PrizePicks

Full-stack Engineer

• Architect and implement performant, scalable, and reliable backend systems primarily in Rails and Go
• Identify and extract well-scoped capabilities from existing Rails systems, designing clear interfaces and incremental migration paths
• Design reliable data flows between backend services and BigQuery and Snowflake warehouses
• Lead complex initiatives from discovery and technical design through implementation, rollout, monitoring, and iteration
• Break work into executable pieces, clarify sequencing and ownership, and track risks and dependencies
• Partner with Product, Design, QA, Data, Platform, and engineering teams across domains
• Diagnose and resolve performance bottlenecks, optimize database queries, and improve backend resilience
• Propose and drive architectural decisions and communicate technical recommendations
• Mentor engineers through code reviews, pairing, design discussions, and technical guidance
• Improve code quality, testing, observability, deployment, and operational ownership
• Participate in the on-call rotation, root cause analysis, and long-term reliability improvements

Senior Software Engineer, Ruby on Rails

• Design and build performant, scalable, and reliable Rails-based backend services
• Lead complex feature delivery end-to-end, from product requirements through deployment and monitoring
• Diagnose and resolve performance bottlenecks
• Optimize database queries and improve backend resilience under load
• Propose and drive architectural decisions, evaluating tradeoffs and communicating recommendations
• Mentor Software Engineers I, II, and III through code reviews, pairing, and technical guidance
• Define and improve engineering practices around code quality, testing, observability, and deployment
• Collaborate with Product Managers, Designers, QA, and engineering teams to translate product goals into technical solutions
• Participate in the on-call rotation, root cause analysis, and long-term reliability improvements

Senior Software Engineer – Gamification, Ruby on Rails

• Participate in team-level architectural decisions around data modeling, service boundaries, API design, and background processing patterns
• Own feature development end-to-end, from technical design through delivery
• Break complex projects into well-scoped, deliverable pieces
• Write idiomatic, performant, well-tested Ruby code
• Improve code quality, performance, reliability, and developer experience
• Guide junior engineers through code reviews, pairing sessions, and design feedback
• Collaborate with Product, Design, and QA to align product goals and implementation
• Participate in on-call rotation, incident response, root cause analysis, and systemic improvements
• Document technical decisions, data models, and service patterns

Board Software Engineer III, Ruby on Rails

Frontend Engineer

• Take ownership of features end-to-end, from technical design through delivery, breaking complex UI and interaction flows into deliverable pieces
• Write clean, performant, well-tested TypeScript and React Native code
• Participate in architectural decisions involving component patterns, state management, navigation, and performance optimization
• Improve app performance, code quality, accessibility, and developer experience
• Guide Software Engineers I and II through code reviews, pairing sessions, and design feedback
• Collaborate with Product, Design, and QA to align product goals and implementation
• Participate in the on-call rotation, incident response, root cause analysis, and systemic improvements
• Document technical decisions, component patterns, and architecture

Software Engineer III – Front End

• Build the agent platform and tooling, including orchestration, tool/function calling, evaluation harnesses, prompt/version management, tracing/observability, and safety/guardrails
• Support retrieval-augmented generation (RAG), structured extraction, and production inference workflows
• Work with application engineering teams to embed AI into software development workflows such as code review assistance, test generation, incident support, and developer copilots
• Decide what to delegate to agents versus retain as human work, scope agent tasks, and adapt the boundary as tooling maturity changes
• Diagnose agent behavior from traces, intermediate steps, inputs, and failure points
• Verify AI-generated output and tests before trusting or deploying them
• Own applied AI projects from prototype through production, including data needs, system design, model/vendor selection, rollout, monitoring, and iteration
• Partner with product, design, and data/ML stakeholders to deliver customer-facing outcomes
• Assess AI adoption across teams, identify bottlenecks and failure modes, build missing capabilities, teach existing tools, and advocate for adoption
• Establish engineering practices for reliability, evaluation, incident response, privacy/security, and AI development
• Coach engineers through design reviews, pairing, and pragmatic technical leadership
• Mentor peers and improve organization-wide engineering quality

Senior Software Engineer, Applied AI

Operations

• Post and maintain accurate pre-game and in-game player projections for all supported markets and leagues covered by PrizePicks
• Monitor player projections throughout the day and track key information needed for projections
• Manage risk and monitor projections using modeling and quantitative analysis
• Understand PrizePicks members' play patterns and adjust internal processes accordingly
• Work with sport owners to implement strategies, best practices, and processes around key markets
• Support and execute product initiatives
• Help establish standard operating procedures for PrizePicks game operations tasks
• Apply and adapt game operations skills for other assigned sports

Game Operations Analyst – Pre Match

Platform Engineer

• Design and build end-to-end machine learning infrastructure to transition experimental Data Science models into robust, high-availability production services
• Build automation to deploy low-latency inference services serving model predictions in milliseconds
• Power real-time decisions for dynamic oddsmaking, risk analysis, and smart deposit defaults
• Lead creation and optimization of a centralized feature store for complex models across business domains
• Build and operate core ML platform components for training and experimentation with the Infrastructure team
• Champion model deployment, monitoring, and ML CI/CD best practices
• Implement automated retraining pipelines and observability to detect data drift and model degradation

Machine Learning Platform Engineer

DevOps Engineer

• Design, implement, maintain, and monitor reliable production systems at scale
• Lead incident response, mitigate production issues, and conduct post mortem analysis
• Proactively monitor performance, analyze system failures, identify bottlenecks, and propose solutions
• Create and support observability/monitoring tools and vendor integrations
• Drive a reliability culture focused on system reliability, scalability, resilience, and security
• Train and mentor other engineers

Senior Site Reliability Engineer, SRE

Product Designer

• Drive End-to-End Delivery: Execute within the complete design lifecycle within the Promotions and Rewards domain.
• Build & Refine Interfaces: Focus on hands-on design and high-fidelity prototyping to create polished, visually stunning rewards interfaces.
• Develop & Ship New Features: Utilize AI, rapid prototyping, and iterative design to conceptualize, develop, and launch groundbreaking promotion mechanics and system features.
• Maintain Design Standards: Uphold high design quality through consistent design reviews and ensuring consistent excellence across all visual and interaction design.
• Drive Cross-Functional Collaboration: Foster effective partnerships with Product, Engineering, Marketing, and Revenue Operations teams ensuring seamless handoffs and total alignment between business goals and the rewards journey.

• Deliver features independently: Own the implementation of small-to-medium features in the React Native app from design through deployment with minimal guidance.
• Write production-quality code: Produce well-tested, maintainable TypeScript code that meets team standards for quality, performance, and user experience.
• Contribute to technical design: Participate in design discussions for team features, offering informed opinions on component architecture, state management, and UI patterns.
• Improve app quality: Identify and fix bugs, address technical debt, and improve performance and accessibility in the features you work on.
• Review code thoughtfully: Provide constructive, thorough feedback in code reviews that helps teammates improve and maintains codebase quality.
• Collaborate cross-functionally: Work with Product Managers and Designers to refine requirements and ensure implementations match design intent and product goals.
• Participate in on-call rotation: Respond to production incidents, contribute to resolution, and help document learnings for the team.
• Share knowledge: Document your work and share context through team discussions, making it easier for others to understand and build on your contributions.

Software Engineer II, React Native

Backend Engineer

• Design and build backend services: Architect and implement Go-based microservices that are performant, scalable, and reliable, supporting real-time and high-throughput workloads.
• Own technical delivery: Lead the technical design and implementation of complex features end-to-end — from product requirements through deployment and monitoring.
• Drive system reliability: Diagnose and resolve performance bottlenecks, optimize database queries, and improve the resilience of distributed systems under load.
• Define technical direction: Propose and drive architectural decisions for your team’s services, evaluating tradeoffs and communicating recommendations clearly.
• Mentor and elevate: Provide hands-on mentorship to Software Engineers I, II, and III on your team and in the organization through code reviews, pairing, and technical guidance.
• Improve engineering practices: Define, advocate for, and improve best practices around code quality, testing, observability, and deployment for your team.
• Collaborate cross-functionally: Work closely with Product Managers, Designers, QA, and other engineering teams to translate product goals into well-scoped technical solutions.
• Participate in on-call rotation: Share responsibility for production incidents, contributing to root cause analysis and long-term reliability improvements.

Senior Software Engineer, Go

Social Media Manager

• Help lead Gametime social strategy and content ideation around major leagues, including, but not limited to: NFL, NBA, MLB, WNBA, UFC, college football and college basketball.
• Own live, reactionary social coverage, ideating, creating, and publishing share-worthy content that resonates with our users and sparks conversations across platforms including, but not limited to: X, Instagram, TikTok, Threads, and Facebook.
• Assist with community engagement across platforms, building and maintaining meaningful relationships with our users.
• Actively monitor social media trends, memes, and cultural conversations to ensure PrizePicks remains at the forefront of the industry.
• Maintain an 'always on' approach to social media, constantly tracking the player, league, team, and cultural storylines that matter to the PrizePicks audience, and surfacing insights that inform planning and execution across the full Social Media & Community team.
• Support planning for integrated marketing campaigns and tentpole events, ensuring live Gametime coverage supports marketing and business priorities.
• Conduct content and channel reporting to measure performance, identify strengths and weaknesses, and inform future Gametime strategies.
• Participate in strategy and campaign planning sessions, ideation sessions, reporting syncs, and other internal and cross-functional processes.

Data Scientist

• Lead a team of data scientists, covering topics across retention and acquisition marketing
• Oversee the development & maintenance of production-grade machine learning models, across topics such as customer lifetime value, customer segmentation, multi-armed bandits, media mix modeling, and attribution
• Manage projects centered around marketing data analysis, including leveraging causal inference frameworks, to assess impact from efforts and drive outcomes
• Integrate LLMs into data & operations workflows, to increase throughput & scale across domains
• Mentor junior team members, enhancing analytical rigor throughout the PrizePicks Analytics Team
• Effectively manage projects, ensuring deadlines and objectives are met, and business impact is made
• Collaborate with senior leadership, to align marketing data science effort with overall company & marketing goals