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Natter

AI-driven enterprise conversation intelligence and insights

Staff or Principal Software Engineer

Software EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • The candidate must have operated at Staff level or above, or as a startup senior technical lead with equivalent scope and impact across multiple teams or the engineering organization.
  • The candidate must have set and delivered technical direction, authored strategy or major architectural direction, and driven alignment across engineers and leadership without formal authority.
  • The candidate must have led the design of production systems handling significant load, data, or complexity and owned their consequences, including migrations, re-architectures, incidents, and decisions requiring reversal.
  • The candidate must have owned production incidents with business impact, from response through root cause analysis to systemic fixes.
  • The candidate must have developed other engineers into senior or Staff roles and introduced standards or practices that endured beyond direct involvement.
  • The candidate must have exceptional written communication, including design and strategy documents that influence decisions.
  • The candidate must regularly write high-quality production code, have deep expertise in at least one of distributed systems, data infrastructure, or frontend architecture, and be fluent enough across the stack to make sound decisions.
  • The candidate must have deep AWS and infrastructure experience, including production cloud architecture, infrastructure as code, continuous integration and continuous delivery, and observability at scale.

Responsibilities

  • Help define the platform’s multi-year technical direction, connect it to business outcomes, and turn it into an executable roadmap with the engineering team.
  • Personally lead the design of critical, high-risk systems, including the AI conversation pipeline, data architecture, and multi-tenant platform, from first principles through production at scale.
  • Make and defend high-impact decisions about build versus buy, data models, service boundaries, and platform choices; establish the standard for decision-making through design documents.
  • Own platform-wide standards for reliability, security, observability, performance, and cost, and hold the engineering team to them.
  • Contribute to how the company hires, levels, and grows engineers; mentor senior engineers toward Staff-level contributions and own the technical hiring bar.
  • Partner with product and engineering leadership and provide technical insight that improves product direction.
  • Represent the company technically with major clients during security reviews, architecture deep dives, and high-stakes incidents.
  • Remain hands-on in critical work by building prototypes, coding difficult components, and responding to serious technical failures.
  • Work across the listed stack: Kotlin, TypeScript, Python, Rust, React, Postgres, DynamoDB, Kafka, ECS, EKS, Lambda, and AWS CDK.

Desired Qualifications

  • Experience building and operating AI- or large language model-powered products in production, including evaluation and latency, cost, and reliability trade-offs.
  • Experience with enterprise B2B SaaS at scale, including multi-tenancy, single sign-on, data isolation, and compliance with SOC 2, ISO 27001, or GDPR.
  • Production experience with event-driven and streaming architectures such as Kafka.
  • Experience taking a platform and engineering team through rapid startup growth.
  • Public technical work, such as talks, writing, or meaningful open-source contributions.

About the Company

Natter

AI-driven enterprise conversation intelligence and insights

Natter provides an AI-native conversation intelligence platform that replaces traditional enterprise feedback methods like surveys and focus groups by enabling thousands of simultaneous one-on-one video conversations. Participants join via a browser link, and the system guides them with structured prompts while AI transcribes and analyzes each conversation in parallel to identify themes, sentiment, and priorities, delivering actionable insights within hours. Unlike surveys and focus groups, it scales to enterprise needs and tends to surface more themes thanks to a psychologically safe, candid discussion format. The goal is to help large organizations make faster, data-backed decisions by turning deep conversations into structured, real-time insights for leadership across HR, sales, strategy, and policy.

Company size
51-200
Company stage
Series A
Total funding
$24M
Headquarters
London, United Kingdom
Founded
2021

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