• Architect and build full stack data driven solutions • Work with cloud expertise including Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure • Collaborate in agile software development methodologies as part of a scrum team • Possibly take on multiple roles, such as Product Owner, Scrum Master, and Business Analyst • Participate in commercial implementations of tools like Cloudera, AWS Redis etc.

• Build and maintain an internal LLM gateway that handles routing, fallbacks, and rate limiting • Create reusable components for common AI patterns (RAG, function calling, streaming responses) • Develop SDKs or libraries that simplify AI integration for application developers • Implement prompt management systems and evaluation frameworks • Design and deploy vector database infrastructure for semantic search • Create monitoring dashboards for AI usage, costs, and performance metrics • Write technical documentation and best practice guides for AI implementation • Evaluate and integrate new AI services and models as they become available • Build testing frameworks for prompt regression and model output validation

• Design and develop iOS mobile applications and SDKs, ensuring high performance, quality, and responsiveness. • Create new, secure, and reliable features that enhance real-time data, video, and audio capabilities. • Implement modern iOS development design patterns to improve code maintainability and efficiency. • Propose and integrate innovative tools, frameworks, automations, and processes that enhance team productivity and code quality. • Collaborate with product management and UX teams to solve customer challenges by providing engineering solutions and trade-offs. • Participate in an agile development environment to deliver high-quality software solutions. • Refactor legacy codebases to improve maintainability and scalability, ensuring minimal disruption to ongoing development processes.

• Architect and build distributed systems that manage large, complex data and file workflows. • Translate regulatory and business requirements into usable, scalable technical solutions. • Apply machine learning and LLM techniques to analyze content, automate tasks, and enhance product intelligence. • Partner with cross-functional teams to design solutions that align technical feasibility with business value. • Experiment with new development approaches, including agentic and adaptive system design.