Why This Role Stands Out
This role at Planso offers an exceptional opportunity to build cutting-edge AI-powered products and develop your skills in LLMs, RAG, and document understanding within the dynamic architecture, engineering, and construction industry. You'll thrive here if you have strong programming fundamentals, a passion for problem-solving, and a desire to contribute to impactful AI solutions with a collaborative team. Apply now to advance your career in applied AI!
Quick Overview
Job Description
Planso builds AI-powered decision-intelligence products for the global architecture, engineering and construction industry. We work on complex problems involving enterprise data, documents and domain-specific reasoning.
Responsibilities
- Build and evaluate LLM-powered product capabilities.
- Develop pipelines for document understanding, information extraction and retrieval.
- Experiment with embeddings, reranking, RAG and agentic workflows.
- Create evaluation datasets and measure accuracy, relevance and reliability.
- Analyse failure cases and improve prompts, models and guardrails.
- Work with engineers and domain specialists to take prototypes into production.
- Maintain clear documentation of experiments and technical decisions.
What we are looking for
- Strong Python and programming fundamentals.
- Understanding of machine learning, NLP or information retrieval.
- Familiarity with LLM APIs, embeddings and RAG.
- Ability to work with structured and unstructured data.
- Understanding of evaluation metrics such as precision and recall.
- Strong problem-solving ability, ownership and curiosity.
Good to have
- Experience with PyTorch, Hugging Face, LangChain, LangGraph or LlamaIndex.
- Exposure to vector databases, knowledge graphs or document-processing systems.
- Experience building APIs using FastAPI.
- Relevant internship, academic or personal projects.
ApplicationShare your résumé, GitHub or portfolio, and a short note about an AI project you built—including one challenge you encountered and how you addressed it
- Experience building production-grade applied AI systems.
- Exposure to enterprise AI and complex real-world data.
- Opportunity to work closely with the founding and engineering teams.
- Significant ownership and a fast learning environment.
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