2 months ago
Berlin, Germany +6 moreSenior
Responsibilities
- Define and improve guardrails and safe defaults for AI-powered systems.
- Shape privacy, PII-handling, provider-governance, and model-governance practices.
- Translate policy, risk, and governance requirements into reusable platform patterns and engineering controls.
- Define production-readiness expectations and contribute to readiness checks, automated validations, and scalable governance mechanisms.
- Improve logging, tracing, and observability so AI systems are auditable and safer to operate.
- Partner with Security, Legal, Architecture, and product engineering teams on practical standards.
- Document guidance and support teams in addressing AI-specific risks, including unsafe outputs, privacy exposure, provider misuse, and poor trace hygiene.
- Contribute to engineering practices through implementation, testing, collaboration, mentoring, and team maturity improvement.
Requirements
- Strong software engineering fundamentals and experience working on production systems.
- Practical experience in security, governance, privacy, compliance, or risk-related engineering work.
- Hands-on experience applying relevant controls to AI- or LLM-powered systems.
- Understanding of AI-specific risks, including privacy exposure, PII handling, unsafe outputs, provider/model risk, and misuse or abuse patterns.
- Experience translating policy or risk requirements into practical engineering controls, patterns, or defaults.
- Understanding of making AI systems observable, auditable, and safer to operate in production.
- Ability to collaborate with engineers, architects, Security, Legal, and other non-engineering stakeholders.
- Practical experience with Python and/or JavaScript/TypeScript.
- Experience across the lifecycle of a platform capability, from design and implementation through rollout and iteration.
- Understanding of information security and security-conscious solution design.
- Comfort applying unit testing, continuous integration, and continuous deployment.
- Strong synchronous and asynchronous communication, judgment, pragmatism, and ability to work through ambiguity.
- Preferred experience includes AI or LLM guardrails, governance automation, readiness gates, policy checks, preflight validation, tracing, auditability, logging, evaluation workflows, regression checks, provider risk assessment, privacy-by-design, regulated environments, and developer guidance.
Benefits
- Four-day Flexi-Week with one lighter or completely disconnected day per week at full pay and no reduction to annual holiday allowance.
- Hybrid/remote Flexi-office working scheme in an international culture.
- Monthly work-expense contribution and remote-working furniture package.
- Health and wellbeing support, initiatives, and sports offers.
- Access to the Awin Academy training suite and professional development resources.
- Peer-to-peer recognition vouchers.
- Hiring is available in multiple countries, with additional benefits discussed during the initial interview.
Tech Stack
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