Technical Lead - AI-Powered Team

Lead the squad building intelligent automation into our Climate ERP

We're a Series A climate tech startup (€6.5M funding, 50+ team) with clients like Maersk, Zalando, and DMG MORI. We're looking for a Technical Lead to guide our new product squad in building AI-enhanced features that help enterprises automate their carbon management.

Location: Remote-first (Berlin, Munich, Cologne/Bonn, Hamburg, Lisbon, or London based)
Team: You'll lead up to 5 engineers in a cross-functional squad with a PM

The Role

You'll be the technical leader for our fourth product squad, focused on integrating intelligent features into our Climate ERP platform. Your squad will work closely with our data science team to bring AI capabilities to production.

Technical Leadership (70%)

• Own technical architecture for the integration of AI-powered features (automated data matching, emission predictions, anomaly detection) that are usually built by our Data Science team
• Build robust integrations with LLM models and AI services (Claude, AWS Bedrock, internal models, Pipedream, etc.)
• Write production code in NestJS, React, TypeScript, PostgreSQL, AWS
• Design scalable data pipelines that feed our AI models
• Ensure reliable, performant delivery of AI features to enterprise clients

People Leadership (30%)

• Manage and mentor 5 software engineers
• Collaborate with our data scientists to translate ML models into production features
• Partner with your squad's PM and Designer to define AI feature roadmap
• Report directly to our CTO

What We're Looking For

Must-Haves:

• 2+ years of technical leadership experience
• Strong full-stack experience with TypeScript, Node.js (NestJS preferred), React
• Experience integrating AI/ML capabilities into production applications (via APIs, model serving, etc.)
• Solid understanding of data pipelines and API design
• Track record of shipping data-intensive features
• Excellent communication skills in English

Nice-to-Haves:

• Experience working with data scientists or ML engineers
• Familiarity with LLMs and prompt engineering (OpenAI, Anthropic)
• Background in data processing at scale (batch processing, streaming)
• Knowledge of Python for data manipulation
• Experience with AWS ML services (SageMaker, Bedrock)
• Domain knowledge in sustainability or supply chain

What You'll Build

Your squad will focus on intelligent features like:

• Smart Data Ingestion: AI-powered parsing and mapping of customer emission data
• Automated Insights: Anomaly detection in carbon reporting and predictive analytics
• Intelligent Matching: Auto-matching activities to emission factors using NLP
• Supply Chain Intelligence: AI-assisted supplier risk assessment and recommendations
• Natural Language Interfaces: LLM-powered features for data exploration and reporting

Why This Role is Exciting

• Real Impact: Your work directly helps companies reduce millions of tons of CO2
• AI in Production: Ship AI features to enterprise clients, not just experiments
• Cross-functional Collaboration: Work directly with data scientists and climate experts
• Modern Stack: Full ownership of your squad's technical decisions
• Growth Path: Shape our AI strategy as we scale from 50 to 100+ people

What We Offer

• Competitive salary + equity (VSOP)
• Home office setup + Annual learning budget
• 27 vacation days + public holidays
• Monthly coworking budget
• Flexible remote work with quarterly team offsites
• Direct collaboration with our data science team
• Opportunity to define our AI integration strategy

Our AI/Data Challenges

• Processing millions of emission data points with intelligent categorization
• Building self-improving data quality systems
• Creating recommendation engines for decarbonization actions
• Developing automated compliance checking against regulations
• Scaling ML model inference for real-time features

Tech Stack Context

• Backend: NestJS, TypeScript, PostgreSQL, Redis
• Frontend: React, TypeScript, Material-UI
• Infrastructure: AWS (ECS, Lambda, RDS, S3)
• AI/ML: Python models served via APIs, OpenAI integration, AWS SageMaker
• Data: Apache Airflow, pandas, custom ETL pipelines

Interview Process

1. Initial call with our CTO (30 min)
2. Technical discussion including AI integration approaches (60 min)
3. System design: Building an AI-powered feature end-to-end (60 min)
4. Meet your future squad and data science team (45 min)
5. Reference checks & offer

We move quickly - full process completed within 2 weeks.

Ready to bring AI innovation to climate tech?

Apply with your CV and a brief note about your experience shipping AI-powered features to production.