AI Product Engineer

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 modelling 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 prioritise what matters, move fast, and learn from real users.

Responsibilities:

• Design and deploy AI agents that diagnose funnel issues, trigger actions, and improve outcomes.
• Build and optimise 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 and 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.

Requirements:

• 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 and React frontends.
• Deep understanding of statistical modelling, A/B testing, and impact measurement.
• Familiarity with GenAI, vector databases, and building agentic applications.
• Ability to move independently and align quickly with a bias toward speed, iteration, and clarity.

Nice to Have:

• Experience with PyTorch, TensorFlow, or MLOps tools (Vertex, SageMaker, etc. ).
• Exposure to marketing optimisation, attribution, or funnel analytics.
• Knowledge of Bayesian methods, RL, or bandit algorithms.
• Understanding of cloud platform components (GCP, AWS) and experience with Kubernetes.