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About the Role
We are seeking a Senior AI Data Scientist to build agentic systems that streamline HR processes, including recruitment, onboarding, performance, rewards, and offboarding, across multiple countries. This role focuses on creating robust, cost-effective, and trustworthy autonomous systems rather than predictive models, with a strong emphasis on end-to-end ownership from development to production.
Responsibilities
- Map HR processes and quantify their costs in headcount.
- Build proof-of-concept agentic systems and take them to production.
- Design systems capable of revoking IT access, issuing signed contracts, and flagging pay outliers.
- Map the offboarding process across countries and attach FTE costs per step.
- Facilitate sessions with HR leads to score automation candidates on impact, feasibility, and tool fit.
- Extract requirements from non-technical stakeholders.
- Design state transitions, triggers, branches, system calls, and escalation paths.
- Build guardrails such as dry-run modes, approval gates, least-privilege credentials, and rollback paths.
- Determine human-in-the-loop placement based on confidence thresholds and design review queues.
- Write evaluations for generative and agentic output, including task-completion rate and bias detection.
- Wire agents to webhooks for real-time processing and ensure idempotency.
- Decide on appropriate models (frontier vs. cheap) for different flow steps and prove the decision with data.
- Evaluate technical vendors based on API surface, data model, extensibility, and integration cost.
- Learn HR domain knowledge, including HR-tech systems, data governance, and multi-country employment law constraints.
- Understand and apply EU AI Act obligations for high-risk systems.
- Contribute to organizational design and change management, defining human/agent interaction lines.
Requirements
- 7+ years of experience building data and ML systems, including experience on both sides of the LLM shift.
- Proven experience shipping systems that have permission to take irreversible actions affecting real customers.
- Expertise in Python and ML.
- Experience shipping end-to-end solutions, including readable Python code, current toolchains (uv, Docker), containerization, and instrumentation.
- Production experience with multi-step, tool-calling LLM workflows, including orchestration, retries, idempotency, timeouts, and partial-failure recovery.
- Experience with state-machine design beyond traditional train/serve pipelines.
- Experience with cost and latency engineering as a first-class concern, including model routing, caching, and batching.
- Experience implementing safety measures for action-taking systems, such as staging modes, approval gates, least-privilege scoping, and rollback.
- Experience with evaluation design for generative and agentic output, including LLM-as-judge, golden-transcript regression suites, and red-teaming.
- Applied statistics knowledge to adjudicate trustworthiness of numbers and underlying assumptions.
- Ability to perform process mapping and quantification, capturing actual processes and attaching numerical values.
- Facilitation skills to run workshops with senior non-technical stakeholders and gather requirements.
- Ability to write executive-grade written business cases, including cost modeling and framing for a Finance audience.
- Technical vendor evaluation skills, assessing HR-tech vendors on technical merits rather than sales pitches.
- Ability to debug systems without relying solely on LLM assistance.
- Understanding of deterministic operations over 'LLM does everything' patterns.
- Willingness to own systems when they break.
Skills
- Python
- Machine Learning
- LLM workflows
- Orchestration
- Retries
- Idempotency
- Timeouts
- Partial-failure recovery
- State-machine design
- Cost engineering
- Latency engineering
- Model routing
- Caching
- Batching
- System safety implementation
- Evaluation design for generative and agentic output
- LLM-as-judge
- Golden-transcript regression suites
- Red-teaming
- Applied statistics
- Process mapping
- Process quantification
- Workshop facilitation
- Business case writing
- Cost modeling
- Technical vendor evaluation
- Containerization
- Instrumentation
- PromptOps at scale (nice to have)
- DataOps/MLOps (nice to have)
Location
- 25+ countries
Work Type
- Full-time
Experience Level
- Senior
- 7+ years building data and ML systems
Education Level
- Master's or PhD in Computer Science, AI, Machine Learning or a related field (nice to have)
About the Company
- team.blue is the market leader in enabling digital success for small and medium-sized businesses (SMBs) across Europe.
- Caters to over 3 million customers in 25+ languages.
- Mission: To make online business success simpler by providing customers with the tools and resources they need to excel online.
- Commitment to caring for the environment and each other.
- Ongoing ESG efforts and ambitious sustainability goals.
Equal Opportunity
- Everyone is welcome here.
- Diversity & Inclusion are at our core.
- Value respect, openness, and trusted collaboration.
- Do not tolerate intolerance.