AI Lead
Super.com
What you’ll be working on:
- Partner with cross-functional stakeholders to identify, evaluate, and prioritize AI use cases that drive millions of dollars of business impact
- Embed in tech teams to drive the success of technical AI projects from end-to-end, including data preparation, AI technology selection (ex. which LLM, parameter tuning, prompt engineering, model fine-tuning), output evaluation, and refinement
- Embed in non-tech teams to drive the success of AI vendor integrations, including vendor selection
- Design and implement AI platform components to make it as easy as possible to integrate AI for emerging use cases
- Lead internal AI guilds to evangelize AI capabilities, educate team members on AI technologies and methodologies, and develop best practice guidelines
- Stay abreast of the latest developments in AI, integrating them internally when they’re well-suited to drive business outcomes
- Champion leveraging AI tooling for software development, and ensure our interview process brings in strong candidates who are even more productive by leveraging AI tooling
- Own our company strategy for leveraging AI and devising new AI-first ways of working
Who we’re looking for:
- Masters or PhD in Artificial Intelligence or a related field or equivalent expertise
- Experience designing and implementing AI & ML solutions that drive business impact
- Strong familiarity with cloud platforms & AI providers and their Gen AI & ML services
- Expertise in AI technology selection, evaluation, and refinement (ex. which LLM, parameter tuning, prompt engineering, model fine-tuning)
- Analytics expertise, including data preparation and AI output evaluation
- Proficient with SQL and Python
- Strong interpersonal and communication skills, with the ability to collaborate effectively with cross-functional teams, both tech and non-tech
- Experience mentoring and guiding teams - a passion for educating and evangelizing
- Knowledge of best practices in AI development, including coding standards, version control, testing, evaluation, and documentation
Our Technology:
- We use a state of the art architecture powered by Node and Python microservices and React frontend
- We use Postgres for storage, Redis for caching, and Snowflake for our data warehouse
- We use Gitlab for version control and CI/CD, and our infrastructure is hosted on AWS, making use of Kubernetes, RDS, etc
- We invest heavily in monitoring and automated alerting using Datadog
- We use Amplitude, Hotjar, and LogRocket for client-side metrics and experimentation
- We use Material-UI and maintain our own component library, using Figma for mock-ups
- We integrate with a multitude of third-parties to support our compliance, risk, and security policies
