Technical Lead ID71009

<span id="spandesc"> <div> AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. </div> <div> </div> <div> <b> WHY JOIN US </b> </div> <div> If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! </div> <div> </div> <div> <b> ABOUT THE ROLE </b> </div> <div> We are looking for a <b> Technical Lead </b> to drive end-to-end application engineering for a large-scale marketing analytics platform, serving as the primary owner of code quality and application architecture. You will lead the design and deployment of containerized Python and React applications, integrate complex business logic and AI-powered features into an existing platform, collaborate closely with DevOps teams, and guide senior engineers while ensuring alignment with established engineering standards and long-term maintainability. </div> <div> </div> <div> <b> WHAT YOU WILL DO </b> </div> <div> - Review all PRs and enforce code quality standards, preventing "spaghetti code" and scope creep. </div> <div> - Design and deploy containerized applications using REST APIs. </div> <div> - Embed complex logic, AI features, and outputs from data-heavy backends into the platform without disrupting existing workflows. </div> <div> - Working knowledge of the client's data stack (S3-backed data lake queried via Athena, EKS/Kubernetes) and of how orchestrated pipelines feed the application — enough to collaborate with DevOps and clarify functional/non-functional requirements, without owning the analytical pipeline architecture directly. </div> <div> - Understand how orchestrated data pipelines feed the application and help define functional and non-functional requirements. </div> <div> - Lead senior developers and ensure adherence to engineering best practices and client standards. </div> <div> </div> <div> <b> MUST HAVES </b> </div> <div> - <b> 7+ years of full-stack engineering experience with proven architectural ownership </b> . </div> <div> - Strong production experience with <b> Python using FastAPI or Flask </b> . </div> <div> - Solid experience with <b> TypeScript and React </b> ; knowledge of Next.js or modern state management is a plus. </div> <div> - Experience designing and working with <b> REST APIs </b> , including migration from legacy GraphQL endpoints. </div> <div> - Hands-on experience with <b> Docker and PostgreSQL, including database migrations </b> . </div> <div> - Demonstrated experience building or maintaining <b> data-heavy applications </b> (large payloads/datasets, performance-sensitive queries at the application layer). </div> <div> - Working familiarity with <b> object-storage-backed data lakes and serverless query engines (S3 + Athena or equivalent) and with EKS/Kubernetes concepts </b> — enough to drive DevOps conversations and reason about how data reaches the application. Hands-on pipeline design not required. </div> <div> - Task orchestration awareness: familiar with what a DAG-based orchestrator like Airflow does, or able to pick it up quickly from experience with a comparable engine. Won't be managing Airflow itself. </div> <div> - Strong command-line proficiency in <b> Mac/Linux environments using Bash and Makefiles </b> . </div> <div> - Practical, hands-on use of <b> AI-assisted development tools (e.g., Claude Code) </b> , paired with the critical judgment to challenge AI output when it compromises long-term maintainability — including the leadership presence to set the standard for how the team uses AI tooling responsibly (e.g., flagging risky AI-driven shortcuts during PR review). </div> <div> - Strong soft skills: the ability to hold and defend a technical opinion — challenging a stakeholder's or a tool's proposed "quick fix" with sound reasoning in pursuit of a solution that scales and is maintainable long-term, while still being pragmatic enough to ship. </div> <div> - Upper-intermediate English level. </div> <div> </div> <div> <b> NICE TO HAVES </b> </div> <div> - Production experience with Athena, S3-based data lakes, or Airflow. </div> <div> - Experience building AI features using AWS Bedrock, LangChain, Pydantic AI, or similar technologies. </div> <div> - Experience with monorepo tooling such as Nx or modern package managers including Poetry, UV, or Yarn. </div> <div> - Experience with Redis or other NoSQL and caching technologies. </div> <div> - Exposure to OLAP-style analytics tools (Trino/Presto, ClickHouse, SageMaker) as a plus, not a requirement. </div> <div> - Experience working with marketing data structures, campaign manage