Technology

We have partnered with a high-availability B2B SaaS company delivering mission-critical software to enterprise clients.As customer adoption increases, they are expanding their SRE function to improve reliability, scalability, and performance across their cloud-native environment. This is a core growth function for the business.What you'll be doing:Defining SLIs, SLOs, and error budgetsImproving system reliability across AWS environmentsDriving observability improvementsAutomating infrastructure recovery and scalingLeading incident response and postmortem processesOptimising performance across distributed systems About you:5+ years in SRE, DevOps or cloud infrastructureStrong AWS or GCP experienceKubernetes and container orchestrationExperience in high-availability SaaS environments

We have partnered with a Series C B2B SaaS business investing heavily in its internal developer platform.They are building a dedicated Platform Engineering team responsible for creating self-service cloud infrastructure, improving developer experience, and enabling product teams to ship faster.This is not traditional DevOps. This is platform ownership.What you'll be doingDesigning internal developer platforms on AWSBuilding reusable Terraform modulesCreating scalable Kubernetes foundationsImplementing service mesh and container orchestration strategiesImproving cloud cost visibility and governancePartnering with engineering teams to enhance release velocity About you6+ years in cloud infrastructure or platform engineeringStrong AWS architecture experienceTerraform at scaleKubernetes in productionExperience building internal tooling or developer platformsFamiliarity with GitOps workflows This is a team-build hire. They plan to add multiple engineers into Platform this year.

We have partnered with a fast-growing B2B SaaS company building a high-scale, multi-tenant platform used by enterprise customers across North America.As part of continued growth, they are hiring multiple Senior DevOps Engineers to help evolve their cloud infrastructure and CI/CD ecosystem.You will work closely with platform and application engineering teams to build secure, scalable infrastructure and improve deployment velocity across the business.What you'll be doing:Designing and maintaining AWS-based infrastructureBuilding and scaling Kubernetes clustersDeveloping Infrastructure as Code using TerraformOwning CI/CD pipelines across multiple servicesImproving observability using Datadog, Prometheus or similarDriving automation across environmentsSupporting incident response and reliability improvements About you5+ years in DevOps or cloud infrastructure engineeringDeep AWS experienceStrong Terraform experienceProduction Kubernetes experienceExperience supporting microservices environmentsStrong scripting skills in Python or Bash This team is scaling quickly, and they expect to hire several engineers in this function over the next 12 months.

We have partnered with a technology business that is embedding AI directly into its core platform, focusing on practical, customer-facing use cases rather than standalone experiments. They are now looking to hire an Applied AI Engineer to help turn AI capability into features that are used in production every day.This is a hands-on role for someone who enjoys working at the intersection of engineering, product, and AI, and who is motivated by outcomes rather than experiments that never leave the lab.About the role:Build and ship AI-powered features that are embedded directly into customer-facing productsWork closely with Product and Engineering to translate real user problems into practical AI solutionsDesign and implement AI workflows that move from experimentation into reliable production systemsApply techniques such as LLM integration, prompt engineering, embeddings, and retrieval-based approaches where they add genuine valueIntegrate AI components into existing backend services and product workflowsEvaluate model performance, reliability, and cost in real-world usageIterate quickly based on user feedback and product requirements About you:Strong engineering background with hands-on experience building and shipping AI-powered features into productionSolid experience using Python in real-world systems, including API development and service integrationPractical experience working with LLMs, including prompt design, model integration, and evaluation in live environmentsFamiliarity with techniques such as embeddings, vector search, and retrieval-based approachesExperience integrating AI components into existing backend architectures rather than greenfield demosStrong understanding of trade-offs around performance, cost, reliability, and security in AI systemsProduct-aware mindset, able to align technical decisions with real user and business needs

We have partnered with a fast-growing, product-led technology company that is building a complex, high-traffic platform and is now looking to hire a Staff Software Engineer. This role sits at the highest individual contributor level and is designed for someone who wants deep technical impact without moving into people management.This is a key hire for the business. You will work on the hardest technical problems, influence architecture and engineering standards, and act as a technical reference point for the wider team as the company continues to scale.About the role:Own and solve complex, high-impact technical challenges across the core platformDrive architectural decisions across distributed, cloud-based systemsWork in a backend environment primarily built using Python and Go, with services designed around scalability, performance, and clear ownership boundariesDesign and evolve APIs, microservices, and event-driven services used across the platformContribute to system design around performance, reliability, security, and observabilityPartner closely with Engineering Managers and Product to shape pragmatic technical solutionsSet engineering standards around code quality, testing, and operational excellenceLead by example through hands-on contribution to critical parts of the codebaseMentor senior and mid-level engineers through design reviews and technical guidance About you:Strong experience as a Senior or Staff Engineer in a product-led or startup environmentDeep understanding of modern backend systems and distributed architecturesHands-on experience with Python and/or Go in production environmentsComfortable working with cloud platforms, containerisation, and CI/CD pipelinesExperience designing and operating systems used at scalePragmatic mindset with a strong focus on maintainability and real-world delivery

We have partnered with a product-led technology company that is scaling its engineering function and is now hiring an Engineering Manager to lead a high-performing team. This is a hands-on leadership role for someone who enjoys building teams, improving delivery, and staying close to technical decisions while working on meaningful, customer-facing products.You will play a key role in shaping how the engineering team operates as the company grows, working closely with Product and Design to ship high-quality features at pace without sacrificing code quality or team culture.About the role:Lead a cross-functional product engineering team responsible for building and evolving core customer-facing featuresOwn sprint planning, prioritisation, and delivery, ensuring predictable execution and clear accountabilityPartner closely with Product to shape technical approaches, break down complex initiatives, and sequence work effectivelyRaise the bar on code quality, testing, and engineering standards through reviews, tooling, and best practicesIdentify delivery bottlenecks and actively improve team velocity, collaboration, and ways of workingContribute to architectural discussions, technical trade-offs, and longer-term platform decisionsSupport hiring, onboarding, and development of engineers as the team scales About you:Proven experience as an Engineering Manager or Senior Engineer who has moved into people leadershipStrong background in modern product-led engineering environmentsComfortable balancing people management with technical oversightExperience working closely with product teams in fast-moving environmentsClear communicator who can align engineers, product, and stakeholders

We have partnered with a product-led organisation building large-scale, production-grade machine learning systems.This is a Principal ML Engineer role for someone who wants to set technical direction, solve hard problems and influence how ML is built and deployed across the business.You will be hands-on where it matters, while also shaping architecture, standards and best practices for ML at scale.About the role:Define and evolve the organisation's machine learning architecture and technical standardsLead the design and deployment of scalable ML pipelines and inference systemsOwn the reliability, performance, and observability of models running in productionPartner closely with data science, engineering, and product leaders on high-impact ML initiativesGuide and mentor senior engineers and data scientists on ML engineering best practicesDrive adoption of modern ML and applied AI techniques where they create real valueAbout you:Deep experience building production ML systems using Python and modern ML frameworks such as PyTorch or TensorFlowStrong background in classical ML (scikit-learn, gradient boosting) and feature engineering at scaleProven experience working with large datasets using Pandas or Polars and distributed processing frameworks like Spark or PySparkHands-on experience deploying models using Docker, APIs (for example FastAPI) and cloud-native infrastructureStrong MLOps experience including experiment tracking, model versioning, monitoring and drift detection using tools such as MLflow or Weights & BiasesExperience orchestrating ML workflows with Airflow, Prefect or DagsterSolid cloud experience across AWS, GCP, or Azure, including scalable compute and managed ML servicesPractical exposure to modern applied AI, including embeddings, vector search and retrieval-augmented generationComfortable setting technical direction, making trade-offs and owning ML outcomes in production

We have partnered with a fast-growing, product-led organisation that is investing heavily in modern data science and applied AI.This is a chance to work on problems where experimentation, model impact and real-world deployment actually matter. The environment is hands-on, fast moving and built for people who want to push beyond dashboards and offline models.This role is about building, testing and shipping intelligent systems. Think modern ML stacks, real-time data, large-scale experimentation and the intersection of classical data science with today's AI tooling.About the role:Design and build end-to-end data science solutions, from problem framing to production deploymentWork with large, messy, real-world datasets and turn them into models that influence product and business decisionsDevelop and iterate on machine learning models including predictive, probabilistic and optimisation-based approachesExperiment with modern techniques such as LLM-powered workflows, embeddings and retrieval-augmented approaches where relevantPartner closely with engineers and product teams to productionise models and measure real impactOwn experimentation, validation, and monitoring to ensure models perform in live environments About you:4-6 years of experience in data science or applied machine learning rolesStrong grounding in statistics, experimentation and model evaluation, not just model buildingHands-on experience with Python and common data science librariesComfortable working across the full lifecycle from exploration to deploymentExperience working with modern ML tooling such as feature stores, model pipelines or real-time inference is a plusCurious by nature and excited by new approaches such as LLMs, agentic workflows and multimodal dataAble to communicate complex ideas clearly to non-technical stakeholders

We have partnered with a fast-growing wealthtech startup entering an exciting phase of product and team growth. The business is building consumer-facing financial products and is now looking to strengthen its frontend capability with a Senior Software Engineer focused on React.This role is well suited to someone who enjoys building and evolving live, production-ready frontend systems, shipping new features regularly and working closely with product and design in a true product-led environment.About the role:Take ownership of building and enhancing frontend features used by real customers in a live environmentWork primarily with React and TypeScript to deliver scalable, high-quality UI componentsCollaborate closely with Product, Design and Backend Engineers to translate requirements into well-executed frontend solutionsContribute to frontend architecture, performance optimisation and code quality standardsSupport and influence best practices around testing, maintainability and frontend toolingExposure to React Native is a plus, particularly where features are shared across web and mobile About you:Around 5-6 years of professional software engineering experience, with a strong frontend focusProven experience working in product-led companies where frontend is core to the user experienceStrong hands-on experience with React and TypeScript in production environmentsComfortable working on live systems, shipping features incrementally and owning what you buildSolid understanding of modern frontend patterns, state management and performance considerationsExperience with React Native is beneficial but not essentialThis is a great opportunity to join a growing wealthtech business where frontend engineering plays a critical role in shaping the product and customer experience.

We have partnered with a high-availability B2B SaaS company delivering mission-critical software to enterprise clients.As customer adoption increases, they are expanding their SRE function to improve reliability, scalability, and performance across their cloud-native environment. This is a core growth function for the business.What you'll be doing:Defining SLIs, SLOs, and error budgetsImproving system reliability across AWS environmentsDriving observability improvementsAutomating infrastructure recovery and scalingLeading incident response and postmortem processesOptimising performance across distributed systems About you:5+ years in SRE, DevOps or cloud infrastructureStrong AWS or GCP experienceKubernetes and container orchestrationExperience in high-availability SaaS environments

We have partnered with a Series C B2B SaaS business investing heavily in its internal developer platform.They are building a dedicated Platform Engineering team responsible for creating self-service cloud infrastructure, improving developer experience, and enabling product teams to ship faster.This is not traditional DevOps. This is platform ownership.What you'll be doingDesigning internal developer platforms on AWSBuilding reusable Terraform modulesCreating scalable Kubernetes foundationsImplementing service mesh and container orchestration strategiesImproving cloud cost visibility and governancePartnering with engineering teams to enhance release velocity About you6+ years in cloud infrastructure or platform engineeringStrong AWS architecture experienceTerraform at scaleKubernetes in productionExperience building internal tooling or developer platformsFamiliarity with GitOps workflows This is a team-build hire. They plan to add multiple engineers into Platform this year.

We have partnered with a fast-growing B2B SaaS company building a high-scale, multi-tenant platform used by enterprise customers across North America.As part of continued growth, they are hiring multiple Senior DevOps Engineers to help evolve their cloud infrastructure and CI/CD ecosystem.You will work closely with platform and application engineering teams to build secure, scalable infrastructure and improve deployment velocity across the business.What you'll be doing:Designing and maintaining AWS-based infrastructureBuilding and scaling Kubernetes clustersDeveloping Infrastructure as Code using TerraformOwning CI/CD pipelines across multiple servicesImproving observability using Datadog, Prometheus or similarDriving automation across environmentsSupporting incident response and reliability improvements About you5+ years in DevOps or cloud infrastructure engineeringDeep AWS experienceStrong Terraform experienceProduction Kubernetes experienceExperience supporting microservices environmentsStrong scripting skills in Python or Bash This team is scaling quickly, and they expect to hire several engineers in this function over the next 12 months.

We have partnered with a technology business that is embedding AI directly into its core platform, focusing on practical, customer-facing use cases rather than standalone experiments. They are now looking to hire an Applied AI Engineer to help turn AI capability into features that are used in production every day.This is a hands-on role for someone who enjoys working at the intersection of engineering, product, and AI, and who is motivated by outcomes rather than experiments that never leave the lab.About the role:Build and ship AI-powered features that are embedded directly into customer-facing productsWork closely with Product and Engineering to translate real user problems into practical AI solutionsDesign and implement AI workflows that move from experimentation into reliable production systemsApply techniques such as LLM integration, prompt engineering, embeddings, and retrieval-based approaches where they add genuine valueIntegrate AI components into existing backend services and product workflowsEvaluate model performance, reliability, and cost in real-world usageIterate quickly based on user feedback and product requirements About you:Strong engineering background with hands-on experience building and shipping AI-powered features into productionSolid experience using Python in real-world systems, including API development and service integrationPractical experience working with LLMs, including prompt design, model integration, and evaluation in live environmentsFamiliarity with techniques such as embeddings, vector search, and retrieval-based approachesExperience integrating AI components into existing backend architectures rather than greenfield demosStrong understanding of trade-offs around performance, cost, reliability, and security in AI systemsProduct-aware mindset, able to align technical decisions with real user and business needs

We have partnered with a fast-growing, product-led technology company that is building a complex, high-traffic platform and is now looking to hire a Staff Software Engineer. This role sits at the highest individual contributor level and is designed for someone who wants deep technical impact without moving into people management.This is a key hire for the business. You will work on the hardest technical problems, influence architecture and engineering standards, and act as a technical reference point for the wider team as the company continues to scale.About the role:Own and solve complex, high-impact technical challenges across the core platformDrive architectural decisions across distributed, cloud-based systemsWork in a backend environment primarily built using Python and Go, with services designed around scalability, performance, and clear ownership boundariesDesign and evolve APIs, microservices, and event-driven services used across the platformContribute to system design around performance, reliability, security, and observabilityPartner closely with Engineering Managers and Product to shape pragmatic technical solutionsSet engineering standards around code quality, testing, and operational excellenceLead by example through hands-on contribution to critical parts of the codebaseMentor senior and mid-level engineers through design reviews and technical guidance About you:Strong experience as a Senior or Staff Engineer in a product-led or startup environmentDeep understanding of modern backend systems and distributed architecturesHands-on experience with Python and/or Go in production environmentsComfortable working with cloud platforms, containerisation, and CI/CD pipelinesExperience designing and operating systems used at scalePragmatic mindset with a strong focus on maintainability and real-world delivery

We have partnered with a product-led technology company that is scaling its engineering function and is now hiring an Engineering Manager to lead a high-performing team. This is a hands-on leadership role for someone who enjoys building teams, improving delivery, and staying close to technical decisions while working on meaningful, customer-facing products.You will play a key role in shaping how the engineering team operates as the company grows, working closely with Product and Design to ship high-quality features at pace without sacrificing code quality or team culture.About the role:Lead a cross-functional product engineering team responsible for building and evolving core customer-facing featuresOwn sprint planning, prioritisation, and delivery, ensuring predictable execution and clear accountabilityPartner closely with Product to shape technical approaches, break down complex initiatives, and sequence work effectivelyRaise the bar on code quality, testing, and engineering standards through reviews, tooling, and best practicesIdentify delivery bottlenecks and actively improve team velocity, collaboration, and ways of workingContribute to architectural discussions, technical trade-offs, and longer-term platform decisionsSupport hiring, onboarding, and development of engineers as the team scales About you:Proven experience as an Engineering Manager or Senior Engineer who has moved into people leadershipStrong background in modern product-led engineering environmentsComfortable balancing people management with technical oversightExperience working closely with product teams in fast-moving environmentsClear communicator who can align engineers, product, and stakeholders

We have partnered with a product-led organisation building large-scale, production-grade machine learning systems.This is a Principal ML Engineer role for someone who wants to set technical direction, solve hard problems and influence how ML is built and deployed across the business.You will be hands-on where it matters, while also shaping architecture, standards and best practices for ML at scale.About the role:Define and evolve the organisation's machine learning architecture and technical standardsLead the design and deployment of scalable ML pipelines and inference systemsOwn the reliability, performance, and observability of models running in productionPartner closely with data science, engineering, and product leaders on high-impact ML initiativesGuide and mentor senior engineers and data scientists on ML engineering best practicesDrive adoption of modern ML and applied AI techniques where they create real valueAbout you:Deep experience building production ML systems using Python and modern ML frameworks such as PyTorch or TensorFlowStrong background in classical ML (scikit-learn, gradient boosting) and feature engineering at scaleProven experience working with large datasets using Pandas or Polars and distributed processing frameworks like Spark or PySparkHands-on experience deploying models using Docker, APIs (for example FastAPI) and cloud-native infrastructureStrong MLOps experience including experiment tracking, model versioning, monitoring and drift detection using tools such as MLflow or Weights & BiasesExperience orchestrating ML workflows with Airflow, Prefect or DagsterSolid cloud experience across AWS, GCP, or Azure, including scalable compute and managed ML servicesPractical exposure to modern applied AI, including embeddings, vector search and retrieval-augmented generationComfortable setting technical direction, making trade-offs and owning ML outcomes in production

We have partnered with a fast-growing, product-led organisation that is investing heavily in modern data science and applied AI.This is a chance to work on problems where experimentation, model impact and real-world deployment actually matter. The environment is hands-on, fast moving and built for people who want to push beyond dashboards and offline models.This role is about building, testing and shipping intelligent systems. Think modern ML stacks, real-time data, large-scale experimentation and the intersection of classical data science with today's AI tooling.About the role:Design and build end-to-end data science solutions, from problem framing to production deploymentWork with large, messy, real-world datasets and turn them into models that influence product and business decisionsDevelop and iterate on machine learning models including predictive, probabilistic and optimisation-based approachesExperiment with modern techniques such as LLM-powered workflows, embeddings and retrieval-augmented approaches where relevantPartner closely with engineers and product teams to productionise models and measure real impactOwn experimentation, validation, and monitoring to ensure models perform in live environments About you:4-6 years of experience in data science or applied machine learning rolesStrong grounding in statistics, experimentation and model evaluation, not just model buildingHands-on experience with Python and common data science librariesComfortable working across the full lifecycle from exploration to deploymentExperience working with modern ML tooling such as feature stores, model pipelines or real-time inference is a plusCurious by nature and excited by new approaches such as LLMs, agentic workflows and multimodal dataAble to communicate complex ideas clearly to non-technical stakeholders

We have partnered with a fast-growing wealthtech startup entering an exciting phase of product and team growth. The business is building consumer-facing financial products and is now looking to strengthen its frontend capability with a Senior Software Engineer focused on React.This role is well suited to someone who enjoys building and evolving live, production-ready frontend systems, shipping new features regularly and working closely with product and design in a true product-led environment.About the role:Take ownership of building and enhancing frontend features used by real customers in a live environmentWork primarily with React and TypeScript to deliver scalable, high-quality UI componentsCollaborate closely with Product, Design and Backend Engineers to translate requirements into well-executed frontend solutionsContribute to frontend architecture, performance optimisation and code quality standardsSupport and influence best practices around testing, maintainability and frontend toolingExposure to React Native is a plus, particularly where features are shared across web and mobile About you:Around 5-6 years of professional software engineering experience, with a strong frontend focusProven experience working in product-led companies where frontend is core to the user experienceStrong hands-on experience with React and TypeScript in production environmentsComfortable working on live systems, shipping features incrementally and owning what you buildSolid understanding of modern frontend patterns, state management and performance considerationsExperience with React Native is beneficial but not essentialThis is a great opportunity to join a growing wealthtech business where frontend engineering plays a critical role in shaping the product and customer experience.