Gen AI Platform Engineer

About the job Gen AI Platform Engineer

We are looking for a Generative AI Platform Engineer to design, build, and scale enterprise-grade AI platforms and APIs that enable the adoption of large language models and generative AI capabilities across the organization. This role is focused on platform engineering, not just model experimentation - you will be responsible for building robust, secure, and highly scalable systems that integrate with leading cloud-based AI services. You will work closely with software engineers, data scientists, and product teams to deliver reusable AI infrastructure, developer-friendly APIs, and production-ready solutions.

Key Responsibilities

Design and build scalable Generative AI platforms, services, and APIs for internal and external consumers

Develop and maintain high-performance backend services using Python and one or more of C++, C#, or Java

Integrate and operationalize LLM and foundation model APIs, including: Azure OpenAI Google Vertex AI AWS Bedrock

Build abstraction layers and orchestration logic to support multiple model providers and deployments

Design RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance

Implement platform capabilities such as: Prompt management and versioning Model routing and fallback strategies, Observability, logging, and monitoring Cost and usage tracking Deploy and operate services on Google Cloud Platform (GCP), leveraging managed services where appropriate Support CI/CD, infrastructure-as-code, and production operations

Contribute to platform architecture decisions and engineering best practices Required 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 What Were Looking For

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