dentsu AustriaRemote
Backend Software Engineer (Python)
United States of America
Full Time
1 week ago
$136,000 - $190,000 USD
Visa Sponsor
Key skills
PythonNoSQLAIOpenAIAnthropicAirflowPostgresMongoDBRedisCachingCI/CDCollaboration
About this role
Dentsu is a leading global media agency, shaping the future of content, advertising, and audience engagement across platforms. The role of backend software engineer involves designing, building, and deploying AI systems capabilities that drive business value and enhance global products, working closely with cross-functional teams.
Responsibilities:
- API System Design: Architect, develop, and test production grade Python APIs for media products
- Orchestration: Support data pipelines, background jobs, and distributed systems that interact with AI models
- Collaboration: Work with technical stakeholders to design scalable systems for easy development, deployment, and monitoring of systems. Create implementation plans teams can work against to achieve product goals
- Deployment & Scaling: Design and robust systems for long running processes. Databases, caching, retry logic, fall back behavior, etc. Ensure errors are routed for proper triaging
- Robust Testing: Design/maintain high quality automated tests and manual stress/quality testing frameworks for AI systems
- Ethics & Compliance: Consider data governance and cyber security practices. Ensuring fairness, transparency, and compliance with regulations
Requirements:
- Bachelor's degree in computer science, engineering, or related field
- 2-4 years experience designing, maintaining, and testing enterprise grade RestAPIs
- Expert Python skills, deep experience with concurrent systems (asyncio, tornado, celery etc)
- Demonstrated production experience complex long running processes that present and collect data
- Experience with workflow orchestration tools (e.g., Prefect, Airflow, Dagster)
- Experience with data persistence. Redis, Postgres, NoSQL, MongoDB, etc
- Demonstrated production experience with monitoring enterprise systems
- Ability to architect systems that are maintainable and extendable. Balancing over engineering while preparing for future requests
- Familiarity with LLMs – their APIs, performance challenges, and how to mitigate those (OpenAI, Anthropic, Cohere, etc.)
- Proficiency with version tracking
- Knowledge of containerization, DevOps tools, and CI/CD pipelines