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

HiPeople is the AI Hiring Platform that takes care of screening, interviews, assessments, and references. So recruiting teams can focus on what matters most. People.

We work with some of the world's leading brands, including the NFL, Zapier, Celonis, and DAZN. and are backed by leading investors and operators such as: Moonfire founder Mattias Ljungman, Capnamic, Cherry, André Christ (LeanIX, an SAP company), Mirko Novakovic (Founder Instana/Dash0), Micha Hernandez (Fiberplane), and others.

We’re hiring an Applied AI Engineer to build the backbone of how we ensure quality, reliability, and trust in our AI systems as we scale toward $10M ARR and beyond .

You’ll work directly with founders and play a central role in making sure our AI products are robust, measurable, and enteprise-production-ready. This role is for people who care deeply about quality, enjoy working on hard system problems, and want to build AI that actually works in the real world.

We are an extremely lean team and plan to reach $10M ARR with fewer than 20 people. Every hire materially changes the company. This role has direct exposure to founders and real responsibility from day one.

What you’ll do

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

What we are looking for

100% alignment with our Ops Principles (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

Background

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

Logistics

This role is remote or on-site in our Berlin office. We do not offer any Visa support for Germany at this time.

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!)

Process

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.