AI is becoming a core part of what we build at Kainjoo — not as a buzzword, but as real, useful features embedded in the products our clients depend on. You’ll be the person who makes that happen: designing and integrating AI and machine learning capabilities into production systems, working closely with backend teams, and pushing the quality bar for what intelligent features can do.
You’ll build Python-based AI services, implement LLM-powered features, and work with backend teams to expose AI outputs through clean APIs. You’ll also help define what’s possible — advising on feasibility, trade-offs, and the right tools for each use case.
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Design and build Python-based AI/ML services (FastAPI or Flask) for intelligent product features
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Implement LLM-powered features: classification, extraction, summarisation, scoring, and agent-based workflows
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Train, validate, and iterate on ML models using structured and time-series data where applicable
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Build and maintain RAG pipelines for knowledge-intensive use cases
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Expose AI outputs via REST APIs consumable by application backends
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Implement feature engineering pipelines from relational data sources
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Monitor model and AI system performance in production — detect drift, evaluate outputs, retrain as needed
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Collaborate with product and engineering teams to define AI-driven feature requirements
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Document system logic and data requirements clearly for non-ML stakeholders
Personality
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You’re excited about applied AI — not just the research, but shipping things that actually work
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You’re rigorous: you evaluate outputs, you catch hallucinations, you don’t ship blindly
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You communicate well about what AI can and can’t do, especially with non-technical stakeholders
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You stay close to the field — you know what’s changed in the last six months
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You’re collaborative and enjoy working at the intersection of product and engineering
Experience
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3+ years of AI/ML engineering or applied AI experience
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Strong Python skills — FastAPI or Flask for service development
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Hands-on experience integrating LLM APIs (OpenAI, Anthropic, or similar) into production systems
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Experience building or working with RAG architectures and vector databases (Pinecone, Weaviate, pgvector, or similar)
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Familiarity with ML frameworks for structured data tasks (scikit-learn, XGBoost, or similar)
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Experience deploying AI/ML services as REST APIs in production
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Ability to evaluate and monitor AI output quality in production
Nice to Have
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Experience with prompt engineering, fine-tuning, or instruction tuning
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Background in operations research or constraint-based optimisation
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Familiarity with PostgreSQL or BigQuery for data access
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Knowledge of agentic AI patterns (tool use, multi-step reasoning, function calling)
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Experience with model monitoring tools (MLflow, Weights & Biases)
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Bachelor’s or Master’s degree in Computer Science, Mathematics, Data Science, or a related field
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Relevant AI/ML certifications or published work are a plus
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Fluent in English; French is a plus
Location
Morges, Switzerland
Engagement type
Remote
Department
KJ. Tech Engineering
