Senior Software Engineer (Data & AI)
Vendelux
full-remoteseniorpermanentbackenddata Full remote 133 days ago via WTTJ
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PythonSQLMachine LearningLLMsRAGEmbeddingsAirflowDagsterAWSGenAI
About the role
Role Overview
Join Vendelux as a Senior Software Engineer (Data & AI). You’ll develop, deploy, and scale AI-powered product features that are central to the core user experience, working end-to-end in a cross-functional startup environment.
Key Missions / Responsibilities
- Architect, implement, and ship data-driven product features that deliver measurable business value.
- Build maintainable and scalable systems, writing clean, testable code.
- Integrate with data pipelines (new and existing) and continuously improve data quality.
- Research and apply modern AI methods to create new product capabilities, including:
- AI agents
- LLMs, RAG, embeddings
- Supervised/unsupervised learning
- Collaborate across data, engineering, and product to translate business problems into effective data solutions.
Requirements
- 5+ years professional experience in software engineering or data engineering.
- At least 3+ years building AI/ML-driven products.
- Strong programming skills in Python and SQL.
- Strong understanding of data science fundamentals and machine learning, with the ability to balance research vs. engineering tradeoffs.
- Proven track record of shipping user-facing features with measurable impact.
- Strong written and verbal communication skills and cross-team collaboration.
Nice to Have
- Experience with modern AI frameworks such as Hugging Face and LangChain.
- Experience designing data pipelines using Airflow, Dagster, or equivalents.
- Production experience applying LLMs/generative AI, including prompt engineering, RAG, and LLM deployment.
- Solid cloud infrastructure knowledge (AWS, GCP, or Azure).
- Startup experience.
- Open to candidates from non-traditional backgrounds.
About Vendelux
Vendelux is a fast-paced startup building a product that uses AI-powered features to deliver user-facing impact. The company focuses on end-to-end development of data-driven capabilities, with strong emphasis on AI/ML engineering best practices and data quality.
Scraped 5/13/2026