• Serve as the lead developer and technical decision-maker on projects, owning execution from prototype through deployment • Proactively move work forward, making pragmatic technical decisions under real-world constraints • Ensure quality, maintainability, and scalability of delivered solutions through code reviews and technical oversight • Translate business, creative, and experiential requirements into clear technical approaches and implementation plans • Design and document system architectures, data flows, integrations, and deployment strategies • Apply strong systems thinking to balance speed, risk, and long-term maintainability • Prototype quickly to validate ideas, de-risk approaches, and inform stakeholder decisions • Build and integrate AI-driven systems, including LLM-based workflows, RAG pipelines, conversational interfaces, and automation tools • Learn and apply new technologies, platforms, and hardware as project needs evolve • Collaborate cross-discipline with Product, Creative, Production, and external partners to ensure alignment and momentum • Support vendor selection and act as technical lead for specialty development partners when needed • Participate in on-site installations, testing, and live deployments, representing Left Field Labs professionally

• Maintain and enhance our existing End-to-End test framework • Review, refactor, and improve existing automated test code • Define, promote, and enforce best practices for End-to-End and system testing • Design and execute performance, load, and stress tests for our cloud platform • Analyze test results and recommend architectural or platform changes to improve scalability, reliability, and cost efficiency • Create, update, review, and execute automated test cases aligned with evolving product features (including manual execution when required) • Build tooling across the entire testing lifecycle, including test case management, test data generation, automated bug capture, and test execution tracking • Educate and mentor engineers on testing strategies, patterns, and processes to continuously improve product quality • Collaborate closely with development, platform, and DevOps teams

• Design, develop, test, deploy, and monitor high-performance backend services and APIs • Build and productionize backend services primarily in Golang • Work with Python-based ML and ML operations workflows, including model integration and inference support • Collaborate closely with ML engineers and research teams to take models from experimentation to production • Develop and maintain services using AWS (Kinesis, DynamoDB, S3) and GCP native services • Deliver production-ready features end-to-end with a strong focus on scalability, performance, and security • Diagnose and resolve production issues using tools such as Prometheus, Grafana, Google Logging, and Cloud Trace • Review code to uphold quality standards and promote best practices • Contribute to evolving backend and ML platform architecture • Participate in on-call rotation, including required night and weekend coverage

• Lead Factory Validation projects from Software, Firmware and Diagnostics perspectives, ensuring successful implementation, integration, and standardization across multiple locations. • Lead the integration and handover of the Software, Firmware and Diags for all products. • Act as a primary consultant, offering strategic direction and leadership to the engineering teams. • Engage with ODMs and cross-functional teams to collect and analyze factory requirements, delivering solutions that meet both business and operational needs. • Analyze Factory processes, systems, and workflows to identify areas for improvement and optimization. • Develop and maintain detailed documentation, including system requirements, processes and standard operating procedures (SOPs). • Collaborate across teams to design, configure, and implement changes to factory ensuring seamless integration and minimal disruption. • Perform system testing, validation, and fixing to ensure exact functionality and alignment with factory requirements. • Monitor, collect, and analyze data to identify and address issues, and propose solutions to enhance system reliability and efficiency. • Collaborate with vendors and external partners to evaluate, select, and implement new factory systems or software/firmware upgrades.