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Data Scientist – AI Engineer
Takeaway.com. Build and improve production, user-facing AI agent components, including prompts, workflows, tool use, and handover to humans .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and shipping user-facing AI agents, with strong capabilities in Python and SQL for data analysis and agent observability. Proficient in developing evaluation datasets, defining metrics, and implementing monitoring solutions to enhance agent performance and reliability.
Highest-signal resume keywords
User-Facing AI Agent DevelopmentPython ProgrammingSQL Data AnalysisAgent Evaluation and MonitoringDashboard and Alert Building
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLAgent FrameworksData VisualizationExperiment DesignRegression TestingQuality MetricsUnit TestingVersion ControlCI/CD
Soft Skills
Clear CommunicationIndependent Problem Solving
Tools & Technologies
Google ADKLangGraphDockerKubernetes
Industry Keywords
AI AgentsAgent Evaluation DatasetsObservabilityMulti-Agent DesignsProduction Systems
Tech Stack
Tools & technologiesDockerKubernetesPythonSQL
About the role
Key responsibilities & impact- Build and improve production, user-facing AI agent components, including prompts, workflows, tool use, and handover to humans
- Translate operational requirements into reliable and testable agent behaviour
- Build and maintain agent evaluation suites using real-conversation and scenario datasets, LLM-as-a-judge, deterministic metrics, and end-to-end tests
- Run offline experiments comparing models, prompts, and agent designs, and make ship/don't-ship recommendations
- Help advance automated and well-grounded online evaluation
- Instrument agents with tracing, structured logging, and quality metrics
- Build and maintain dashboards and alerts for quality, latency, cost, and failure modes
- Analyse production traces and historical conversations to identify regressions and improvement opportunities
- Ship agent changes safely using well-tested Python, code review, and version control while following production, privacy, and security rules
- Use SQL and Python to analyse conversation and operational data and track quality and business metrics
- Quantify the impact of agent changes and communicate actionable recommendations using data visualisation
- Collaborate with Backend Engineers, Operations, Product, and Data Scientists
- Contribute to the internal community building user-facing agents at Just Eat Takeaway.com
- Improve evaluation, testing, and release workflows through automation
Requirements
What you’ll need- Hands-on experience building and shipping user-facing AI agents in production
- Practical experience building agent evaluation datasets, defining metrics, using LLM-as-a-judge, regression testing agents, and running offline and online experiments
- Practical experience with agent observability and monitoring, including tracing and debugging multi-step agent runs, defining quality, cost, and latency signals, and building dashboards and alerts for LLM systems in production
- Experience with agent frameworks such as Google ADK, LangGraph, or similar
- Experience with tool use / MCP and multi-step or multi-agent designs
- Strong Python and SQL skills
- Good software engineering habits, including typing, linting, unit tests, Git, CI/CD, and code review
- Solid data science foundation, including statistics and experiment design
- Ability to reason about whether an observed change is a real improvement
- Comfortable working independently on well-defined problems
- Ability to communicate results clearly to technical and non-technical stakeholders
- Nice to have: experience with feature flags and staged rollouts
- Nice to have: experience with containerised deployments using Docker/Kubernetes
Benefits
Comp & perks- Hybrid work arrangement: 3 days a week from the office and 2 days working from home
- Inclusive culture focused on diversity, belonging, and employee support
- Fun, fast-paced, and supportive work environment
- Opportunities to contribute to an internal community of people building user-facing agents
- Growth and development opportunities