Software Engineer - AI in London

Join PA Media Group's new AI Enablement team as a founding senior engineer who lives at the bleeding edge of AI-native development. This isn't traditional software engineering - you'll leverage agentic engineering approaches, Claude Code, and the latest AI capabilities to ship solutions at unprecedented velocity, moving from concept to working prototype in days whilst pushing the boundaries of what's technically possible.

Working in the latest technologies and partnering tightly with the Product Owner - AI, you'll be embedded directly with the business teams across PA Media, Alamy, Podium, StreamAMG, and Press Release & Marketing Services. You'll experiment relentlessly, iterate rapidly, and enable business success through technology that others haven't figured out how to build yet. This is senior-level engineering for those who thrive on high energy, constant innovation, and the freedom to explore emerging capabilities before they become mainstream.

The Opportunity

This is a founding senior engineer role in PA Media Group's new AI Enablement team. You won't just build AI systems - you'll define what AI-native engineering means for the organization. We're deliberately keeping the team tiny, giving you extraordinary autonomy to experiment, fail fast, and establish patterns that scale. This is the opposite of corporate engineering: no lengthy approval processes, no legacy constraints slowing you down, just smart engineers moving at startup velocity within a 150+ year institution.

You’ll work differently from traditional engineering roles - you’re forward deployed. You’re embedded with the teams who’ll use what you build, getting feedback in real-time, iterating based on actual usage patterns, and seeing your code make immediate tangible impact. You'll move between news production, visual content licensing, sports analytics, streaming platforms, and press distribution - solving wildly different technical challenges whilst building your understanding of what AI can achieve across diverse contexts.

The technical environment rewards innovation and experimentation. You'll have permission to try emerging capabilities, leverage cutting‑edge AI platforms before they're mainstream, and push boundaries that more conservative organizations can’t justify. We expect some experiments to fail - that's the cost of experimentation. What matters is velocity of learning, speed of iteration, and the ability to scale successes aggressively when you discover approaches that work.

The problems you’ll tackle matter beyond technical curiosity: enabling journalists to work faster without sacrificing accuracy, helping visual content discovery at unprecedented scale, powering sports analytics with AI‑enhanced insights, maintaining trust that defines our heritage whilst embracing transformative technology. This is AI-native engineering at its finest - where your code doesn’t just ship features but defines how a heritage institution leads digital transformation rather than follows it.

Our Values

• Integrity: Acting with trustworthiness, fairness, and accountability in everything we do.
• Ambition: Setting bold goals, striving for excellence, and inspiring progress.
• Innovation: Being curious, solving problems, and embracing a creative future. We constantly ask "how might we?" to reimagine what's possible.
• Collaboration: Building meaningful connections, valuing diverse perspectives, and achieving more together.

Key Responsibilities

• Ship AI-powered solutions at velocity using AI-native development approaches - leveraging Claude Code and agentic engineering techniques to build in hours what traditionally takes days, constantly exploring how AI can accelerate your own engineering workflow whilst solving business problems.
• Build rapid proof‑of‑concepts embedded directly with business teams - moving from requirements to working demonstration with astonishing speed, using technologies such as TypeScript/Node.js/AWS to create solutions users can touch and test immediately in their actual working environment.
• Push technical boundaries through continuous experimentation with emerging AI capabilities - you're always testing new models, techniques, and agentic approaches, determining what's hype versus what unlocks genuine business value before the competition recognizes the opportunity.
• Partner closely with the Product Owner - AI to translate validated opportunities into technical reality, turning business requirements into elegant architecture whilst ensuring rapid prototypes can evolve into production systems that scale.
• Engineer sophisticated solutions using modern AI platforms and APIs - building agentic systems, implementing RAG architectures, and creating multi‑step workflows that leverage OpenAI, Anthropic, and emerging providers to deliver capabilities impossible six months ago.
• Enable business success by making AI accessible - creating APIs, integration patterns, and developer experiences that allow other teams to leverage your AI capabilities without needing your deep expertise, multiplying impact across the organization.

Strategic Contributions

• Establish AI-native engineering practices that accelerate the entire organization - demonstrating how tools like Claude Code transform development velocity, creating reusable agentic patterns, and building technical capability that didn't exist before.
• Design and implement lightweight technical standards for responsible and ethical AI deployment - defining pragmatic guardrails that protect quality without killing velocity, establishing evaluation frameworks that enable rapid iteration with appropriate risk management.
• Build a library of proven technical patterns and reusable components - creating the building blocks that turn weeks of custom development into days of configuration, accelerating every subsequent AI implementation across the portfolio.
• Lead through demonstration rather than documentation - shipping working examples that other engineers can learn from, running technical deep‑dives that elevate team capability, and establishing engineering culture through visible excellence.
• Stay connected to the bleeding edge of AI engineering - actively participating in technical communities, experimenting with research releases, and maintaining relationships with AI platform providers that give PA Media Group early access to emerging capabilities.
• Contribute to wider PA Media Group technology approaches and capabilities to drive forward mutual progress and success.

Qualifications

• Senior‑level engineering expertise in TypeScript/Node.js with proven ability to architect and ship production systems in AWS cloud environments.
• AI-native engineering fluency that goes far beyond API consumption - you already use Claude Code or similar tools to accelerate your own development, build agentic systems that chain multiple capabilities, and understand prompt engineering, context management, and model behaviour at a sophisticated level.
• Solid understanding of ML/AI fundamentals - you grasp concepts like embedding spaces, attention mechanisms, RAG architectures, and fine‑tuning well enough to choose appropriate approaches without implementing models from scratch.
• High energy and relentless curiosity that drives continuous experimentation - you experiment with new models the day they're released, and you constantly ask "how might we?" when encountering novel business problems and technology.
• Comfort operating at extreme velocity in ambiguous environments - you thrive when requirements evolve hourly, make confident decisions with incomplete information, and know intuitively when to optimise for learning versus building for scale.
• Strong stakeholder collaboration skills that enable effective forward deployment - you gather requirements from non‑technical users naturally, explain technical trade‑offs without condescension, and build trust through delivering working solutions that exceed expectations.
• Senior-level judgement about when to push boundaries versus when to leverage proven patterns – you experiment aggressively but ship responsibly, understanding the difference between impressive demos and production‑ready systems.
• Experience working in media, content, or data‑intensive domains where you've encountered challenges of scale, quality assurance, and maintaining trust at speed.
• Deep understanding of modern cloud infrastructure (AWS, Azure, GCP) and deployment patterns including containerisation, serverless architectures, and infrastructure as code.
• Background in ML engineering or data science that provides intuition for model behaviour, training dynamics, and evaluation methodologies beyond surface‑level API usage.
• Experience with observability and monitoring tooling that enables rapid debugging of complex agentic systems where behaviour emerges from multiple AI components interacting.
• Familiarity with data pipeline architectures and integration patterns that enable sophisticated AI applications built on top of existing data infrastructure.
• Active participation in AI engineering communities - contributing to open‑source projects, sharing learnings publicly, or maintaining technical blog or social presence that demonstrates thought leadership.

Working Arrangement

This role requires 10 days per month in our London or Yorkshire offices to maintain close collaboration with business teams you’re embedded with, conduct rapid user testing sessions, and build the relationships essential for understanding real business problems worth solving. The nature of forward deployment means being physically present with the teams you’re enabling - this role thrives on face‑to‑face collaboration, rapid user testing, and the spontaneous problem‑solving that happens when engineers and business teams work side‑by‑side.