Generative AI Platform Engineer
Actively Hiring
Full-time Posted 7 months ago
Responsibilities
- check_circle Design and build scalable Generative AI platforms, services, and APIs for internal and external consumers
- check_circle Develop and maintain high-performance backend services using Python and one or more of C++, C#, or Java
- check_circle Integrate and operationalize LLM and foundation model APIs, including: Azure OpenAI Google Vertex AI AWS Bedrock
- check_circle Build abstraction layers and orchestration logic to support multiple model providers and deployments
- check_circle Design RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance
- check_circle Implement platform capabilities such as:
- check_circle Prompt management and versioning Model routing and fallback strategies.
- check_circle Observability, logging, and monitoring Cost and usage tracking
- check_circle Deploy and operate services on Google Cloud Platform (GCP), leveraging managed services where appropriate Support CI/CD, infrastructure-as-code, and production operations
- check_circle Contribute to platform architecture decisions and engineering best practices
Basic qualifications
- 7+ years of professional software engineering experience
- Bachelors degree in Computer Science or a related field (Masters degree preferred)
- Strong proficiency in Python Strong experience in at least one of the following: C++, C#, or Java
- Proven experience building platforms, frameworks, and APIs (not just applications)
- Hands-on experience with Google Cloud Platform (GCP)
- Practical experience integrating with cloud-hosted AI/LLM APIs, including Azure OpenAI, Vertex AI, and/or AWS Bedrock
- Strong understanding of API design, distributed systems, and cloud-native architectures
- Experience taking systems from design through production deployment and operation
Preferred qualifications
- Experience designing multi-tenant or enterprise AI platforms
- Familiarity with MLOps or LLMOps concepts (model lifecycle, monitoring, evaluation)
- Experience with containerization and orchestration (Docker, Kubernetes)
- Knowledge of authentication, authorization, and secure API design
- Experience supporting developer platforms or internal tooling
- A platform-first mindset — you enjoy building reusable systems that enable other teams
- Strong engineering fundamentals and attention to production quality
- Comfort working across cloud services, APIs, and distributed systems
- Ability to collaborate with both technical and non-technical stakeholders
Tags & Focus Areas
Fulltime Remote Ai Data Science Generative Ai