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ID71009
Developer
Python / React.js
Engineering
Python / React.js
Python
React
AWS
Full-time
- Argentina,
- Brazil,
- Colombia,
- Mexico,
- Guatemala
- LATAM,
- Argentina,
- Brazil,
- Colombia,
- Mexico,
- Guatemala
7+ years of experience
5+ years
Senior Lead Architect C-level
Remote
TECH STACK
Python
React
AWS
TypeScript
Docker
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 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.
- Team Leadership: Guide senior developers and ensure alignment with the client's 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
- 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
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Welcome to AgileEngine!
Have any questions?
What is the work format and schedule?
We are a remote-first company, so all our positions are remote. Schedules are flexible, but the main requirement is to have an overlap with your client’s schedule to ensure smooth collaboration. Specific details depend on the project and are discussed during the interview process.
What level of English is required?
We look for Upper-Intermediate (B2) proficiency or higher. Since you will be collaborating with international teams and global clients (including Fortune 500 companies), English is a part of your daily work.
Does AgileEngine provide work equipment?
It depends on your location. We provide equipment in Ukraine, Poland, Argentina, Colombia, Mexico, Brazil, Guatemala, Portugal, Spain, and India. In the USA, equipment is usually provided by the client; otherwise, you will be expected to use your own setup.
What opportunities for professional growth do you offer?
We support continuous growth through personalized development paths tailored to each expert. Also, you can expect:
- An annual learning and development budget
- Internal workshops, tech talks, and mentorship programs
- Opportunities to switch projects or grow into new roles over time
What does a typical team look like, and what tools do you use?
Teams vary by project, but you’ll usually work with a mix of experts across different fields, along with a delivery or project manager who supports collaboration and onboarding.
For day-to-day work, teams commonly use tools like Jira and Google Workspace, along with communication platforms such as Google Chat. Depending on the client, you may also work with Slack, Confluence, Notion, or similar tools.
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