Principal Applied Scientist

Principal Applied Scientist

Berlin Office; Munich Office; Remotely in Germany

About Parloa

Parloa's mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like IKEA and Booking.com already deploying Parloa at scale.

About the Role

As a Principal Applied Scientist at Parloa, you will define and drive our applied AI strategy across AI agents and Generative AI.

This is a highly hands-on and high-impact role at the intersection of research and production. You will explore, validate, and scale approaches that directly shape our product, from model evaluation and routing to agent behavior, memory, and context engineering, while defining how these systems should be measured, benchmarked, and improved across the industry.

Beyond execution, you will act as a technical leader: identifying opportunities, setting direction, and building the foundations of applied science at Parloa.

Areas of Ownership

• Define and lead applied AI initiatives across agent systems, LLM evaluation, and model optimization
• Own ambiguous problem spaces end-to-end : from framing and experimentation to production impact
• Design and implement evaluation & benchmarking frameworks , leveraging and challenging industry standards — and where needed, defining new ones
• Drive innovation in agentic systems , including topics like routing, memory, and context engineering
• Prototype and validate new approaches (e.g., model combinations, fine-tuning strategies, or open-weight models)
• Translate research into production-ready solutions , working closely with engineering teams
• Act as a technical authority and multiplier , mentoring others and shaping best practices
• Establish and lead the Applied Science guild , fostering knowledge sharing and raising the bar across teams
• Influence product and technical strategy , identifying where applied science can unlock the most value

Who You Are

• 12+ years of overall experience in Applied Science or related fields, including at least 5 years of hands-on experience in ML/AI, with a proven track record of delivering systems in production
• Experience with agent-based systems or multi-step LLM workflows
• Strong recent experience working with LLMs and Generative AI systems , ideally in production environments
• Demonstrated ability to own and drive ambiguous problem spaces end-to-end —from problem framing to measurable impact
• Deep understanding of evaluation methodologies, benchmarking, and model performance analysis , including human-in-the-loop approaches
• Hands-on technical skills, with the ability to prototype, experiment, and ship solutions in collaboration with engineering teams
• Experience working on production systems , balancing speed, quality, and scalability
• Proven technical leadership and influence , with experience shaping direction, mentoring others, or driving cross-team initiatives
• Ability to operate at both strategic and execution levels , connecting long-term vision with day-to-day decisions
• Strong communication skills, with the ability to clearly articulate ideas and influence technical and non-technical stakeholders
• Evidence of broader impact (e.g., published work, open-source contributions, internal initiatives, or industry influence) is a plus

We know that great candidates don't always meet every single requirement. If you're excited about this role and believe you could make an impact, we encourage you to apply, even if your experience doesn't perfectly match every qualification.

Nice to Have

• Familiarity with model routing, fine-tuning, or open-weight models
• Background in human-in-the-loop evaluation or annotation systems
• Contributions to public research, blogs, or open-source projects

Our Recruiting Process

Talent Acquisition → Technical Peer Interview → 360° Technical Interview Loop → Bar Raiser

Why Parloa?

We're at the beginning of a new era in customer experience, one where AI doesn't just respond, but understands, reasons, and takes action. We're building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren't just support tickets; they're defining experiences. We're here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale — and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn't a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that's evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We've grown beyond the earliest startup phase, but we've kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we're scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Parloa is committed to upholding the highest data protection standards for our clients' and employees' data. All our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information.

Parloa is an e-verify employer in the USA. Please click here to learn more.

* We provide equal opportunities to all qualified applicants regardless race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background and other characteristics.