Software Developer - Artificial Intelligence
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Summary
Oxford Economics is hiring an early-career software engineer with a strong AI interest for its London AI engineering team, building agents, RAG pipelines, conversational tools, and internal/client-facing AI features. Day to day is hands-on C#/TypeScript development on Azure, taking LLM-powered ideas from prototype to production.
Oxford Economics, a leading economic forecasting and consulting firm, is looking for an ambitious, passionate Software Engineer with a strong interest in AI to join our Technology team and help us build, ship and scale the next generation of AI-enabled capabilities at Oxford Economics.
Mission (Why this role exists)
Mission (Why this role exists)
AI is changing how research-led businesses like ours work, and we're building the team and the capabilities to stay ahead of it. We're growing our dedicated AI engineering team whose job is to design, build, and ship the next generation of AI-enabled capabilities at Oxford Economics: agents, retrieval pipelines, conversational tools, internal platforms, and client-facing features that people use every day.
This is a hands-on role for an engineer early in their career who writes great software and is genuinely excited about where AI is going. You'll spend your time building alongside the rest of the AI team, turning promising ideas into working software and learning fast as the technology moves. Part of the team's remit is partnering closely with our Content, Data, and Models teams, and over time you'll grow into embedding with them directly to understand their work and find where AI can make a real difference.
You'll work with engineers, economists, product owners, and stakeholders across the business, and we'll back you to develop quickly into a trusted expert in building with AI.
You'll spend most of your time building within the AI team, with the balance of your work shifting as you grow. Day to day you will:
Build
Build
- Design, build, and ship production software that brings AI capabilities to OE: agents, RAG pipelines, conversational interfaces, internal tools, and other client-facing features.
- Take ideas from prototype to production, contributing across the software lifecycle: discovery, design, coding, testing, CI/CD, observability, cost monitoring, and safe rollout.
- Help build and operate the services, agents, MCPs, shared libraries, Claude skills, and evaluation harnesses that make up OE's AI platform.
- Apply solid engineering fundamentals: clean code, testing, modularity, performance, security. Because quality and reliability matter as much in AI systems as anywhere else.
Collaborate & partner
- Work with product owners and the rest of the team to turn business needs into tangible, well-scoped deliverables, adapting as those needs evolve.
- Partner with our Content, Data and Models teams to understand what they need, growing into embedding alongside them directly as you build context and credibility.
- Build with safety and responsible use in mind. Sensible data handling, prompt-injection defences, and alignment with ISO 27001 controls and OE's AI Acceptable Use Policy.
Learn & share
- Experiment with new models, frameworks, and techniques, and help the team form an evidence-based view of what's hype and what's worth betting on.
- Share what you learn: patterns, write-ups, brown-bag sessions; helping colleagues across OE raise their own AI fluency as you grow into it.
We care more about trajectory than a tick-box list. For the AI-specific parts especially, real curiosity and hands-on tinkering count for as much as years of experience. If you've explored these things, have views on them and want to go deeper, that's what we're looking for.
Core engineering
- Around 2+ years of professional experience shipping production software in a modern cloud environment.
- Solid engineering fundamentals: testing, version control, code review, modular design, and a developing sense of when to be pragmatic versus principled.
- Proficiency in C# and experience with TypeScript, comfortable working from APIs through to lightweight user interfaces.
- Some hands-on experience with cloud services (e.g. Azure) and modern delivery practices such as CI/CD.
Building with AI
- You've built things with LLMs, even side projects or prototypes, and understand concepts like prompting, tool calling, embeddings, and RAG.
- You've integrated a model API (e.g. OpenAI) and have at least a working feel for cost, latency, context windows, and rate limits.
- An awareness of how building and evaluating LLM systems differs from traditional software, and an interest in getting good at it.
- Familiarity with, or genuine curiosity about, vector databases, embeddings, and retrieval techniques such as semantic and hybrid search.
How you work
- Genuine curiosity and a tinkerer's instinct. You build with AI because you find it interesting, not just because it's the job.
- A bias for shipping: you'd rather get something working in front of people than polish it indefinitely.
- Valuing good engineering practices: fast feedback, testing, and simple design; and wanting to get better at them. You might already follow the people who champion XP-style ways of working; if you don't have deep experience with them yet, the enthusiasm to learn matters more.
- You pick things up fast across unfamiliar domains and can build enough understanding of someone else's problem to be useful.
- You communicate clearly and can explain trade-offs to engineers and non-engineers alike.
Bonus points
- Experience using agentic coding tools (e.g. Claude Code, GitHub Copilot, Codex) to ship real software.
- Hands-on time with MCP, agent frameworks (e.g. Microsoft Agent Framework, LangChain) or your own orchestration.
- Experience with content, publishing, or knowledge-management workflows (CMS integrations, editorial tooling, document processing).
- Exposure to modern data platforms (e.g. Snowflake, ClickHouse, Databricks, BigQuery) or working with data engineering teams.
- A background or coursework in machine learning, NLP, or data science.
- Open-source contributions, side projects, or writing that show you build for the love of it.
- An interest in economics, forecasting, financial services, or research-led businesses.
- A degree in Computer Science, Mathematics, Statistics, or equivalent practical experience.
What success looks like
We don't expect you to arrive doing all of this. Here's the trajectory we'd hope to see:
In your first 3 months
- You're set up and contributing. Your first pieces of AI-enabled software have shipped and are in proper use, with support from the team.
- You understand how OE's AI platform fits together and where your work sits within it.
By 6 months
- You're shipping regularly and driving features forward. Taking the lead in pairing and mobbing sessions, increasingly steering ideas rather than waiting for direction.
- You're a dependable contributor to the team's core work and are starting to support other teams with AI.
By 12 months
- You're putting AI to work in product discovery, building rapid prototypes that test ideas quickly and spark new ones.
- Working software you've built is landing regularly and being used across OE and by our clients, with a short, safe path from prototype to production.
- You've embedded with a team to understand their work and find where AI genuinely helps them, and people come to you for an honest, well-informed answer to "should we do this with AI?"
Key working relationships
Internal: The AI team, Software Engineers, Product Owners, Economists / Consulting and Content teams, IT Operations, Business Development / Marketing.
External: Frontier model providers (OpenAI, Anthropic), cloud providers (Azure), AI tooling and SaaS vendors.
Here are some of the benefits we offer in the UK to ensure you feel valued, supported, and thrive at work:
- Private Healthcare
- Employee Assistance Program
- Enhanced Maternity and Paternity Leave
- Workplace Nursery Scheme
- Cycle to Work Scheme
Oxford Economics is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, colour, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by the law.
Skills
- Agentic AI
- AI
- Anthropic
- API
- Azure
- BigQuery
- Business Development
- CI/CD
- Claude Code
- ClickHouse
- Cloud
- C#
- Data Engineering
- Data Science
- Databricks
- Embeddings
- GitHub
- Github Copilot
- ISO 27001
- LangChain
- LLM
- Machine Learning
- MCP
- NLP
- Observability
- OpenAI
- SaaS
- Snowflake
- Spark
- Statistics
- TypeScript
- Vector Databases
- Version Control