Senior AI Data Scientist – Agentic Process Development
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Job Description
Senior AI Data Scientist building trustworthy agentic systems to automate team.blue’s multi-country HR processes. Developing production integrations, safeguards, evaluations, and cost-efficient LLM workflows.
Responsibilities:
- Map HR processes end to end across multiple countries and quantify FTE cost per step
- Facilitate workshops with Talent, Rewards, and HR Ops leaders to score automation candidates
- Extract requirements from senior non-technical stakeholders
- Design state transitions, triggers, branches, system calls, waits, escalations, and failure handling
- Build guardrails including dry-run mode, approval gates, least-privilege credentials, and rollback paths
- Decide where humans remain in the loop and establish confidence thresholds and usable review queues
- Create evaluations for task completion, hallucination, and gendered or culturally biased language
- Build webhook-based, idempotent agent integrations
- Optimize model selection and routing based on cost and latency
- Evaluate HR-tech vendors and their APIs, data models, extensibility, and integration costs
- Learn HR-tech systems, HR-data governance, employment-law constraints, EU AI Act obligations, and organizational change management
Requirements:
- 7+ years building data and ML systems in industry
- Experience spanning both sides of the LLM shift
- Experience shipping systems with permission to take irreversible actions affecting real customers
- Expert in Python and ML
- End-to-end production ownership, including readable Python, containerisation, and instrumentation
- Current toolchain experience such as uv, Docker, or equivalent
- Production experience with multi-step, tool-calling LLM workflows, including orchestration, retries, idempotency, timeouts, and partial-failure recovery
- State-machine design experience
- Cost and latency engineering, including model routing, caching, and batching
- Safety practices including staging modes, approval gates, least-privilege scoping, and rollback
- Evaluation design for generative and agentic output, including LLM-as-judge, golden-transcript regression suites, and red-teaming
- Applied statistics
- Process mapping and quantification
- Ability to facilitate workshops with senior non-technical stakeholders
- Executive-grade written business cases and cost modelling for Finance audiences
- Technical vendor evaluation covering API surface, data model, extensibility, and integration cost
- Proof of eligibility to work in the country applied for
- Nice to have: Master's or PhD in Computer Science, AI, Machine Learning, or a related field
- Nice to have: Existing EU AI Act / high-risk-AI-system familiarity
- Nice to have: PromptOps at scale
- Nice to have: DataOps/MLOps practice
- Nice to have: Prior exposure to HRIS/HR-tech or automation in an audited or regulated domain
- Relocation packages and visa sponsorship are not supported
Benefits:
- Diversity & Inclusion commitment
- Respectful, open, and trusted collaboration culture
- ESG and sustainability initiatives
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