Offer summary

Qualifications:

Strong programming proficiency in Python and Typescript/React., Experience with backend web services and cloud provider managed services., Familiarity with containerization, CI/CD concepts, and application monitoring., Knowledge of service integrations, distributed tasks, and data engineering is a plus..

Key responsibilities:

Develop and maintain full stack applications using Python and React.

Build and deploy backend web services and manage cloud infrastructure.

Implement CI/CD pipelines and ensure application logging and monitoring.

Collaborate with cross-functional teams to integrate services and optimize performance.

Job description

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (19000+ experts across 33 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

Strong programming proficiency in Python (OOP, Async/Await, etc.).
Strong programming proficiency in Typescript/React and FE development experience.
Previous experience building backend web services (FastAPI or similar).
Previous experience with cloud provider managed services (AWS, Azure) and IaC (Terraform).
Previous experience with containerization and container app deployments (Docker, Kubernetes, etc.).
Previous experience with CI/CD concepts and tooling (Github Actions, Gitlab CI, etc.).
Previous experience with application logging/monitoring (Sentry, ELK stack, Datadog, etc.).
Strong knowledge with service integrations and protocols (REST, streams, web sockets, webhooks).
Strong knowledge with distributed tasks using queues and consumers, pub/sub architecture

Qualifications

Must have Skills: React (Strong), Python (Expert), Docker (Strong), AWS.

Nice to Have Skills:

Previous experience building a user-facing GenAI/LLM software application.
Previous experience with vectors and embeddings (pgvector, chromadb).
Knowledge of LLM RAG/Agent core concepts and fundamentals.
Previous experience with MLOps/LLMOps tools (Arize Phoenix, LangSmith, MLFlow, W&B, etc.).
Data engineering experience (data modeling, data pipelines, event streaming, etc.).

Required profile