The Role
Lead design and delivery of containerized Python and React applications for a large-scale marketing analytics platform. Own architecture and code quality, integrate AI and data-heavy features, collaborate with DevOps on AWS data stack and EKS, review PRs, and mentor senior engineers to ensure scalable, maintainable solutions in ambiguous environments.
Summary Generated by Built In
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.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Technical Lead 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. You will also help shape solutions in an often ambiguous, fast-moving environment by gathering context, defining problems, and turning loosely defined needs into scalable, maintainable technical solutions.
WHAT YOU WILL DO
- Code Governance: Review all PRs and enforce code quality standards, preventing "spaghetti code" and scope creep.
- System Architecture: Design and deploy containerized applications using REST APIs.
- Technical Integration: Embed complex logic, AI features, and outputs from data-heavy backends into the platform without disrupting existing workflows.
- AWS Ecosystem Engagement: Working knowledge of the 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.
- Team Leadership: Guide senior developers and ensure alignment with established engineering practices.
MUST HAVES
- 7+ years of full-stack engineering experience with a strong track record of architectural ownership.
- Strong production experience with Python (FastAPI or Flask).
- Solid TypeScript/React experience (Next.js or modern state management is a plus).
- Comfortable with REST APIs, including migrating away from legacy GraphQL endpoints where needed.
- Docker and relational databases (PostgreSQL), including comfort with database migrations.
- Demonstrated experience building or maintaining data-heavy applications (large payloads/datasets, performance-sensitive queries at the application layer).
- AWS Ecosystem: working familiarity with object-storage-backed data lakes and serverless query engines (S3 + Athena or equivalent) and with EKS/Kubernetes concepts — enough to drive DevOps conversations and reason about how data reaches the application. Hands-on pipeline design not required.
- 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.
- Highly comfortable in Mac/Linux terminal-centric environments (Bash, Makefiles).
- Practical, hands-on use of AI-assisted development tools (e.g., Claude Code), 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).
- 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.
- Comfort with ambiguity (mandatory): work is frequently ad hoc and underspecified. This role requires defining the problem — gathering context, identifying constraints, and framing the work — before solving it, rather than waiting for a specification. Experience limited to well-specified work executed through agent workflows is not a fit.
- Upper-intermediate English level.
NICE TO HAVES
- Direct production experience with Athena, S3-based data lakes, or Airflow.
- Production AI features using AWS Bedrock, LangChain, Pydantic AI, or similar.
- Monorepo tooling (Nx) or modern package managers (Poetry, UV, Yarn).
- NoSQL/caching layers (Redis).
- Exposure to OLAP-style analytics tools (Trino/Presto, ClickHouse, SageMaker) as a plus, not a requirement.
- Experience with marketing data structures, campaign management APIs, or digital advertising metrics.
PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
Skills Required
- 7+ years of full-stack engineering experience with architectural ownership
- Production experience with Python (FastAPI or Flask)
- TypeScript and React experience (Next.js a plus)
- Strong experience with REST APIs and migrating from legacy GraphQL when needed
- Docker containerization experience
- Relational databases (PostgreSQL) including database migrations
- Experience building/maintaining data-heavy, performance-sensitive applications
- Familiarity with AWS data stack concepts (S3-backed data lakes, Athena) and EKS/Kubernetes
- Awareness of DAG-based orchestration (Airflow) or comparable engines
- Comfortable in Mac/Linux terminal-centric environments (Bash, Makefiles)
- Practical hands-on use of AI-assisted development tools (e.g., Claude Code) with critical judgment
- Ability to lead teams, enforce code governance, and defend technical decisions
- Comfort with ambiguity and ability to define problems and frame solutions
- Upper-intermediate English
- Direct production experience with Athena, S3 data lakes, or Airflow
- Production AI features using AWS Bedrock, LangChain, Pydantic AI or similar
- Monorepo tooling (Nx) or modern package managers (Poetry, UV, Yarn)
- NoSQL/caching layers (Redis)
- Exposure to OLAP tools (Trino/Presto, ClickHouse, SageMaker)
- Experience with marketing data structures, campaign management APIs, or advertising metrics
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The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
