Integrate GenAI model APIs (OpenAI, Bedrock, Gemini) into production systems

Design and maintain backend services using FastAPI

Manage authentication flows (Keycloak, SSO, LDAP)

Build and optimize RAG pipelines, embeddings, and caching structures

Deploy and operate AI microservices on Kubernetes (scaling, configuration, rollouts)

Own DevOps operations for AI services (CI/CD, container builds, configs, secrets)

Ensure performance, reliability, and security of AI backend components

Work closely with business teams to clarify user needs and translate them into backend capabilities

Collaborate with product, data, and frontend teams to deliver AI-driven features

Continuously evaluate emerging GenAI technologies to improve system efficiency

DESIRED SKILLS AND EXPERIENCE

3-4 years of experience in related field

Bachelor's degree in a related technical field

Strong experience with Python and FastAPI

Good understanding of GPT/LLM APIs and GenAI solution patterns

Hands-on experience with Docker and Kubernetes

Experience with CI/CD (Azure DevOps or similar)

Solid knowledge of RESTful APIs and microservice architecture

Experience with MongoDB, Redis, and relational databases

Familiar with event-driven architectures

Nice to have: Elastic/Kibana

Nice to have: Kafka/RabbitMQ

Nice to have: Exposure to AI MLOps concepts

Strong problem‑solving and communication skills

Strong willingness to learn new technologies