AI Engineer

How You’ll Contribute

Design and maintain scalable data-to-AI pipelines covering ingestion, transformation, feature/prompt engineering, model training, orchestration, deployment, and monitoring.
Deliver AI-driven solutions that measurably improve key product or operational metrics (e.g., revenue uplift, cost reduction, consumer satisfaction, platform efficiency, prediction accuracy, latency reduction).
Partner with Data and Product to identify and execute AI opportunities aligned with strategic objectives.
Establish and enforce AI and machine learning and data operational standards, governance, and best practices across the organization.
Deliver actionable, data-driven insights and reporting to inform business decisions and evaluate performance across products, operations, and AI systems.
Build reliable experimentation frameworks to validate model performance and business impact and drive iterative improvements through reliable model evaluation and testing.
Own the scalability, robustness, observability, optimization and operational excellence of production AI systems and data pipelines.

Strengths That Shine in This Role

Strong analytical and problem-solving skills, with the ability to translate ambiguous business requirements into structured AI and data solutions.
Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Ability to collaborate effectively across Product, Engineering, BI, and Data teams.
Strong organizational skills and ability to manage multiple priorities in a fast-paced environment.
Proactive, ownership-oriented mindset with the ability to work independently and drive solutions from concept to production.
Professionalism and composure when operating under pressure or resolving production issues.

Skills That Matter in This Role

Minimum of 3-5 years of designing, building, and operationalizing end-to-end data and AI systems in production environments
Sound knowledge of machine learning lifecycle from data gathering and data preparation to feature engineering to model deployment, monitoring and iteration.
Hands-on experience with LLM-based systems (e.g., RAG architectures, prompt engineering, model evaluation, API integration).
Strong programming skills in Python & SQL, experience writing production-quality code
Exposure to AWS Bedrock and preferably AWS Sagemaker, Cloud based AI/ML services and modern data platforms
Experience integrating external AI/LLM APIs and building and operationalizing application-layer AI services is desirable.
Strong software engineering fundamentals, including experience with CI/CD, testing practices, and containerization concepts.

Why You’ll Love Working Here

Thrive in an award-winning, innovation-driven culture that champions growth, embraces diversity, and fosters inclusion for all. See our awards →
Earn competitive pay with annual performance-based bonuses that recognize your impact
Invest in your future with our 401(k) plan featuring company matching
Stay healthy with comprehensive medical, dental, and vision coverage, plus HSA and FSA options
Recharge with paid vacation and sick days — and a paid day off for your birthday
Make an impact with two paid volunteer days to give back to your community
Advance your skills with  free access to LinkedIn Learning and our education reimbursement program
Prioritize your mental health with a free premium Headspace membership
Stay active with our on-site fitness center
Refuel at fully stocked refreshment stations with complimentary drinks and snacks
Enjoy exclusive perks with access to “Tickets at Work” discounts and memberships