AI Engineer

Key Responsibilities

• Maintain and expand brain-platform, our core AI microservice API that connects to external AI providers. This also includes maintaining a collection of SDKs for the API. 
• Improve the reliability of the platform by fixing bugs, adding fallback functionality, etc
• Expand the number of models and providers available in the platform
• Widen the range of functionality offered by the platform with greater levels of control and flexibility
• Maintain and expand Compass, our Streamlit-based app for non-technical employees to use AI models and tools
• Develop new experimental pages and features by collaborating with various teams
• Identify successful features and help migrate them into more stable applications across Pattern
• Assist with developing AI workflows and agentic patterns
• On occasion, you will be tasked to venture beyond the foundational AI layer and assist with building and fixing AI workflows and agentic patterns that solve problems across Pattern
• In other cases, you’ll operate as an advisor for others who are building those AI workflows, providing guidance on how the foundational AI layer works and advising on best practices 
• Training and creating educational resources for the company
• Work with your lead engineer to hold training sessions with other teams and introduce them to new tools and best practices
• Create documentation and training materials to help people quickly learn how to use AI tools that you build


Requirements


• An absolute obsession with learning about LLMs and AIs, balanced with an understanding of when NOT to use LLMs to solve problems (using AI as an accelerant vs as a crutch)
• Strong python programming skills, helpful if familiar with libraries such as FastAPI, Pydantic, Streamlit, etc
• Good grasp of core software engineering principles such as SOLID, CI/CD, type checking and linting, etc.
• Understand cloud architecture in AWS (S3, DynamoDB, RDS, ECS/EC2, etc)
• Experience with generative AI models and tools (OpenAI, Anthropic, Bedrock, etc)




Optional:


• Knows Airflow, an orchestration platform. 


Experience Level


• 1-3 years of post-college experience beyond internships in AI engineering roles.




Sounds great! What's the company culture?


We want individuals who are:


• Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern’s processes and outcomes.
• Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data.
• Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner’s expectations and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern.
• Team of Doers- Someone who is a part of team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners.


What is the hiring process?


• Initial phone interview with Pattern’s talent acquisition team
• Video interview with a hiring manager
• Onsite interview with a panel of department leaders
• Professional reference checks
• Executive review
• Offer


How can I stand out as an applicant?


• Be prepared to talk about professional accomplishments with specific data to quantify examples
• Be ready to talk about how you can add value and be the best addition to the team
• Focus on mentioning how you would make a difference at Pattern
• Be prepared to talk about any side projects related to data and analytics