Technical Lead and Data Science

该职位来源于猎聘 Role Summary The Senior AI Technical Lead is a senior, hands-on technical leader responsible for designing, building, deploying, and operating production-grade Artificial Intelligence (AI) and Generative AI (GenAI) solutions for internal MANN+HUMMEL customers across divisions and central functions. This role is an immediate contributor who sets technical direction through reference architectures, reusable components, and engineering standards, while mentoring junior and mid-level developers within the Global Data Analytics team. Key Responsibilities

• End-to-end delivery: Own AI/GenAI solutions from problem framing through production deployment and operational readiness.
• Python engineering: Build robust services, APIs, and automation in Python with strong testing and maintainability practices.
• Multi-cloud solutions: Architect and implement solutions across AWS, Microsoft Azure, Google Cloud Platform (GCP); familiarity with Alibaba Cloud (Alicloud) is a plus.
• Infrastructure as Code (IaC): Implement and maintain IaC using Terraform and/or cloud-native equivalents.
• CI/CD: Build and maintain CI/CD pipelines using Bitbucket and/or GitHub (e.g., GitHub Actions), including automated testing, security checks, and environment promotion.
• Traditional AI/ML: Deliver machine learning, neural networks, recommendation engines, time series forecasting, and statistical analysis solutions; define evaluation and monitoring.
• GenAI/LLM solutions: Implement LLM-based solutions including prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling, structured outputs, and safety controls (grounding, access control, sensitive data handling).
• Data engineering & platforms: Build data pipelines and integrate with Snowflake and/or Databricks; ensure data quality, observability, and performance.
• Agentic orchestration: Apply MCP (Model Context Protocol) and A2A (Agent-to-Agent) patterns for agent coordination, orchestration, guardrails, and auditability.
• Mentorship & standards: Mentor junior/mid-level developers via pairing, code/design reviews, and coaching; establish “golden paths,” templates, and reference implementations. Required Qualifications
• 10+ years in software engineering, data engineering, ML engineering, or applied AI with ownership of production systems.
• Expert-level Python development (architecture, testing, packaging, performance).
• Strong experience delivering cloud solutions on AWS/Azure/GCP; multi-cloud mindset. Alicloud is a plus.
• Hands-on IaC experience (Terraform preferred) and CI/CD using Bitbucket and/or GitHub.
• Deep applied knowledge of ML and data science methods (modeling, evaluation, statistics, time series, recommendations).
• Demonstrated GenAI delivery experience with LLMs (RAG, tool use, evaluation, safety controls).
• Experience building data pipelines and working with Snowflake and/or Databricks.
• Working knowledge of MCP and A2A for agentic coordination/orchestration. Preferred Qualifications
• Containers/orchestration (Docker, Kubernetes), API management patterns.
• Vector search / embeddings / vector databases (technology-agnostic).
• Enterprise security patterns (least privilege, secrets management, audit logging).
• Experience working with globally distributed teams. Success Measures
• Production deployments delivered with measurable internal impact (time saved, quality improvements, cost reduction).
• Stable operations: monitoring, alerting, incident readiness, and cost controls in place.
• Reusable components and reference architectures adopted by the team.
• Improved team capability through mentorship and consistent engineering practices. Internal Stakeholders / Interfaces
• Global Data Analytics (data engineering, analytics engineering, data science)
• IT security, enterprise architecture, cloud/platform teams
• Internal business customers across divisions and central functions