Full Stack Engineer

Senior Product Engineer London Hybrid Startup £90,000 - £130,000 + meaningful equity

• Golang
• Rust
• TypeScript, Node.js
• React.js, Next.js
• AWS or GCP

Most B2B SaaS products are effectively dashboards on top of a database. This isn't that. We're working with an Agentic AI startup building infrastructure and intelligent software systems that sit underneath large scale operational workflows and real time decision making processes. The platform processes very high volumes of live data, powers complex orchestration pipelines, and delivers AI driven functionality directly into customer environments at enterprise scale. The engineering challenges are genuinely difficult. Not "we use Kubernetes so we're scaling" difficult. More the kind of problems involving distributed systems, real time data ingestion, AI orchestration pipelines, and building software that customers rely on day to day inside production environments. The team is still small enough that every engineer materially changes the trajectory of the business. No giant hierarchy, no endless roadmap theatre, no Jira archaeology expedition trying to work out why a ticket exists. That means speaking to customers, understanding commercial context, shaping product direction, building systems, shipping to production, monitoring outcomes, and iterating quickly.

• Real time event streaming systems handling very high traffic volumes
• AI powered workflows and orchestration pipelines
• Product engineering across backend infrastructure and frontend applications
• CRM and third party integration infrastructure
• Identity resolution and large scale data processing
• Systems where reliability and speed both matter because customers actively use what gets shipped

• Enjoy ambiguity rather than waiting for perfect specs
• Think commercially as well as technically
• Want ownership rather than ticket queues
• Care about shipping quickly
• Like being close to founders, customers, and product decisions
• Have worked in strong start ups or fast moving product environments before
• Technical background matters, but mindset matters more. Open to strong engineers from different backend ecosystems if built complex systems and can learn quickly.

A few things worth knowing:

• High frequency of deployments per week
• Engineers use AI tooling heavily to improve speed and workflow efficiency
• Minimal meeting culture
• High trust environment with lots of autonomy
• Strong engineering standards without unnecessary process theatre
• Small team, meaningful ownership, direct impact

If you're the type of engineer who likes solving hard problems with smart people, has energy & ambition, and actually seeing your work used in production by real customers, this is a very good opportunity.