Senior Data & AI Engineer: Build Production AI Features

Requirements

• This role is perfect for someone motivated more by impact than method, loves to solve data problems using whatever means necessary, and is eager to see their output shape the user experience
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• 5+ years of professional experience in software engineering or data engineering, with at least 3+ years building AI/ML-driven products
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• Strong programming skills in Python and proficiency in SQL
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• Experience with modern AI frameworks (eg HuggingFace, LangChain, etc.) and designing data pipelines (Airflow, Dagster, or equivalent),
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• Solid understanding of cloud-based infrastructure (AWS, GCP, or Azure)
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• Experience applying LLMs and generative AI in production, including prompt engineering, RAG, and LLM deployment
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• Strong grasp of fundamental data science and machine learning techniques, with the ability to balance research and engineering tradeoffs
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• Demonstrated ability to translate business problems into data solutions that drive business value
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• Proven track record of shipping user-facing features with measurable impact
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• Excellent written and verbal communication skills; ability to collaborate across data, engineering, and product teams
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• Startup experience preferred
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• Not all candidates will check all of the requirements listed above and that’s ok! We are open to great people from non-traditional backgrounds

What the job involves

• We’re looking for a Senior Engineer, Data & AI who thrives at the intersection of software engineering, data engineering, and applied AI to build production-grade systems
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• You’ll develop, deploy, and scale features that sit at the core of our product
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• Design & Build AI-Powered Features: Architect, implement, and ship data-driven product features, always starting with the customer problem first. From prototyping through production, you’ll apply the right level of technology (whether simple heuristics or advanced AI) to deliver impact
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• Build for Production: Build maintainable and scalable systems, including writing clean, testable code, integrating with new and existing data pipelines, and deploying solutions and services into cloud environments
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• End to End Solution Delivery: Operate as an end-to-end developer in a fast paced startup. This involves identifying opportunities, prototyping solutions, securing stakeholder support, and productionalizing features that deliver measurable business value
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• Applied AI Innovation: Research and apply modern methods (AI agents, LLMs, RAG, embeddings, supervised/unsupervised learning) to power new product capabilities, prioritizing impact and speed over perfection
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• Enhance User Experience Through AI: Translate business problems into AI solutions that improve user workflows, accelerate insights, and drive measurable value
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• Collaborate Cross-Functionally: Work with business stakeholders and other engineers to turn customer problems into technical requirements and impactful features
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• Promote Best Practices: Establish and evangelize standards for AI/ML engineering and data quality across the team