Senior Software Engineer, Backend – AI Platform
Build and operate reliable backend services, APIs, data systems, and asynchronous workflows powering AI Platform products. The role requires at least five years of production backend engineering experience, strong testing and system design fundamentals, and proficiency in Python, Go, or Java.
About the job
Responsibilities
- Design, build, and maintain backend services that power AI Platform products.
- Develop production systems in Python or other modern backend languages and frameworks, emphasizing maintainability, reliability, and performance.
- Build and evolve REST APIs and/or gRPC services, including request validation, error handling, and versioning.
- Design and maintain relational and/or NoSQL data models across MySQL, PostgreSQL, DynamoDB, and Redis.
- Build and maintain asynchronous processing flows using queues and worker-based systems.
- Work on real-time streaming features, retrieval workflows, and service communication patterns supporting AI interactions.
- Write automated unit and integration tests and contribute to CI-based quality gates.
- Debug production issues across service boundaries using logs, metrics, and system reasoning.
- Collaborate with frontend, product, and AI/ML teams to define API contracts and deliver end-to-end features.
- Contribute to code reviews, system quality, and engineering standards.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- At least five years of professional backend software engineering experience in production environments.
- Strong proficiency in at least one production backend language, such as Python, Go, or Java, with the ability to work across a polyglot environment.
- Strong software engineering fundamentals, including system design, debugging, code quality, testing, and operational ownership.
- Experience building and maintaining REST APIs and/or gRPC services.
- Experience with relational databases and/or NoSQL data stores in production systems.
- Experience with asynchronous processing patterns such as queues, workers, retries, and failure handling.
- Proficiency with Docker and familiarity with modern backend development workflows.
- Strong testing discipline, including unit testing, integration testing, and mocking dependencies.
- Experience building or operating services on cloud infrastructure in production.
- Strong communication and collaboration skills across frontend, product, and AI/ML teams.
- Demonstrated depth in production systems engineering beyond scripting, framework usage, or cloud configuration.
Nice-to-haves
- AWS familiarity.
- Experience with FastAPI, Flask, Spring Boot, Go service frameworks, or equivalent.
- Experience with Redis, WebSockets, or real-time streaming systems.
- Experience with LLM/AI integration, semantic retrieval systems, or token streaming.
- Experience with observability tooling, structured logging, Sentry, or metrics systems.
- Experience in fintech or regulated domains.
Skills
Python, Go, Java, REST APIs, gRPC, MySQL, Postgres, DynamoDB, Redis, Docker, AWS, FastAPI, Flask, Spring Boot, WebSockets
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