Backend & MLOps Engineer

About the client
We are in search of a Backend / ML Operations Engineer who has the drive to be part of a founding team tackling a difficult but meaningful problem. You’ll be responsible for building and scaling the backbone of our AI platform—from robust APIs and data pipelines to distributed task orchestration and deployment infrastructure. Beyond development, you will work closely with co-founders on all facets of the startup as we grow  in the coming years.

What You'll Do:

• Backend services & APIs: Architect and implement scalable services using FastAPI, ensuring high performance, reliability, and maintainability.


• Distributed processing & workflows: Build task queues and background job systems with Celery and Redis to handle complex AI/LLM workflows.


• Infrastructure & DevOps: Own our AWS cloud environment, designing secure, resilient infrastructure with containerization (Docker), and orchestration (ECS/EKS).


• MLOps best practices: Implement CI/CD pipelines, automated testing, observability, and monitoring to ensure smooth experimentation-to-production deployment.


• Data & LLM pipelines (Nice to have): Support proprietary data ingestion, preprocessing, and orchestration into LLM workflows (RAG, evaluation, benchmarking,
  agent pipelines).


• System reliability & scalability: Optimize performance, manage resource scaling, and enforce backend and DevOps best practices.

What You Need

• Engineering excellence: Strong experience in backend engineering with Python, FastAPI, Celery, Redis, AWS, Docker, and related DevOps tooling.


• Infrastructure mindset: Deep understanding of distributed systems, monitoring, scaling, and backend best practices.


• MLOps fluency: Familiarity with model deployment, experiment tracking, model registries, and feedback loops.


• LLM experience: Exposure to workflows using GPT, Claude, Gemini, or other foundation models (through professional or personal projects).


• Independent thinking: Ability to make sound technical decisions, troubleshoot complex issues, and deliver results with minimal guidance.


• Collaboration skills: Clear, thoughtful communication and a willingness to both give and receive feedback.


• Ownership & drive: Comfortable wearing many hats and building core systems from scratch in a fast-paced startup environment.


• Regional focus: This role is for candidates based in the Philippines, as we are building our regional engineering team here.