Job Description

Collinson is a global loyalty and benefits company.

We use our expertise and products to craft customer experiences which enable some of the world’s best-known brands to acquire, engage and retain the most demanding and choice-rich customers. In particular, our unique expertise and insight into high earning, frequent travellers allow us to create products and solutions for our clients that inspire greater customer engagement to drive more profitable relationships, enrich their travel experiences, protect what matters and assist in in times of need.

While specializing in Financial Services, Travel and Retail, we also support clients in multiple sectors. We have worked with over 90 airlines, 20 hotel groups and more than 600 financial institutions and banks, with clients including Accor Hotels, Air France KLM, American Express, British Airways, Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel Group, Sephora, Visa and Vhi.

We take our 30 years’ experience working with these kinds of household names in over 170 countries and help our clients to deliver the smarter experiences it takes to differentiate their propositions and help them win deeper devotion with their customers.

Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world’s best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand’s reward programmes and loyalty initiatives.

Purpose of the job

We're looking for an AI Platform Engineer, someone who believes the ability to work effectively with AI should belong to every team, not just a handful of specialists.

This role is pivotal to how Collinson adopts and scales AI across our engineering teams. You'll build the platform, tooling, and practices that let teams deploy AI capabilities safely and effectively, laying the foundations for how we work with AI as an organization, focusing on integrating AI within our Software Developer Lifecycle (SDLC).

We're early in our AI journey, so you'll operate with a degree of autonomy and ambiguity, working consultatively with teams to understand what they need and helping them get there. You'll be hands-on, educating, and surfacing the risks and opportunities that leadership needs to make the bigger calls.

Key Responsibilities

· Educate and partner with engineering teams on working effectively with AI, establishing the patterns and best practices that help them adopt new capabilities safely.

· Integrate AI across the software development lifecycle, embedding it into IDEs, code review, test generation, CI/CD pipelines, and documentation workflows, and connecting the tools used within our environment including Jira, Confluence, and GitHub.

· Build the platform layer that enables teams to safely deploy and run agents.

· Develop orchestration tooling that coordinates multi-agent workflows, manages state, and routes work across agents.

· Create and maintain MCP servers, command line tools and prompt libraries that teams can safely build on.

· Own the operational health, safety, and cost efficiency of AI systems in production.

· Instrument AI systems for end-to-end observability in Datadog, capturing traces, token usage, latency, and cost at the span level so teams can see how agents and prompts behave in production and act on regressions before they reach users.

· Build testing harnesses for non-deterministic systems that measure whether agent and prompt changes improve accuracy.

What You’ll Bring

We know that great engineers come from many different backgrounds. If you meet most of these requirements, we'd love to hear from you:

· Production AI operations experience. You've shipped and operated real LLM or agentic AI systems in production, with hands-on exposure to observability, cost control, monitoring, and the failure modes that surface with real users.

· Agentic system design. You understand multi-agent coordination, tool integration, and orchestration patterns (AWS Bedrock, AgentCore, or similar).

· Cloud infrastructure comfort. You're comfortable shipping and operating on cloud platforms, with AWS experience essential.

· Consultative problem-solving. You're at ease with fuzzy briefs, ask sharp questions, and help teams discover what they actually need rather than waiting for a spec.

· Hands-on engineering experience in TypeScript or Python, comfortable with Terraform, containers, Kubernetes, CI/CD, and API design, so you can build and operate production-grade platform tooling rather than just prototype it.

· Communication and teaching. You can explain complex AI concepts to engineers at any level and bring people along with you.

· Evaluation framework experience. You've designed rigorous testing and measurement approaches for non-deterministic AI systems.

Personal Attributes

· Someone who lifts the people around them and enjoys sharing what they know.

· A collaborator who values diverse opinions and voices.

· Confident in decision-making, even under pressure.

· Passionate about continuous improvement and engineering excellence.

· Committed to creating safe, inclusive spaces where every team member can thrive.