AI Product Engineer

Out of the Blue is building agentic AI to help eCommerce brands scale smarter and protect revenue. Our platform proactively detects and acts on what breaks growth—misfiring pixels, broken tracking, underperforming funnels.

We combine GenAI, classic ML, and optimization to surface insights, recommend fixes, and deploy autonomous agents that take action across the stack.

We’re a post-product, post-revenue startup backed by SF-based investors, with a team from Google, PayPal, eBay , and alumni of Stanford, Berkeley, and Booth .

The Role

As an AI Product Engineer , you’ll help design, build, and ship intelligent systems that drive business-critical insights and decisions for high-growth DTC brands and agencies.

You’ll work across the full lifecycle—from data pipelines and modeling to LLM integrations and agent deployments. This role blends engineering, applied ML, and product thinking to deliver real-time, high-leverage outcomes .

You’ll collaborate closely with founders, PMs, and GTM teams to prioritize what matters, move fast, and learn from real users.

Your Impact

Design and deploy AI agents that diagnose funnel issues , trigger actions, and improve outcomes

Build and optimize ML models for forecasting , anomaly detection , root-cause analysis and causal inference

Integrate LLMs, prompt workflows , and semantic search into customer-facing features

Understand and contribute to E2E application development in terms of delivering customer features (from data extraction, analysis, APIs & front-end components)

Own ML workflows end-to-end: data prep, training, evaluation, deployment, and monitoring

Translate messy data and ambiguity into clean, scalable intelligence

What You Bring

3–6 years of experience in ML or applied AI, preferably in product or startup environments

Strong in Python and building production-grade ML systems

Understanding of overall application stack including Node.js backends & React frontends

Deep understanding of statistical modeling , A/B testing, and impact measurement

Familiarity with GenAI , vector databases, and building agentic applications

Ability to move independently and align quickly—bias toward speed, iteration, and clarity

Nice to Have

Experience with PyTorch , TensorFlow , or MLOps tools (Vertex, SageMaker, etc.)

Exposure to marketing optimization , attribution, or funnel analytics

Knowledge of Bayesian methods , RL , or bandit algorithms

Understanding of Cloud platform components ( GCP, AWS ) and experience with Kubernetes