AI Engineering Lead
New
E
EggAIAgentic AI
Remote (EU only). We only accept candidates located in the EU.Full-TimeLead
Salary not disclosed
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Job Details
- Required Skills
- PythonJavascriptTypeScript
Requirements
- Demonstrated technical leadership that generated business impact, including experience leading small engineering teams.
- Experience designing, shipping, and operating production-grade AI systems.
- Practical judgment across AI architecture, context, tools, evaluation, observability, production controls, reliability, and cost.
- Advanced use of agentic AI in day-to-day work and the ability to test meaningful advances and adapt working methods.
- Experience owning difficult stakeholder environments and connecting technical decisions to business value, user needs, risk, and organizational change.
- Strong coding skills and ability to write and review production-grade code in Python, TypeScript/JavaScript, or similar.
- Strong engineering foundations and first-principles judgment about established practices and their implementation in AI-native systems.
- Strong statistical and experimental judgment, including creating instrumentation, annotation, review, and feedback loops for improving systems.
- Experience operating AI systems in security-sensitive or regulated environments is an additional strength.
- Experience creating AI tooling, evaluation infrastructure, data assets, or engineering platforms for multiple projects is an additional strength.
- A track record of hiring, onboarding, and developing engineering talent is an additional strength.
- Meaningful open-source work, public technical contributions, or active participation in the AI-engineering community is an additional strength.
Responsibilities
- Validate business opportunities against AI capabilities and constraints, and identify new opportunities.
- Own solution design and system architecture across agents, tools, data, evaluations, controls, human oversight, and deterministic boundaries.
- Implement critical agents, integrations, evaluation infrastructure, permissions, observability, controls, and feedback loops.
- Lead the team and client through implementation and adoption, owning engineering quality and production readiness.
- Establish a clear delivery rhythm and engineering accountability across the project team.
- Package successful work as tools, datasets, evaluations, patterns, and engineering methods.
- Write and review production code, set technical direction, and develop engineers through example, review, feedback, and coaching.
- Guide senior client stakeholders through difficult decisions.
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