The ad says“Coach leaders and engineers on effective agentic development, context engineering and critical review of AI-generated work so speed never comes at the cost of engineering judgement”
The ad says“Build and lead a small, exceptional, AI-native engineering organisation that turns real customer problems into scalable, reliable and cost-effective software — while developing the next generation of engineering leaders and continuously improving how Storyful ships”
The ad says“Distributed / event-driven systems and APIs”
The ad says“Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering”
The ad says“Cloud architecture (AWS) and cost optimisation”
The ad says“Modern backend and web architectures”
The ad says“CI/CD and infrastructure as code”
The ad says“Hands-on Claude / Claude Code experience is a hard requirement. Over the last two years you have led teams that moved beyond experimentation and became demonstrably AI mature”
The ad says“Hands-on Claude / Claude Code experience is a hard requirement. Over the last two years you have led teams that moved beyond experimentation and became demonstrably AI mature”
The ad says“Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering”
The ad says“Coach leaders and engineers on effective agentic development, context engineering and critical review of AI-generated work so speed never comes at the cost of engineering judgement”
The ad says“Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering”
The ad says“CI/CD and infrastructure as code”
The ad says“Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering”
The ad says“Security and reliability fundamentals”
The ad says“Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering”
The ad says“Security and reliability fundamentals”
The ad says“Modern backend and web architectures”
Build and lead a small, exceptional, AI-native engineering organisation that turns real customer problems into scalable, reliable and cost-effective software — while developing the next generation of engineering leaders and continuously improving how Storyful ships
Software engineering is changing rapidly. Agentic development has removed many of the old constraints around writing code, but it has also shifted the bottlenecks into planning, verification, review, quality, security and decision-making
We want a leader who has already made that transition. You will lead an organisation of approximately 18 people through Tech, our QA Automation Lead, Infrastructure Lead and Principal Engineer. Your job is to create the conditions in which talented people do their best work: clear outcomes, strong technical judgement, high trust, low ego, fast feedback and just enough process
This is not a role for a manager who has moved away from engineering. You will lead from the front — coaching leaders, challenging architecture, joining incidents, reviewing code and occasionally prototyping or shipping with Claude when that is the highest-leverage thing you can do
Lead, coach and develop 5 -7 senior technical leaders, creating clear growth plans, candid feedback loops and meaningful succession paths
Build a track record of promotions and expanded leadership scope by developing the leaders of tomorrow — not by becoming the decision-maker for everything
Set a high bar for performance, ownership and collaboration; address under-performance early and fairly, and recognise exceptional impact
Create a culture of humility, curiosity, challenge and psychological safety where strong people can disagree well and then commit
Design and continuously improve a lightweight engineering operating model: clear accountabilities, fast decisions, small batches, short feedback loops and minimal ceremony
Remove process that no longer adds value. Encourage teams to prototype, test assumptions quickly and fail fast in discovery — while maintaining a high bar for production quality and customer trust
Give teams autonomy inside clear guardrails, making ownership and decision rights obvious across Engineering, QA Automation and Infrastructure
Use delivery and quality data to find bottlenecks and improve the system rather than using metrics as targets in themselves
Make Claude and Claude Code a standard part of how the organisation discovers, designs, builds, tests, reviews, documents and operates software
Codify an AI operating system that includes shared context, reusable skills, deterministic guardrails, permissions/hooks, review standards, testing practices and appropriate governance
Coach leaders and engineers on effective agentic development, context engineering and critical review of AI-generated work so speed never comes at the cost of engineering judgement
Measure whether AI adoption is actually improving outcomes — including cycle time, onboarding/ramp time, quality, reliability and the speed at which customer problems are solved
Partner closely with Product and business leaders to translate customer pain points and company priorities into clear engineering outcomes
Keep teams focused on the problem being solved, not the volume of tickets completed. Challenge scope, sequence work intelligently and create momentum through ambiguity
Build tight feedback loops between customers, Product and Engineering so teams can learn quickly from what is actually happening in the market
Be accountable for predictable delivery while preserving the ability to change direction when evidence says we should
Provide technical leadership across architecture, scalability, reliability, security, observability, infrastructure, quality automation and cloud cost
Be comfortable going deep with technical audiences: lead design reviews, challenge trade-offs, review production code, debug difficult problems and make build-versus-buy or sequencing decisions
Ensure quality is engineered into the delivery lifecycle through strong automation, CI/CD, observability, incident learning and pragmatic engineering standards
Work closely with the Principal Engineer and technical leads so architecture evolves deliberately without creating unnecessary centralised decision-making
Stay close enough to the work to understand the reality of the teams you lead. Prototype with Claude, review code and get involved when your technical judgement can materially unblock progress
Communicate technical strategy clearly to engineers and business strategy clearly to executives, connecting architecture choices to customer value, risk, cost and growth
Bring energy, urgency and optimism without creating chaos. Be the person who raises standards, creates clarity and makes the people around them better
What success looks like (first 6–12 months):
A stronger leadership bench: every lead has clear expectations and development goals, and there is visible evidence of people growing into broader responsibility
A simple, understood engineering operating model that improves speed, collaboration and accountability without adding bureaucracy
Claude Code is embedded as an organisational capability rather than an individual productivity tool, with reusable skills, guardrails, review practices and measurable improvements in delivery and quality
Engineering teams are demonstrably more autonomous and consistently connect technical work to customer and business outcomes
Reliability, quality, infrastructure and cloud-cost practices are measurable, owned and improving as the platform scales
The team have a trusted engineering leader who can move fluently between strategy, people, architecture and execution
Benefits
20 weeks of parental leave
4 weeks of paid caregiver leave
Up to 4 weeks of remote work per year
1 paid volunteer day annually
$700 caregiver reimbursement
Headspace emotional wellness membership
ClassPass fitness and wellness membership
Financial rewards for well-being activities
Preferred experience
Experience leading across product engineering plus disciplines such as Infrastructure / SRE / Platform and QA Automation, with a strong understanding of reliability, observability, CI/CD, testing and cloud economics
Evidence that you personally changed an engineering operating model around AI: improving throughput and/or quality, teaching teams how to work effectively with AI, and establishing guardrails, skills, processes and governance
Hands-on Claude / Claude Code experience is a hard requirement. Over the last two years you have led teams that moved beyond experimentation and became demonstrably AI mature
A track record of building scalable, reliable, secure and cost-effective software that solves real customer problems — not technology for technology’s sake
A demonstrable track record of developing people and leaders: promotions, expanded scope, strong succession pipelines and teams that became more capable under your leadership
Strong software engineering foundations and enough recent hands-on experience to review production code, contribute to architecture, prototype and debug credibly
Excellent communication and influence: comfortable debating architecture with senior engineers and discussing strategy, trade-offs and investment with executives
High agency, humility and sound judgement in ambiguous environments. You know when to delegate, when to challenge and when to get directly involved
Proven engineering leadership experience in a high-growth or scale-up SaaS product business, including recent experience managing Tech Leads, Engineering Managers or equivalent senior technical leaders
Strong product and customer instincts, with examples of engineering decisions driven by customer evidence and measurable business outcomes
We do not require an exact technology match. We do expect you to be technically fluent, able to learn quickly and able to choose tools pragmatically
Experience building data-intensive, AI-powered, media, intelligence or real-time information products
Deep experience in one or more of: distributed systems, cloud infrastructure, platform engineering, reliability engineering, developer productivity or automated quality engineering
Experience defining engineering career frameworks, leadership expectations or succession programmes
Experience scaling an engineering organisation through a meaningful growth or transformation phase
Experience using AI to improve more than coding — for example incident response, documentation, testing, architecture review, developer onboarding or engineering analytics
Shared project context and instructions
AI-assisted code review, testing, debugging and prototyping
Skills, hooks, permissions and guardrails
Claude / Claude Code
Automated testing and quality engineering
Observability, SLOs and incident management
Cloud architecture (AWS) and cost optimisation
CI/CD and infrastructure as code
Security and reliability fundamentals
Modern backend and web architectures
Distributed / event-driven systems and APIs
Ability to read, review and occasionally ship production code
