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Jobs(38,923)/AI Engineer Role(1,022)/hipeople-official (1) - Applied AI Engineer – Systems & Reliability (remote/Berlin-based)
hipeople-official

hipeople-official - Applied AI Engineer – Systems & Reliability (remote/Berlin-based)

Remote - Germany+ Equity2mo ago
RemoteEMEAArtificial IntelligenceData AnalyticsAI EngineerGoDocumentationData Quality

Requirements

• 100% alignment with our Ops Principles https://docs.google.com/document/d/1XIxbcK6Il4xm4kofx8fsKoEP9J13B33V8KBPRquImBs/edit?usp=sharing (if you feel this isn’t you, do not apply) • Excitement for building in Go • Experience working with AI/ML systems, LLMs, or data-intensive applications • High ownership mindset and attention to detail • Strong interest in quality, reliability, and system performance, not just building features • Ability to debug complex systems across prompts, models, and data pipelines • Clear communication and documentation skills • Comfort improving systems and processes, not just using them • Experience with evaluation methods, metrics, or experimentation is a strong plus • Familiarity with monitoring, CI/CD, and production systems is a plus • Strong candidates often come from: • AI/ML engineering or applied AI roles • Backend or systems engineering roles with exposure to AI/ML • Data science roles with strong engineering and production experience • Other paths that demonstrate building and improving real-world systems with rigor • This role is remote or on-site in our Berlin office. We do not offer any Visa support for Germany at this time.

Responsibilities

• Own evaluation systems and quality standards • Build and maintain evaluation pipelines for core AI workflows across screening, interviews, assessments, and references • Define metrics, benchmarks, and acceptance criteria for AI outputs • Track performance over time (quality trends, drift, regressions) and make results visible across the team • Drive continuous improvement of AI performance • Identify issues across prompts, workflows, and data pipelines using both quantitative analysis and deep dives into real cases • Design and implement improvements across: • prompting strategies • model selection, configuration, and fine-tuning • input data quality and preprocessing • orchestration and workflow design • Push new systems from “working” (80%) to reliable and high-quality (95%+) • Ensure reliability, monitoring, and stability • Build and improve monitoring for AI systems (e.g. dashboards, alerts, tracing) • Detect and prevent failure modes, breakdown risks, and performance degradation • Monitor usage, rate limits, and capacity to ensure stable operation at scale • Drive testing, CI, and safe shipping practices • Integrate AI and prompt testing into CI (e.g. regression tests, golden datasets, staging environments) • Define standards and tooling so product and engineering teams can safely ship without introducing regressions • Act as a quality gate for AI-related changes • Own AI system audits and compliance support • Prepare and support internal and external audits (e.g. SOC 2 and beyond) • Provide evidence, documentation, and artifacts for AI system behavior and controls • Translate audit findings into concrete improvements in systems and processes • Productionize AI workflows (not just prototype them) • Build and productionize AI workflows that meet defined quality and reliability standards • Support product and engineering teams in integrating AI cleanly into product logic and user experience • Ensure new AI capabilities are robust, measurable, and maintainable before release

Benefits

• Direct ownership of one of the most critical parts of the company: AI quality and reliability • Work closely with founders on core product and technical decisions • Competitive salary and meaningful stock options • Educational stipend to support ongoing learning and development • The best team to work with (true story!) • Step 1: AI Application Screen (immediate) • Step 2: AI Recruiter Interview (right after successful AI Application Screen) • Step 3: AI Skills-Assessment (right after successful AI Recruiter Interview) • Step 4: Interview with Co-founder • Step 5: Interview with the team (incl. Live Case Study) • Step 6: References + Offer • Duration: 1 week, end-to-end • 🌈 We proudly believe in the power of diversity and inclusion. Diversity of thought fuels our success which can only be achieved with a diverse team. We welcome people from any race, orientation, gender, religion, age, ethnicity, differently-abled, neurodiverse or identity, we value all uniqueness.

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