The Portfolio Group
We're looking for a Senior Software Engineer to join a growing AI team and take ownership of the application and integration layer behind a new generation of AI-powered products. This is a genuinely full-stack engineering role, combining production-grade backend development, API design, AI integrations and frontend engineering. You'll work across the full application lifecycle, designing the services and interfaces that connect AI capabilities to the products customers and colleagues use every day. You'll play a key role in building MCP integrations, agent-to-agent connectivity and robust API services, while also developing responsive, accessible interfaces in React and TypeScript. What you'll be doing Own the application and integration layer of AI products end to end, covering APIs, integrations, service boundaries and frontend development. Design, build and maintain MCP servers that safely expose systems, content and tooling to AI agents. Develop agent-to-agent connectivity, including message contracts, state management, retries and failure handling. Design clear, scalable APIs using REST and/or GraphQL, including authentication, authorisation, versioning and streaming interfaces such as SSE or WebSockets. Build production frontend applications using React, TypeScript and JavaScript. Work closely with UX and product teams to turn designs into accessible, responsive and intuitive interfaces. Develop AI-specific user experiences including streaming responses, citations, source information, agent/tool progress and graceful error handling. Integrate with internal platforms and third-party services, considering security, scalability, performance and reliability. Establish automated testing across backend and frontend applications, including unit, contract and end-to-end testing. Work with the platform engineering team on deployment, observability, logging, tracing and operational readiness. Act as the technical owner for the application and integration layer, making and documenting key architectural decisions. Provide technical guidance, code reviews and mentoring to other engineers. You should have: Strong commercial experience with Python for backend and integration development. Strong TypeScript/JavaScript and React experience building production applications. Strong API design experience, including REST and/or GraphQL, authentication, authorisation, versioning and streaming. Hands-on experience with MCP (Model Context Protocol) or comparable tool/plugin integration technologies, alongside an interest in AI agents and agent-to-agent connectivity. Solid experience with AWS, ideally including services such as Lambda, ECS, API Gateway, S3, CloudFront, Cognito and IAM. Experience designing and operating distributed or event-driven systems. A strong understanding of observability, testing and CI/CD practices. Experience working with data platforms or stores such as MongoDB, OpenSearch or Databricks. Experience integrating internal systems and third-party services securely and reliably. Experience working closely with designers to deliver production-quality frontend applications. A good understanding of accessibility and frontend performance. Experience with RAG, AI agents, tool use or other generative AI application patterns would be advantageous, although deep ML expertise isn't required. This is an opportunity to have genuine ownership over how AI capabilities become usable, scalable software products. You'll be joining an AI-focused engineering environment where you can work at the intersection of software engineering, APIs, cloud infrastructure and generative AI, while helping establish the engineering standards and architecture that will support future products. If you're a senior engineer who enjoys moving between backend architecture and frontend delivery, wants ownership rather than simply a list of tickets, and is excited about where AI agents and modern application architecture are heading, we'd love to hear from you. INDLON 52212MSR The Portfolio Group are acting on behalf of our client in recruiting for this position.
We're looking for a Senior Software Engineer to join a growing AI team and take ownership of the application and integration layer behind a new generation of AI-powered products. This is a genuinely full-stack engineering role, combining production-grade backend development, API design, AI integrations and frontend engineering. You'll work across the full application lifecycle, designing the services and interfaces that connect AI capabilities to the products customers and colleagues use every day. You'll play a key role in building MCP integrations, agent-to-agent connectivity and robust API services, while also developing responsive, accessible interfaces in React and TypeScript. What you'll be doing Own the application and integration layer of AI products end to end, covering APIs, integrations, service boundaries and frontend development. Design, build and maintain MCP servers that safely expose systems, content and tooling to AI agents. Develop agent-to-agent connectivity, including message contracts, state management, retries and failure handling. Design clear, scalable APIs using REST and/or GraphQL, including authentication, authorisation, versioning and streaming interfaces such as SSE or WebSockets. Build production frontend applications using React, TypeScript and JavaScript. Work closely with UX and product teams to turn designs into accessible, responsive and intuitive interfaces. Develop AI-specific user experiences including streaming responses, citations, source information, agent/tool progress and graceful error handling. Integrate with internal platforms and third-party services, considering security, scalability, performance and reliability. Establish automated testing across backend and frontend applications, including unit, contract and end-to-end testing. Work with the platform engineering team on deployment, observability, logging, tracing and operational readiness. Act as the technical owner for the application and integration layer, making and documenting key architectural decisions. Provide technical guidance, code reviews and mentoring to other engineers. You should have: Strong commercial experience with Python for backend and integration development. Strong TypeScript/JavaScript and React experience building production applications. Strong API design experience, including REST and/or GraphQL, authentication, authorisation, versioning and streaming. Hands-on experience with MCP (Model Context Protocol) or comparable tool/plugin integration technologies, alongside an interest in AI agents and agent-to-agent connectivity. Solid experience with AWS, ideally including services such as Lambda, ECS, API Gateway, S3, CloudFront, Cognito and IAM. Experience designing and operating distributed or event-driven systems. A strong understanding of observability, testing and CI/CD practices. Experience working with data platforms or stores such as MongoDB, OpenSearch or Databricks. Experience integrating internal systems and third-party services securely and reliably. Experience working closely with designers to deliver production-quality frontend applications. A good understanding of accessibility and frontend performance. Experience with RAG, AI agents, tool use or other generative AI application patterns would be advantageous, although deep ML expertise isn't required. This is an opportunity to have genuine ownership over how AI capabilities become usable, scalable software products. You'll be joining an AI-focused engineering environment where you can work at the intersection of software engineering, APIs, cloud infrastructure and generative AI, while helping establish the engineering standards and architecture that will support future products. If you're a senior engineer who enjoys moving between backend architecture and frontend delivery, wants ownership rather than simply a list of tickets, and is excited about where AI agents and modern application architecture are heading, we'd love to hear from you. INDLON 52212MSR The Portfolio Group are acting on behalf of our client in recruiting for this position.
reed.co.uk
Reed.ai is looking for a Senior Engineer (Agentic Developer) to join their team in Holborn, London. Overview Join a collaborative, forward-thinking team that values creativity, experimentation, and impact-and help redefine the future of recruitment through intelligent, human-centered technology. Reed.ai is building its recruitment platform using an AI-agent-first way of working. Coding agents do most of the typing; engineers are responsible for what gets built, why, and whether it is good enough to deploy. The platform was built this way from the start with agent fleets working in evidence-gated waves under human direction and it has now launched its product to the market. You'll join a startup-style venture backed by the strength of an established business, at the moment delivery is shifting from a contracted build team to a permanent in-house core: the ways of working you help set now are the ones the platform scales on. We're looking for a senior engineer who has made the shift already. You will turn product intent into clear specifications. You will direct and coordinate coding agents across the stack. You will design the tests, evaluations and review gates that keep quality high. And you will be fully accountable for every line that reaches production, whoever, or whatever, wrote it. You'll write less code than in a traditional senior role and read far more. Success is measured by the outcomes you deliver, how reliable and safe the platform is, and how much the team's agentic workflow improves over time. Lines committed is not a measure we use. How we work Spec-first. Product intent arrives as a brief; work starts by writing the implementable specification and playing it back in plain language before build. The specification is the means of production, its precision sets the ceiling on what the agents can safely build. Evidence-gated. Work ships when its gate proves green, tests passing on enforcing infrastructure, invariants held, migrations verified - not when someone asserts it. Work that cannot prove its gate reverts itself; a clean tree is a passing outcome. Discernment. AI output is a claim, not a fact, a draft until a named human can defend its content without the tool. Fluent and plausible is not the same as correct, and passing output onward at face value is the failure mode we guard against hardest. Drift-aware. The codebase moves faster than any document describing it. Verifying against the live repository is step one of every task; divergence between the signed-off spec and the code is a defect, even when the drifted version is nicer. Communicating constantly. Shared surfaces are claimed before they're touched, coordination notes travel inside pull requests, and the daily standup ends with "what did I change that someone else's brief still assumes?" Key Responsibilities Translate product requirements into testable specifications and tasks, then plan and supervise coding agents across the full stack. Maintain context packs, repository guidance and decision records to support consistent agent output, writing code directly where needed. Define acceptance criteria and independent tests before generation, keeping security controls enabled throughout verification. Review agent-generated code for correctness, security and architectural fit, and maintain automated quality gates in CI/CD. Evaluate AI features for matching accuracy, regressions, adversarial cases, bias and fairness across candidate groups. Maintain coherent architecture, restrict agent access and uphold security, privacy, UK GDPR and applicable recruitment AI obligations. Improve agentic workflows, assess new tools and models, and mentor engineers in spec-first, agent-driven development. Collaborate with product, design and customer experience to test hypotheses and deliver weekly releases behind feature flags. Skills and Experience Substantial commercial engineering experience at senior or lead level, building and running production SaaS systems. Hands-on delivery using AI coding agents such as Claude Code, Cursor or Codex, with evidence of effective workflows, failures caught and results achieved. Strong critical code-review skills and clear written communication to produce precise specifications for agents. Strong PostgreSQL, relational design, REST API and cloud-native fundamentals (AWS preferred), with depth in at least two of Go, Python and TypeScript. Experience in automated testing, CI/CD, DevOps and live database migrations, alongside a working understanding of security, data protection and GDPR. Desirable: experience building or evaluating LLM features, including retrieval, embeddings, vector search, agent orchestration and evaluation frameworks. Desirable: experience with OpenSearch/Elasticsearch, Docker, Kubernetes or event-driven architecture, plus front-end performance and accessibility. Desirable: recruitment, HR technology or matching-system knowledge, and experience in startups or new ventures within larger organisations. Benefits Hybrid working as standard 25 days annual leave plus bank holidays Flexible holiday scheme Paid time off to move home Contributory pension scheme Enhanced family leave benefits Insurance benefits including life assurance Love Mondays events Discount scheme including gyms and popular retailers Range of wellbeing and mental health support avenues Office in a fantastic location, with countless bars, restaurants and theatres right on the doorstep.
Reed.ai is looking for a Senior Engineer (Agentic Developer) to join their team in Holborn, London. Overview Join a collaborative, forward-thinking team that values creativity, experimentation, and impact-and help redefine the future of recruitment through intelligent, human-centered technology. Reed.ai is building its recruitment platform using an AI-agent-first way of working. Coding agents do most of the typing; engineers are responsible for what gets built, why, and whether it is good enough to deploy. The platform was built this way from the start with agent fleets working in evidence-gated waves under human direction and it has now launched its product to the market. You'll join a startup-style venture backed by the strength of an established business, at the moment delivery is shifting from a contracted build team to a permanent in-house core: the ways of working you help set now are the ones the platform scales on. We're looking for a senior engineer who has made the shift already. You will turn product intent into clear specifications. You will direct and coordinate coding agents across the stack. You will design the tests, evaluations and review gates that keep quality high. And you will be fully accountable for every line that reaches production, whoever, or whatever, wrote it. You'll write less code than in a traditional senior role and read far more. Success is measured by the outcomes you deliver, how reliable and safe the platform is, and how much the team's agentic workflow improves over time. Lines committed is not a measure we use. How we work Spec-first. Product intent arrives as a brief; work starts by writing the implementable specification and playing it back in plain language before build. The specification is the means of production, its precision sets the ceiling on what the agents can safely build. Evidence-gated. Work ships when its gate proves green, tests passing on enforcing infrastructure, invariants held, migrations verified - not when someone asserts it. Work that cannot prove its gate reverts itself; a clean tree is a passing outcome. Discernment. AI output is a claim, not a fact, a draft until a named human can defend its content without the tool. Fluent and plausible is not the same as correct, and passing output onward at face value is the failure mode we guard against hardest. Drift-aware. The codebase moves faster than any document describing it. Verifying against the live repository is step one of every task; divergence between the signed-off spec and the code is a defect, even when the drifted version is nicer. Communicating constantly. Shared surfaces are claimed before they're touched, coordination notes travel inside pull requests, and the daily standup ends with "what did I change that someone else's brief still assumes?" Key Responsibilities Translate product requirements into testable specifications and tasks, then plan and supervise coding agents across the full stack. Maintain context packs, repository guidance and decision records to support consistent agent output, writing code directly where needed. Define acceptance criteria and independent tests before generation, keeping security controls enabled throughout verification. Review agent-generated code for correctness, security and architectural fit, and maintain automated quality gates in CI/CD. Evaluate AI features for matching accuracy, regressions, adversarial cases, bias and fairness across candidate groups. Maintain coherent architecture, restrict agent access and uphold security, privacy, UK GDPR and applicable recruitment AI obligations. Improve agentic workflows, assess new tools and models, and mentor engineers in spec-first, agent-driven development. Collaborate with product, design and customer experience to test hypotheses and deliver weekly releases behind feature flags. Skills and Experience Substantial commercial engineering experience at senior or lead level, building and running production SaaS systems. Hands-on delivery using AI coding agents such as Claude Code, Cursor or Codex, with evidence of effective workflows, failures caught and results achieved. Strong critical code-review skills and clear written communication to produce precise specifications for agents. Strong PostgreSQL, relational design, REST API and cloud-native fundamentals (AWS preferred), with depth in at least two of Go, Python and TypeScript. Experience in automated testing, CI/CD, DevOps and live database migrations, alongside a working understanding of security, data protection and GDPR. Desirable: experience building or evaluating LLM features, including retrieval, embeddings, vector search, agent orchestration and evaluation frameworks. Desirable: experience with OpenSearch/Elasticsearch, Docker, Kubernetes or event-driven architecture, plus front-end performance and accessibility. Desirable: recruitment, HR technology or matching-system knowledge, and experience in startups or new ventures within larger organisations. Benefits Hybrid working as standard 25 days annual leave plus bank holidays Flexible holiday scheme Paid time off to move home Contributory pension scheme Enhanced family leave benefits Insurance benefits including life assurance Love Mondays events Discount scheme including gyms and popular retailers Range of wellbeing and mental health support avenues Office in a fantastic location, with countless bars, restaurants and theatres right on the doorstep.
