Remote Senior AI Engineer for Data & Marketing Tools

True; United States; Remote; USD 200,000 - 320,000; Full time

Job summary

Our company is hiring for a product engineering role developing AI-powered tools for data and marketing workflows. You will explore new product ideas, prototype quickly, and build reliable AI systems that help users gain insights from their own data.

Collaborate with a small team to prototype and ship product capabilities, while making architectural choices for AI features and production LLM pipelines and evaluating model effectiveness in real-world usage.

Qualifications

• Five to twelve years of software engineering experience building core products, ideally in AI or machine learning contexts.
• Strong backend engineering skills and experience applying machine learning in product or engineering work.
• Experience with complex AI applications beyond straightforward retrieval-augmented generation.
• Product engineering experience in a fast-moving startup or growth-stage environment, with a record of increasing scope.
• Strong product intuition, customer focus, clear communication, and structured problem-solving.
• Experience building products from inception through iteration, such as as an early engineering hire or founder, is valuable.

Responsibilities

• Build proofs of concept to explore how AI can improve data and marketing workflows.
• Work with a small team to prototype and ship product ideas, helping establish new product capabilities.
• Make architectural and framework choices for AI-powered features and production LLM pipelines.
• Evaluate where different models and AI methods are effective within the product.
• Develop data agents that answer analytics and data science questions using customer data.
• Study user workflows and create seamless AI-assisted experiences.

Job description

Our company is hiring for a product engineering role developing AI-powered tools for data and marketing workflows. You will explore new product ideas, prototype quickly, and build reliable AI systems that help users gain insights from their own data.

Collaborate with a small team to prototype and ship product capabilities, while making architectural choices for AI features and production LLM pipelines and evaluating model effectiveness in real-world usage.