# Senior Software Engineer at Signal AI

Signal AI is hiring a Senior Software Engineer for a remote role open to applicants in United Kingdom. Level rates it Little AI ●○○○; you can [apply on Signal AI](https://jobsbylevel.com/go/7acf8846-11f7-40a5-9744-45ab980b248d?utm_medium=ai-agent).

AI Level 1, AI centrality 7 out of 100. Remote (London Office).

## Details

- Company: [Signal AI](https://jobsbylevel.com/companies/signal-ai)
- AI level: AI Level 1 (score 7 out of 100)
- Location: Remote (London Office)
- Posted: October 26, 2026
- Apply: https://jobsbylevel.com/go/7acf8846-11f7-40a5-9744-45ab980b248d?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-software-engineer-at-signal-ai-4a0cae

## Prepare for this job

The job page lists 2 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-software-engineer-at-signal-ai-4a0cae

## Description

At Signal AI, we use cutting-edge AI technology to offer clarity on decisions that shape businesses and society. We value restless curiosity, creative thinking, and diverse perspectives as we strive to become AI-native. We believe that AI is a collaborator, not just a tool, and we invite passionate individuals to join us on our journey as we continue to learn, experiment, and grow together. About the role Engineers at Signal AI are expected to bring a strong product mindset to their work. They’re comfortable with complex problems and proactively look for ambiguous ones rather than wait for others to resolve them, and work wherever the product needs them across the full stack. Engineers work closely with other disciplines, including applied research and design, as part of teams that own revenue-critical products from ideation through to production. Owning a product end to end means much of an engineer’s time goes on understanding the problem: talking to colleagues in research, design and product, testing assumptions, and deciding what is worth building. Our engineering teams are organised around the needs of the business. We value collaboration and teamwork, and we believe the best solutions to complex problems come from working together. You will work primarily within a small cross-functional team, contributing to its architecture and to engineering standards. You will provide clear, focused technical plans for current and future solutions, and you will keep the long-term technical vision in view. AI-assisted development is part of everyday work across the organisation. We expect engineers to use tools like Claude Code to move quickly across the entire software development lifecycle, so more of their time is spent on the product questions that matter. What You’ll Be Doing Building intuitive user interfaces and data visualisations that unlock valuable insights for our customers. Building services that can cope with large volumes of data. Implementing and maintaining the AWS infrastructure that supports the services owned by the team. Build, maintain and evolve large-scale distributed systems, ensuring they remain resilient. Building observability into everything you ship (logging, metrics, alerting). Owning BAU in your primary domain and building enough operational familiarity with the other domains to support incidents, understand cross-domain interactions, and describe architectural boundaries. Collaborating with Product and Design to define and scope the products we build. Communicating with other teams and stakeholders when needed. Working in a collaborative environment. Pairing for most of your time, giving and receiving reviews, and helping to uphold the team’s shared quality standard. Working with AI This is not specifically an AI Engineer role, but every senior engineer in this team is expected to be AI-literate, in two directions: using AI to build better, and building AI into the product responsibly. Keep your practice current. Use current models, coding agents and agent tooling in your daily work, and re-test earlier assumptions as capabilities change; what was unreliable six months ago may be routine today. Open mind, evidence-led. Give a new tool, pattern or model a fair chance and evaluate it against our own codebases and workflows before ruling it out. Push back when something is presented as a silver bullet and adopting it would bring more risk, or more change, than the team can absorb. Make both calls on evidence, not on instinct or hype. Quality bar parity. Agent-generated code and content are held to the same standard as human work. Review it, test it and secure it the same way. Build to learn. A working prototype in front of a Product owner or a customer beats a slide. Be as willing to report a disappointing result as an exciting one, and kill weak ideas early. Design the human checkpoints and watch the cost. For agentic features, define what the system may decide alone, what needs approval and what

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Source: https://jobsbylevel.com/jobs/senior-software-engineer-at-signal-ai-4a0cae

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