AI Engineer

The Role

• The Fastmarkets Innovation & AI team sits within the Technology function and is responsible for developing and delivering the company’s AI and data strategy through agentic AI systems, intelligent data applications, and AI-powered analytics. The team has built a modern data platform and is actively shipping AI capabilities across the business—from agentic request intake systems to natural language data exploration tools powered by LLMs and semantic models.

  Reporting directly into the Head of AI Enablement, we are looking for an AI Engineer to design, build, and ship AI-powered applications and features. This is a fantastic opportunity to join us and contribute to a high-performing workstream delivering transformational AI capabilities across both internal tools and monetizable data assets. You will work with cutting-edge AI technologies—Anthropic Claude, Snowflake Cortex AI, semantic models, and agentic frameworks—to build systems that enable users to interact with data and insights in entirely new ways.

  The AI Engineer will take responsibility for the full lifecycle of AI features: from designing agents and LLM-powered workflows, to connecting them to data via pipelines and semantic models, to shipping polished user-facing applications. You will ensure that AI systems are reliable, observable, and deliver measurable business value.

  We actively leverage AI tools across the engineering workflow, including Anthropic Claude for code generation, design, and review, and Snowflake Cortex AI capabilities for in-platform intelligence. The successful candidate will be expected to embrace AI-assisted development as a core part of how we work.

  The role requires a high standard of expertise in Python and TypeScript/JavaScript, as well as specialist knowledge of LLMs, prompt engineering, agentic systems, and semantic data modelling. You should be comfortable working across the full stack—from designing LLM-powered backends to building modern React frontends.

Principal Accountabilities

· Design and develop agentic AI systems that solve real business problems—request intake agents, natural language query systems, intelligent data exploration tools, and AI-powered search and analysis features

· Integrate LLMs into applications using best practices: prompt engineering, tool use, multi-turn conversation management, output validation, and cost optimisation

· Build semantic models and data schemas that enable natural language querying over enterprise data (Snowflake Cortex Analyst, custom RAG systems)

· Connect AI systems to data pipelines: design how data flows from source → transformation → semantic layer → AI application, ensuring freshness, quality, and lineage are observable

· Develop full-stack AI applications: Next.js frontends with streaming chat UIs, FastAPI/Python backends for agentic workflows, and server-side integration with LLMs and data platforms

· Implement observability and evaluation frameworks for AI systems—structured logging, conversation tracing, golden evals, and adversarial verification of agent behaviour

· Work with modern orchestration and deployment patterns: containerised on-demand environments, Snowflake SPCS, CI/CD pipelines, and infrastructure-as-code

· Write production-grade Python and TypeScript: follow code-first practices, maintain strict type safety, build testable systems with clear separation of concerns

· Embrace AI-assisted development: use Claude for code generation, architecture design, and code review to accelerate delivery without compromising quality

· Identify and promote best practices in AI engineering: recommend improvements to prompting strategies, evaluation methodology, data schema design, and system reliability

· Excellent problem-solving skills and ability to embrace change—AI is a rapidly evolving field; you should be curious, experimental, and comfortable with ambiguity

· Effective communication and collaboration skills: you’ll work cross-functionally with data engineers, product teams, and business stakeholders to translate requirements into shipped AI features

· Natural self-starter, with enthusiasm for learning and research: staying current with the latest in LLMs, prompt engineering, and agentic systems is essential

KEY INTERFACES

Internal:

· Head of AI Enablement

· Data Engineering team (for data pipeline and schema design)

· Technology & Infrastructure teams

· Product and Commercial teams

· BI & Analytics teams & stakeholders across the business

External:

· Anthropic technical partnerships team

· Snowflake technical account team

· Cloud platform providers (Azure, AWS, Snowflake)

· Third-party vendor and tooling support

We recruit talented, dynamic people with diverse backgrounds and experiences, all united by a belief in our mission to provide the world’s leading and most trusted price reporting, events, and intelligence service for the markets we serve. We’re proud to be an equal opportunities employer and are committed to creating a fully inclusive workplace, where everyone feels able to participate and contribute meaningfully.

If you are open-minded, curious, resilient, solutions-oriented and committed to promoting equality, then read on.

KNOWLEDGE, EXPERIENCE AND SKILLS

We are looking for an individual who is highly motivated, driven, and have a passion to be part of a fast-paced, successful team. Being a strong team player is also important as well as someone who is happy to work flexibly.

Essential

· Advanced Python expertise – async/await, dependency injection, structured logging, testing patterns, Python type hints (Pydantic v2). Experience building production API services (FastAPI, Django, Flask).

· TypeScript / JavaScript expertise – React 18+, Next.js (App Router, Server Components), async state management, type-safe API clients. Comfortable with modern frontend patterns and server-driven rendering.

· LLM and prompt engineering knowledge – multi-turn conversation design, tool use and function calling, prompt optimisation, output parsing and validation, cost and latency considerations, understanding of model capabilities and limitations.

· Familiarity with agentic AI frameworks – experience building or working with agents, ReAct patterns, tool-calling loops, planning and reasoning, constraint satisfaction. Can implement agent loops from scratch using the Anthropic SDK.

· Snowflake expertise – SQL (CTEs, stored procedures, query tuning), Snowflake-specific features (Snowpark for Python transformations, zero-copy cloning, containerised compute). Knowledge of Cortex AI capabilities (Cortex Analyst, embeddings, vector search) is highly desirable.

· Semantic data modelling – designing data schemas and semantic layers that enable natural language queries. Understanding of fact tables, dimensions, metrics, and how LLMs reason over structured data. Familiarity with Cortex Analyst YAML or similar semantic modelling approaches.

· API integration and data transformation – working with REST/GraphQL APIs, JSON/Protocol Buffer parsing, data validation, designing robust connectors that handle edge cases and errors gracefully.

· Git version control – branching strategies, pull requests, merge conflict resolution, atomic commits, clear commit messages.

· CI/CD principles and experience – GitHub Actions, test automation, deployment pipelines, infrastructure-as-code mindset.

· Cloud services experience – Azure, AWS, or GCP. Ability to identify and configure suitable cloud services and resources.

· Solid understanding of data modelling approaches – fact tables, dimensions, normalisation, and denormalisation tradeoffs. How to structure data to serve both analytics and AI use cases.

· Excellent analytical and problem-solving skills – you can diagnose why an agent is failing, why a semantic model isn’t returning the right results, or why a data pipeline isn’t fresh.

· Strong communication skills with attention to detail – you can explain AI system design decisions to non-technical stakeholders and write clear documentation.

Desirable

· Experience with Anthropic Claude and the Anthropic Python SDK – hands-on work building agentic systems or multi-turn applications.

· Snowflake Cortex Analyst experience – designing semantic models, writing YAML, iterating on metrics and dimensions for NL query accuracy.

· Semantic search and RAG – building retrieval-augmented generation systems, vector databases, embedding strategies, and hybrid search (lexical + semantic).

· Container orchestration and Kubernetes – deploying containerised services, understanding networking, resource management, scaling patterns.

· Infrastructure as Code – Terraform, Pulumi, or similar, defining cloud resources as code.

· Event streaming and real-time data – Apache Kafka, Azure Service Bus, or similar; designing systems that react to data changes in near-real-time.

· Evaluation frameworks for AI systems – golden datasets, adversarial testing, metric definition, A/B testing of prompts or models.

· Data quality and observability – implementing automated checks, monitoring, and alerting for both data pipelines and AI systems. Familiarity with tools like dbt, Great Expectations.

· Exposure to CRM systems (Salesforce) and marketing platforms (Marketo).

· Experience shipping full-stack AI applications – end-to-end responsibility from data → AI backend → user-facing frontend.

Formal Qualifications

· Degree in Computer Science, Engineering, Mathematics, or related technical field OR 3+ years’ professional experience building AI systems, data applications, or production ML systems

· Can demonstrate experience working on a project that delivered transformational change or exceptional business value – or a personal AI/data project that required significant research, learning, and execution (e.g. a bot, data analysis tool, RAG system, semantic search application)

· Certifications in Snowflake, cloud platforms, or LLM engineering are a nice-to-have but not required.

If you're excited about the role but your experience, skills or qualifications don't perfectly align, we encourage you to apply anyway.

Our Values

Fastmarkets people come from all different walks of life. It’s this mix of brilliant personalities, experiences and insights that gives us that warm, open, and friendly culture you can feel as soon as you meet us. But however wonderfully different we all are, there are six things we all have in common – and they form our Fastmarkets values.

Created by our own employees to reflect some of the personal traits that Fastmarkets people have, our values are key to what makes our culture unique. They reflect who each of us are and they're embedded in everything we do. Our values are:

• METRICS DRIVEN. We use insights to improve our customers’ experience and our business performance
• ACCOUNTABLE. We are accountable to ourselves and those we work with: we keep our promises and get things done
• GROWTH MINDSET. This value enables us to be nimble to the changing realities and operate with a sense of urgency
• INCLUSIVE. We are inclusive and respectful, celebrating each of us and giving everyone a deep sense of belonging with the desire to bring their best self to work every day.
• CUSTOMER CENTRIC. We are customer-centric in all that we do
• COLLABORATIVE. We are collaborative, able to work across teams and capitalise on the diversity of intellect, perspectives, and experiences.

We are committed to ensuring all candidates feel welcomed and supported. Should your application advance and you require accommodations for the interview process, please inform us so we can make the necessary arrangements.

Reward and benefits at Fastmarkets

We believe in fair pay and benefits that support you both inside and outside of work. Through Fastmarkets Rewards, you'll have access to a range of core benefits and a flexible allowance, giving you the freedom to tailor your package to suit your lifestyle, wellbeing and financial priorities. We know that everyone's needs are different, so we've designed our benefits to support our diverse global team wherever they're based.

Specific benefits may vary by country and role.

You’ve read a little about us – now it’s over to you!

If you like what you’ve read so far and think you can see yourself as a Fastmarkets person, it’s time to fill in your application form. This form is an important part of the selection process: it’s used to determine whether or not you’ll be chosen to have an interview and acts as a basis for the questions we’ll ask you on the day.

It’s vital that you try to capture all the relevant information we have asked for on the form so we can get a good feel for who you are and why you’re great.