GenAI Engineer
We are seeking a GenAI Engineer to lead the end-to-end development, deployment and operation of enterprise-grade AI-powered applications. The role combines backend engineering, LLM integration, cloud infrastructure and AI platform operations to deliver scalable GenAI solutions in production environments. You will work closely with AI/DS, Product and DevOps teams to build and scale AI-driven applications, ensuring reliability, observability, performance optimization and operational excellence across the full AI SDLC. The role also includes contributing to GenAI-assisted development practices, scaling enterprise AI SDLC processes, supporting AI Beauty Chat initiatives through agentic micro-pod delivery models and performing System Steward responsibilities across AI platform initiatives.
Responsibilities
- Design, develop, deploy and maintain backend services for AI/LLM-powered applications
- Own E2E delivery of GenAI features from implementation to production support
- Integration and operation of LLM APIs (e.g. OpenAI) in enterprise production environments
- Development of APIs, orchestration layers and microservices supporting agentic AI workflows
- Optimization of LLM systems for latency, resiliency, retries, fallbacks and cost efficiency
- Implementation of CI/CD pipelines, observability, monitoring and logging for AI services
- Collaboration with AI/DS, Product, DevOps and platform teams to streamline delivery and improve reliability
- Work with Azure cloud environments and distributed systems (Redis, Kafka, SQL/NoSQL)
- Support for MCP integrations, agentic memory initiatives and AI orchestration frameworks
- Drive GenAI-assisted development practices and scale AI SDLC processes
- Contribution to AI Beauty Chat delivery through agentic micro-pod execution models
- Execution of System Steward responsibilities in agentic micro-pods
Requirements
- 2+ years of Python backend engineering experience
- Expertise in building and operating production-grade GenAI/LLM applications end-to-end
- Hands-on experience with OpenAI or other LLM APIs in production
- Proficiency in prompt engineering, agentic workflows and orchestration patterns
- Capability to handle LLM operational challenges: latency, retries, fallbacks, observability and cost optimization
- Strong understanding of scalable backend and distributed system architecture
- Skills in CI/CD, DevOps workflows and Azure cloud environments
- Background in applying GenAI across the SDLC (AI-assisted development, testing, deployment and delivery workflows)
- Working knowledge of SQL/NoSQL databases, Redis and Kafka
- Familiarity with Databricks and MCP
- Excellent English communication skills (B2+ level)
