Full Stack Engineer - AI Systems Location: UK Remote/Hybrid Job Type: Permanent, Full-Time Salary: £120,000 + Equity About the Opportunity A high-growth AI startup is seeking a Full Stack Engineer - AI Systems to help build the next generation of AI-native productivity products. This is an opportunity to join a small, highly talented engineering team building intelligent systems that go far beyond traditional chat applications. The company is developing a proactive AI assistant capable of managing workflows, maintaining context, interacting with tools, and completing real-world tasks with minimal user input. You'll work at the intersection of product engineering, AI systems, and user experience, helping to transform advanced AI capabilities into reliable, production-grade solutions used by people every day. The Role As a Full Stack Engineer - AI Systems, you will play a key role in designing, building, and scaling AI-native workflows across Front End, Back End, and AI infrastructure. You will be responsible for creating systems that can reason, plan, execute tasks, recover from failures, and provide a seamless user experience. This role is ideal for engineers who enjoy solving complex technical challenges and want to work on cutting-edge AI products. Key Responsibilities Product Development Build end-to-end features across Front End, Back End, and AI systems. Develop scalable applications that support intelligent workflows. Deliver production-ready solutions focused on user impact. AI & Agent Systems Design and implement agent workflows capable of multi-step reasoning and task execution. Build systems that coordinate planning, tool usage, recovery, and completion across complex workflows. Integrate LLMs, retrieval systems, memory layers, and external services into user-facing products. Reliability & Performance Design low-latency, Real Time AI experiences. Implement monitoring, observability, and evaluation frameworks. Improve workflow reliability and build robust fallback mechanisms. Optimise performance across AI-powered applications. Collaboration Work closely with Product, Engineering, and Machine Learning teams. Contribute to architectural decisions and product strategy. Continuously improve features based on user feedback and production insights. Required Skills & Experience Strong commercial experience as a Full Stack Engineer. Experience developing both Front End and Back End applications. Solid understanding of system design and API architecture. Experience building AI-powered products using: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Agentic systems AI workflows Proven track record of delivering features from concept through to production. Strong problem-solving and decision-making skills. Comfortable working in a fast-paced startup environment. Desirable Experience Building autonomous or agent-based systems. Working with model evaluation and testing frameworks. Experience with vector databases and retrieval technologies. Kubernetes and cloud-native infrastructure. Real Time application optimisation and observability tooling. Technology Stack Next.js Python Node.js PyTorch OpenAI & Anthropic APIs Open-source LLMs SQL & NoSQL Databases Docker Kubernetes What's on Offer? Competitive salary and equity package. Opportunity to work on cutting-edge AI technology. Significant ownership and autonomy. Direct influence over product direction and technical architecture. Fast-moving, highly collaborative environment. Exposure to some of the most challenging problems in AI, including: Agent orchestration Workflow automation Persistent memory Reasoning systems Reliability engineering About You You thrive in environments where ambiguity is common, ownership is expected, and innovation happens quickly. You're excited by the idea of building products that could fundamentally change how people interact with software and leverage AI in their daily lives. If you're passionate about AI, product development, and building intelligent systems at scale, we'd love to hear from you. Apply now for a confidential discussion.
Jul 14, 2026
Full time
Full Stack Engineer - AI Systems Location: UK Remote/Hybrid Job Type: Permanent, Full-Time Salary: £120,000 + Equity About the Opportunity A high-growth AI startup is seeking a Full Stack Engineer - AI Systems to help build the next generation of AI-native productivity products. This is an opportunity to join a small, highly talented engineering team building intelligent systems that go far beyond traditional chat applications. The company is developing a proactive AI assistant capable of managing workflows, maintaining context, interacting with tools, and completing real-world tasks with minimal user input. You'll work at the intersection of product engineering, AI systems, and user experience, helping to transform advanced AI capabilities into reliable, production-grade solutions used by people every day. The Role As a Full Stack Engineer - AI Systems, you will play a key role in designing, building, and scaling AI-native workflows across Front End, Back End, and AI infrastructure. You will be responsible for creating systems that can reason, plan, execute tasks, recover from failures, and provide a seamless user experience. This role is ideal for engineers who enjoy solving complex technical challenges and want to work on cutting-edge AI products. Key Responsibilities Product Development Build end-to-end features across Front End, Back End, and AI systems. Develop scalable applications that support intelligent workflows. Deliver production-ready solutions focused on user impact. AI & Agent Systems Design and implement agent workflows capable of multi-step reasoning and task execution. Build systems that coordinate planning, tool usage, recovery, and completion across complex workflows. Integrate LLMs, retrieval systems, memory layers, and external services into user-facing products. Reliability & Performance Design low-latency, Real Time AI experiences. Implement monitoring, observability, and evaluation frameworks. Improve workflow reliability and build robust fallback mechanisms. Optimise performance across AI-powered applications. Collaboration Work closely with Product, Engineering, and Machine Learning teams. Contribute to architectural decisions and product strategy. Continuously improve features based on user feedback and production insights. Required Skills & Experience Strong commercial experience as a Full Stack Engineer. Experience developing both Front End and Back End applications. Solid understanding of system design and API architecture. Experience building AI-powered products using: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Agentic systems AI workflows Proven track record of delivering features from concept through to production. Strong problem-solving and decision-making skills. Comfortable working in a fast-paced startup environment. Desirable Experience Building autonomous or agent-based systems. Working with model evaluation and testing frameworks. Experience with vector databases and retrieval technologies. Kubernetes and cloud-native infrastructure. Real Time application optimisation and observability tooling. Technology Stack Next.js Python Node.js PyTorch OpenAI & Anthropic APIs Open-source LLMs SQL & NoSQL Databases Docker Kubernetes What's on Offer? Competitive salary and equity package. Opportunity to work on cutting-edge AI technology. Significant ownership and autonomy. Direct influence over product direction and technical architecture. Fast-moving, highly collaborative environment. Exposure to some of the most challenging problems in AI, including: Agent orchestration Workflow automation Persistent memory Reasoning systems Reliability engineering About You You thrive in environments where ambiguity is common, ownership is expected, and innovation happens quickly. You're excited by the idea of building products that could fundamentally change how people interact with software and leverage AI in their daily lives. If you're passionate about AI, product development, and building intelligent systems at scale, we'd love to hear from you. Apply now for a confidential discussion.
As a Backend Engineer, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience. You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. Focus Build and operate Back End systems that serve AI-powered features in production. Design inference pipelines, orchestration layers, and service boundaries around models. Own production concerns: monitoring, logging, alerting, and incident response. Optimize latency and throughput across inference, caching, batching, and streaming. Ideal Experiences Strong Back End engineering fundamentals in production environments. Experience running high-throughput, low-latency services. Familiarity with AI inference patterns (LLMs, embeddings, multimodal). Comfortable debugging distributed systems under load. Bias toward shipping and learning from production behavior. Outcomes Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput. APIs are stable, clear, and support seamless integration with Front End and ML systems. Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact. Iterative improvements based on real usage continuously increase system performance and reliability. Tech Stack Python NodeJs Pytorch OpenAI/Anthropic/open-source LLMs SQl & noSQL Kubernetes Docker How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product
Jul 13, 2026
Full time
As a Backend Engineer, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience. You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. Focus Build and operate Back End systems that serve AI-powered features in production. Design inference pipelines, orchestration layers, and service boundaries around models. Own production concerns: monitoring, logging, alerting, and incident response. Optimize latency and throughput across inference, caching, batching, and streaming. Ideal Experiences Strong Back End engineering fundamentals in production environments. Experience running high-throughput, low-latency services. Familiarity with AI inference patterns (LLMs, embeddings, multimodal). Comfortable debugging distributed systems under load. Bias toward shipping and learning from production behavior. Outcomes Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput. APIs are stable, clear, and support seamless integration with Front End and ML systems. Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact. Iterative improvements based on real usage continuously increase system performance and reliability. Tech Stack Python NodeJs Pytorch OpenAI/Anthropic/open-source LLMs SQl & noSQL Kubernetes Docker How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product
Senior Data Engineer (Azure Databricks) - SC Cleared Location: London, UK (3 days per week onsite) Salary: Up to £75,000 per annum Job Type: Permanent, Full-Time Security Clearance: Active SC Clearance Required The Opportunity We are seeking an experienced Senior Data Engineer to join a high-performing team responsible for developing and enhancing a modern Azure-based data platform supporting economic analysis, forecasting, and modelling activities. This role offers the opportunity to work with large-scale datasets, cloud-native technologies, and modern data engineering practices. You will play a key role in designing and optimising data pipelines, implementing data governance processes, and delivering reliable data solutions that enable critical business insights. Key Responsibilities Data Pipeline Development & Optimisation Design, develop, and maintain scalable and reliable data pipelines. Build ETL/ELT solutions to ingest, transform, and load data from multiple sources, including APIs, databases, and external data providers. Optimise pipeline performance, scalability, and cost efficiency. Implement data quality controls, validation processes, and monitoring solutions. Data Transformation & Processing Develop complex data transformation logic using Spark (PySpark or Scala). Build data cleansing, enrichment, aggregation, and processing solutions. Ensure data accuracy, consistency, and reliability throughout the data life cycle. Azure Databricks Development Develop and support solutions within Azure Databricks. Work extensively with Unity Catalog, Delta Lake, Spark SQL, and related Databricks services. Apply Databricks best practices for development, deployment, and workload optimisation. Develop solutions using SQL, Python, R, YAML, and JavaScript. Data Integration Integrate data from relational databases, APIs, and streaming platforms. Design and implement robust data integration patterns. Collaborate with development teams to support seamless data exchange across systems. Data Quality & Governance Utilise Azure Purview for data governance and data quality initiatives. Implement data lineage, metadata management, monitoring, and alerting capabilities. Ensure compliance with organisational data governance standards and best practices. Collaboration & Delivery Work closely with data scientists, analysts, economists, and technical stakeholders. Translate business requirements into scalable technical solutions. Participate in code reviews, technical discussions, and knowledge-sharing sessions. Contribute to Agile delivery processes and continuous improvement initiatives. DevOps & Automation Automate data engineering workflows and deployments. Develop and maintain CI/CD pipelines. Promote DevOps best practices across the wider engineering team. Required Skills & Experience 8+ years of Data Engineering experience (10+ years preferred). Minimum 3 years of hands-on Azure Databricks experience. Strong expertise in Python, PySpark, and/or Scala. Extensive experience with: Azure Databricks Azure Data Factory Azure Blob Storage Azure SQL Database Delta Lake Spark SQL Strong understanding of: Data architecture Data modelling Data warehousing Data integration patterns Experience working with large-scale datasets and complex data pipelines. Knowledge of SQL and NoSQL databases. Experience with data governance, data quality frameworks, and metadata management. Experience using Git and working within Agile delivery environments. Excellent communication, stakeholder management, and problem-solving skills. Desirable Skills Azure Purview Kafka Azure Event Hubs Power BI Tableau Azure DevOps Jenkins Docker Kubernetes Experience within Financial Services, Banking, or Economic Data environments Microsoft Certified: Azure Data Engineer Associate Databricks Certifications What's On Offer Salary up to £75,000. Hybrid working model with 3 days per week in a London office. Opportunity to work on a large-scale Azure and Databricks data platform. Exposure to enterprise-level data engineering challenges and modern cloud technologies. Collaborative and technically focused environment. Career development and certification support opportunities. Please note: Active SC Clearance is required for this position. Applicants without current SC Clearance will not be considered.
Jul 13, 2026
Full time
Senior Data Engineer (Azure Databricks) - SC Cleared Location: London, UK (3 days per week onsite) Salary: Up to £75,000 per annum Job Type: Permanent, Full-Time Security Clearance: Active SC Clearance Required The Opportunity We are seeking an experienced Senior Data Engineer to join a high-performing team responsible for developing and enhancing a modern Azure-based data platform supporting economic analysis, forecasting, and modelling activities. This role offers the opportunity to work with large-scale datasets, cloud-native technologies, and modern data engineering practices. You will play a key role in designing and optimising data pipelines, implementing data governance processes, and delivering reliable data solutions that enable critical business insights. Key Responsibilities Data Pipeline Development & Optimisation Design, develop, and maintain scalable and reliable data pipelines. Build ETL/ELT solutions to ingest, transform, and load data from multiple sources, including APIs, databases, and external data providers. Optimise pipeline performance, scalability, and cost efficiency. Implement data quality controls, validation processes, and monitoring solutions. Data Transformation & Processing Develop complex data transformation logic using Spark (PySpark or Scala). Build data cleansing, enrichment, aggregation, and processing solutions. Ensure data accuracy, consistency, and reliability throughout the data life cycle. Azure Databricks Development Develop and support solutions within Azure Databricks. Work extensively with Unity Catalog, Delta Lake, Spark SQL, and related Databricks services. Apply Databricks best practices for development, deployment, and workload optimisation. Develop solutions using SQL, Python, R, YAML, and JavaScript. Data Integration Integrate data from relational databases, APIs, and streaming platforms. Design and implement robust data integration patterns. Collaborate with development teams to support seamless data exchange across systems. Data Quality & Governance Utilise Azure Purview for data governance and data quality initiatives. Implement data lineage, metadata management, monitoring, and alerting capabilities. Ensure compliance with organisational data governance standards and best practices. Collaboration & Delivery Work closely with data scientists, analysts, economists, and technical stakeholders. Translate business requirements into scalable technical solutions. Participate in code reviews, technical discussions, and knowledge-sharing sessions. Contribute to Agile delivery processes and continuous improvement initiatives. DevOps & Automation Automate data engineering workflows and deployments. Develop and maintain CI/CD pipelines. Promote DevOps best practices across the wider engineering team. Required Skills & Experience 8+ years of Data Engineering experience (10+ years preferred). Minimum 3 years of hands-on Azure Databricks experience. Strong expertise in Python, PySpark, and/or Scala. Extensive experience with: Azure Databricks Azure Data Factory Azure Blob Storage Azure SQL Database Delta Lake Spark SQL Strong understanding of: Data architecture Data modelling Data warehousing Data integration patterns Experience working with large-scale datasets and complex data pipelines. Knowledge of SQL and NoSQL databases. Experience with data governance, data quality frameworks, and metadata management. Experience using Git and working within Agile delivery environments. Excellent communication, stakeholder management, and problem-solving skills. Desirable Skills Azure Purview Kafka Azure Event Hubs Power BI Tableau Azure DevOps Jenkins Docker Kubernetes Experience within Financial Services, Banking, or Economic Data environments Microsoft Certified: Azure Data Engineer Associate Databricks Certifications What's On Offer Salary up to £75,000. Hybrid working model with 3 days per week in a London office. Opportunity to work on a large-scale Azure and Databricks data platform. Exposure to enterprise-level data engineering challenges and modern cloud technologies. Collaborative and technically focused environment. Career development and certification support opportunities. Please note: Active SC Clearance is required for this position. Applicants without current SC Clearance will not be considered.
Data Product Owner Engagement Details Contract Duration: 6 months (with potential for extension) Start Date: ASAP Rate: Up to £700 per day (outside IR35) Interview Process: Two-stage, with a targeted completion within 1-2 days for expedited onboarding. Position Overview We are looking for a Data Product Owner to lead the strategic definition and delivery of data products for a major transformation program in the insurance sector. This role is crucial for bridging complex business requirements with technical solutions, ensuring that every data product delivers measurable, tangible value. You'll partner with our expert engineering teams and act as a key driver of change within a top-tier consultancy environment. Key Responsibilities Product Strategy: Own and prioritize the data product backlog, translating business needs into actionable features, user stories, and clear release plans. Benefits Realization: Establish frameworks to measure, track, and report on value realization and benefits to ensure all data initiatives have a demonstrable ROI. Technical Partnership: Collaborate closely with data engineering teams, providing technical guidance and ensuring scalable data solutions are designed and delivered. Data Governance: Champion data governance and quality assurance, embedding best practices and compliance controls throughout the entire data life cycle. Stakeholder Management: Align product roadmaps with key business stakeholders and regulatory requirements, ensuring technical and business objectives are met. Required Qualifications Experience: Proven experience as a Data Product Owner in a data-centric delivery environment, with a strong background in leading agile teams. Technical Skills: Hands-on experience with Databricks is essential. . Proficiency with Snowflake is highly advantageous. Solid understanding of the AWS ecosystem is required. Competencies: In-depth knowledge of data governance, quality management, and regulatory compliance. Demonstrated track record of benefits realization and outcome-driven delivery. Prior experience within the insurance industry is highly desirable.
Oct 02, 2025
Contractor
Data Product Owner Engagement Details Contract Duration: 6 months (with potential for extension) Start Date: ASAP Rate: Up to £700 per day (outside IR35) Interview Process: Two-stage, with a targeted completion within 1-2 days for expedited onboarding. Position Overview We are looking for a Data Product Owner to lead the strategic definition and delivery of data products for a major transformation program in the insurance sector. This role is crucial for bridging complex business requirements with technical solutions, ensuring that every data product delivers measurable, tangible value. You'll partner with our expert engineering teams and act as a key driver of change within a top-tier consultancy environment. Key Responsibilities Product Strategy: Own and prioritize the data product backlog, translating business needs into actionable features, user stories, and clear release plans. Benefits Realization: Establish frameworks to measure, track, and report on value realization and benefits to ensure all data initiatives have a demonstrable ROI. Technical Partnership: Collaborate closely with data engineering teams, providing technical guidance and ensuring scalable data solutions are designed and delivered. Data Governance: Champion data governance and quality assurance, embedding best practices and compliance controls throughout the entire data life cycle. Stakeholder Management: Align product roadmaps with key business stakeholders and regulatory requirements, ensuring technical and business objectives are met. Required Qualifications Experience: Proven experience as a Data Product Owner in a data-centric delivery environment, with a strong background in leading agile teams. Technical Skills: Hands-on experience with Databricks is essential. . Proficiency with Snowflake is highly advantageous. Solid understanding of the AWS ecosystem is required. Competencies: In-depth knowledge of data governance, quality management, and regulatory compliance. Demonstrated track record of benefits realization and outcome-driven delivery. Prior experience within the insurance industry is highly desirable.
