• You decide when, where, and how you work on projects and tasks. • We match you with work that fits your skills. • Gain more experience and develop various skills. • Have access to various opportunities across different industries and companies. • Be a part of the team with full-time collaboration.

• Use AI coding assistants such as OpenAI Codex, Claude Code, Cursor, GitHub Copilot, or equivalent tools as part of daily development workflows. • Apply AI-assisted approaches to software design, implementation, testing, debugging, refactoring, and documentation. • Develop and maintain reusable prompts, workflows, skills, and agent instructions that improve engineering effectiveness and consistency. • Use agentic development techniques to accelerate feature delivery while maintaining engineering quality standards. • Contribute to the evolution of AI-enabled engineering practices across teams and projects. • Design, build, and maintain modern web applications across frontend and backend systems. • Develop scalable APIs, services, and user interfaces using modern engineering practices. • Contribute to architectural decisions and system design discussions. • Ensure software solutions meet performance, security, reliability, and maintainability requirements. • Collaborate with multidisciplinary teams to deliver high-quality customer experiences. • Review and validate AI-generated code to ensure production readiness. • Implement automated testing and quality assurance practices throughout the SDLC. • Participate in code reviews and contribute to engineering standards and best practices. • Design and implement mechanisms that increase trust in AI-generated outputs, including automated validation, testing strategies, specification conformance checks, evaluation frameworks, and feedback loops. • Establish guardrails and verification workflows that ensure agent-generated code and artifacts meet functional, security, performance, and maintainability requirements. • Evaluate the effectiveness, reliability, and quality of AI-assisted development workflows and continuously improve them. • Contribute to the development of reliable engineering practices for agentic software development. • Work closely with Product Owners, Designers, QA Engineers, and other Software Engineers. • Support the adoption of AI-enabled engineering practices across teams. • Share knowledge, workflows, and best practices related to AI-assisted software development. • Mentor other engineers on effective and responsible use of AI throughout the software development lifecycle.

• Own two of the most strategically important product surfaces in our platform: AI-Native Intelligence Dashboard and Payments & Monetization • Lead the team of senior engineers, set technical direction, and ship AI-powered capabilities that customers can see, feel, and measure • Multiply your impact by leading, mentoring, and developing Engineering Managers and senior engineers • Own the outcome for execution across multiple AI engineering teams • Drive an AI First approach to engineering • Practice Change Agility by guiding teams through evolving AI technologies • Apply First Principles Problem Solving to complex AI and product challenges • Leverage Data-Driven Decision Making to assess system performance • Collaborate cross-functionally with Product, Design, Data, Security Research, and other Engineering leaders

• Design and build multi-agent systems end-to-end : planning loops, sub-agent delegation, memory and context management – that reason about live operations the way an experienced operator would • Design the agent's tools and capabilities: clean, safe, composable tools and MCP (Model Context Protocol) integrations that let agents query data, run analyses, and act reliably • Implement AI agents as scalable backend services following our development and security guidelines • Collaborate closely with Data Scientists and domain experts to bring agents and models from concept to production • Continuously improve, evaluate, and optimize agent behavior in production with eval harnesses and guardrails • Translate customer requirements into effective and scalable AI solutions • Design and implement secure APIs, real-time streaming backends (SSE, WebSockets ), and backend components • Develop and maintain data access layers and pluggable data sources with strict customer data isolation • Ensure high standards of quality, performance, and security • Contribute to technical specifications and architecture decisions