AI Native Staff Engineer

Carv; Amsterdam; Hybrid; EUR 80,000 - 100,000; Full time

Benefits offered by this job

Competitive compensation package

Meaningful stock options

Top-tier tools (e.g., MacBook Pro)

Hybrid work setup

Opportunity for significant impact

Job summary

A leading AI solutions provider in Amsterdam seeks an experienced Staff Engineer to build and ship AI-native product features. You will architect systems integrating LLMs and agents, mentor engineers, and ensure production reliability. Ideal candidates have over 8 years of software engineering experience, particularly in cloud environments like GCP or AWS. The role offers a competitive compensation package, stock options, and a hybrid work setup, emphasizing real impact and ownership in AI product development.

Qualifications

• Proven track record in designing and shipping large-scale production systems.
• Experience operating systems in production including incident handling and performance tuning.
• Strong judgment on when to use AI vs deterministic logic.

Responsibilities

• Design and ship AI-powered product features from conception to deployment.
• Architect systems that integrate LLMs, agents, and traditional software.
• Mentor engineers to improve AI-native workflows.

Skills

Experience shipping LLM-powered features

Production system design

Cloud-native experience

Backend engineering fundamentals

Education

8+ years of software engineering experience

Tools

GCP

AWS

Azure

Vector databases

Job description

You've built agentic systems. You've shipped LLM-powered features to production. You know the difference between a cool demo and something that actually works at scale.

What You’ll Do

Build AI-Native Product Systems

• Design and ship AI-powered product features end-to-end
• Architect systems where LLMs, agents, and traditional software work together
• Implement RAG pipelines, structured reasoning flows, and tool-using agents
• Continuously improve reliability, latency, and cost efficiency

Engineer With AI at Full Leverage

• Use AI agents to accelerate development, testing, and architecture decisions
• Prototype rapidly and ship production-grade systems
• Set up internal AI tooling that multiplies team output
• Push the boundary of what’s possible with current models

Own Impact, Not Experiments

• Translate product problems into scalable AI-powered solutions
• Measure real‑world performance (accuracy, business impact, UX)
• Optimize for production robustness — not just demo quality

Shape Our AI‑Native Engineering Culture

• Raise the bar for how we use AI internally
• Establish pragmatic standards for evaluation and iteration
• Mentor engineers on AI-native workflows
• Contribute to long-term technical direction

What We’re Looking For

You:

• Actively use LLMs in your daily workflow
• Have built agents, RAG systems, or AI-powered tools
• Care about practical reliability over theoretical elegance
• Think in orchestration, not just prompts
• Experiment constantly with new models and tools

We care less about:

• Academic ML background
• Publishing papers
• Training models from scratch

We care more about:

• What you’ve shipped
• How you use AI to move faster
• How you think about systems that include AI components

Why Join Us

We’re redefining recruitment with AI at the core of the product — not bolted on.

You’ll:

• Work directly with experienced SaaS leadership (15+ years building in this space)
• Have real ownership over architecture and AI direction
• Built in a high-velocity, high-impact environment
• Help define what AI-native enterprise software looks like

What’s in It for You

• Very competitive compensation package
• Meaningful stock options
• Top-tier tools (MacBook Pro + AI tooling budget)
• Hybrid setup + occasional travel
• Really make an impact

Staff-Level Engineering Depth

• 8+ years of professional software engineering experience
• Proven track record in designing and shipping large-scale production systems
• Experience owning architecture across services or product domains
• Strong backend engineering fundamentals (APIs, distributed systems, data modeling, concurrency, reliability)
• Experience operating systems in production (monitoring, incident handling, performance tuning)
• Cloud-native experience (GCP, AWS, or Azure)

Production AI Systems (Not Research)

• Experience shipping LLM-powered features to real users in production
• Designed and implemented RAG systems in production environments
• Built or architected AI agents or tool-using multi-step reasoning systems
• Designed evaluation frameworks for LLM output quality, safety, and regression detection
• Experience optimizing AI systems for latency, cost efficiency, and reliability
• Experience integrating vector databases and embedding pipelines into scalable systems

AI-Native Engineering Approach

• Actively use AI tools and agents to augment your engineering workflow
• Demonstrated ability to design systems where AI components and deterministic systems work together
• Experience turning fast AI prototypes into production-grade systems
• Strong judgment around when to use AI vs deterministic logic

Ownership & Impact

• Experience leading complex technical initiatives end-to-end
• Ability to translate ambiguous business problems into system architecture
• Experience mentoring senior engineers or setting technical standards
• Track record of shipping high-impact features with measurable outcomes