engineers in designing scalable, secure, resilient platform services
• Create an inclusive, psychologically safe environment; tailor leadership to individual strengths and motivations. 

What you’ll bring  

• Proven experience in site reliability engineering management, overseeing observability, monitoring, reliability, and service delivery in production environments.
• Understanding of reliability in distributed software microservices and cloud-based environments.
• Experience implementing and running modern SRE tooling and incident management workflows, SRE service management frameworks e.g. SLO/SLIs.
• Familiarity with platform engineering concepts including developer platforms, reusable platform components, reducing friction for product teams.
• Experience improving operational processes and developing documented procedures (monitoring, DR, incident response, upgrade processes).
• Leadership, team management, collaboration and communication skills, aligned with expectations for managing technical/engineering teams.