Jobgether
Staff AI Engineer, Payments Intelligence

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Job Description: Staff AI Engineer, Payments Intelligence
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer, Payments Intelligence based in the United Kingdom.
As a Staff AI Engineer, you’ll serve as a senior technical leader responsible for shaping the architecture and delivery of AI systems at the core of a global payments platform. You’ll design and build production-grade AI agents, LLM pipelines, and intelligence products that solve complex payment and operational challenges. Your work will span agentic AI, conversational experiences, data intelligence, automation, evaluation, and AI safety. You’ll operate in a highly technical, hands-on environment where reliability, scalability, latency, and responsible AI are critical. You’ll collaborate closely with Product, Data Science, and senior engineering teams while mentoring other engineers and setting technical direction. This is an opportunity to have significant influence over how AI-powered payment products are designed, evaluated, and deployed globally.
Accountabilities
- Lead the architecture and technical direction of AI agents and Payments Intelligence systems, including multi-step agents, tool use, orchestration, memory, and retrieval-augmented generation (RAG).
- Design, develop, and productionize LLM and agentic AI systems engineered for reliability, scalability, low latency, and high-quality outcomes.
- Build intelligent conversational experiences capable of engaging customers dynamically across channels such as phone and messaging platforms, including multilingual interactions across 70+ languages.
- Develop AI solutions that retrieve payment information, recover revenue from failed transactions, automate internal operations, support customers, and generate actionable merchant insights.
- Establish rigorous approaches to AI evaluation, observability, safety, and guardrails to ensure reliable behavior in a compliance-sensitive, multi-market environment.
- Architect data and intelligence products that transform complex payment data into actionable insights for merchants.
- Define responsible practices for using AI-assisted development tools throughout the design, evaluation, and deployment lifecycle.
- Collaborate with Product, Data Science, and senior engineering stakeholders to deliver complex, cross-functional AI initiatives.
- Mentor engineers, promote strong engineering standards, and raise the technical bar for AI development across the organization.
- Own technical outcomes from system architecture through production deployment, with a focus on measurable impact and continuous improvement.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- Extensive software engineering experience with a proven track record of building and shipping production LLM or AI-agent systems.
- Deep expertise in agentic AI systems, including multi-step agents, tool use, orchestration, memory, and RAG.
- Strong LLM application development skills, including prompt engineering, evaluation, testing, and safety guardrails.
- Advanced Python skills for AI/ML development, combined with strong backend engineering capabilities in Go and/or Kotlin.
- Experience with model serving, LLM inference, and cloud infrastructure for running AI workloads in production, ideally with AWS or a comparable platform.
- Hands-on experience with AI evaluation and observability platforms such as LangFuse, LangSmith, Braintrust, or MLflow.
- Strong knowledge of automated testing and CI/CD practices for reliable production systems.
- Proven technical leadership experience, including mentoring engineers, defining technical vision, and delivering complex cross-team projects.
- Advanced written and spoken English proficiency.
- Experience with fine-tuning, RLHF, or model customization is advantageous.
- Familiarity with vector databases such as Pinecone, Weaviate, or FAISS and embedding-based retrieval.
- Experience building agent workflows using MCP servers or modern agent frameworks.
- Knowledge of conversational AI, speech-to-text, text-to-speech, and multilingual AI systems is a plus.
- Previous experience in payments, fintech, or another highly regulated environment is preferred.
- Experience operating multi-tenant AI platforms or managing GPU and AI resources at scale is beneficial.
- Familiarity with data pipelines and orchestration tools such as Airflow or Prefect, and data warehouses such as Databricks, Snowflake, or BigQuery, is a plus.
- Spanish proficiency is considered an additional advantage.
- Strong ownership, curiosity, problem-solving ability, and a hands-on approach to technical leadership.


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Benefits
- Competitive compensation.
- Fully remote working environment with the flexibility to work from anywhere.
- One-time home office allowance to help you create an effective workspace.
- Work equipment provided.
- Stock options.
- Health plan available wherever you are.
- Flexible days off.
- Language, professional, and personal development courses.
- Opportunity to work on advanced AI and agentic systems operating at significant production scale.
- International and distributed environment with collaboration across multiple markets and technical disciplines.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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