16 set - Milano
Jobtailor
Own the target architecture and decide what to rebuild, retire, or scale
Review and support AI Agents work across code review, test definition, and other SDLC tasks
Build and run the team's AI layer for code generation, data and schema work, testing, documentation, and self-healing operations
Lead technical design, refinement, development, and testing for a 2–3 person squad
Run 1:1s, set objectives, give feedback, and drive senior engineers' career growth
Align peers, product, and stakeholders across tribes on goals, dependencies, and trade-offs
Represent the area in cross-R&D; initiatives and lead relevant initiatives
Replace manual, repetitive engineering work with agentic solutions
Treat the area as a product with documented interfaces, self-serve tooling, sandbox, and automated certification
Remove impediments and provide insights supported by Agile/Lean metrics
Requirements
Expert-level command of API design (REST/GraphQL), event-driven architecture, data pipelines, and cloud-native engineering on AWS
Proven,
hands-on application of AI/LLMs and agentic workflows to real production engineering problems, including designing guardrails, evaluation, and review processes
Strong reliability and observability practice in high-volume, multi-tenant B2B SaaS
Proven people management of a small senior team while still contributing technically
Effective stakeholder communication
Ability to lead cross-tribe initiatives and align others
Ability to identify risks, analyze issues, triage quickly, distinguish signal from noise, and make independent decisions
Coaching and enabling people without compromising execution and quality
Core Competencies
Demonstrates expert-level command of API Design, Event-Driven Architecture, and Cloud-Native Engineering on AWS, while effectively managing a small senior team and leading cross-tribe initiatives. Proficient in applying AI/LLMs to production engineering challenges and ensuring reliability and observability in high-volume B2B SaaS enviro
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