Responsibilities-Develop and maintain backend microservices using Python, Java and Spring Boot-Build and integrate APIs (both GraphQL and REST) for scalable service communication-Deploy and manage services on Google Cloud Platform (GKE)-Work with Google Cloud Spanner (Postgres dialect) and pub/sub tools like Confluent Kafka (or similar)-Automate CI/CD pipelines using Git

Hub Actions and Argo CD-Design and implement AI-driven microservices-Collaborate with Data Scientists and MLOps teams to integrate ML Models-Implement NLP pipelines -Enable continuous learning and model retraining workflows using Vertex AI or Kubeflow on GCP-Enable observability and reliability of AI decisions by logging model predictions, confidence scores and fallbacks into data lakes or monitoring tools Required Qualifications-5+ years of backend development experience with Java and Spring Boot-2+ years working with APIs (GraphQL and REST) in microservices architectures-2+ years' experience integrating or consuming ML/AI models in production environments (, Tensor

Flow Serving or Vertex AI Endpoints) -Experience working with structured and unstructured data (, clinical documents, NLP processing). -Familiarity with ML model lifecycle - from data ingestion, training, deployment, to real-time inference (MLOPS) -2+ years hands-on experience with GCP, AWS, or Azure-2+ years working with pub/sub tools like Kafka or similar-2+ years' experience with databases (Postgres or similar)-2+ years' experience with CI/CD tools (Git

Hub Actions, Jenkins, Argo CD,



or similar)Preferred Qualifications-Hands-on experience with Google Cloud Platform-Familiarity with Kubernetes concepts; experience deploying services on GKE is a plus-Strong understanding of microservice best practices and distributed systems-Familiarity with Vertex AI, Kubeflow or similar AI platforms on GCP for model training and serving -Understanding of GenAI use cases, LLM prompt engineering and agentic orchestration (, transformers) -Experience deploying Python-based ML Services into Java microservice ecosystems (via REST, gRPC or sidecar patterns) -Knowledge of claim adjudication, Rx domain logic or healthcare specific workflow automation Education Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience)Responsibilities-Develop and maintain backend microservices using Python, Java and Spring Boot-Build and integrate APIs (both GraphQL and REST) for scalable service communication-Deploy and manage services on Google Cloud Platform (GKE)-Work with Google Cloud Spanner (Postgres dialect) and pub/sub tools like Confluent Kafka (or similar)-Automate CI/CD pipelines using Git

Hub Actions and Argo CD-Design and implement AI-driven microservices-Collaborate with Data Scientists and MLOps teams to integrate ML Models-Implement NLP pipelines -Enable continuous learning and model retraining workflows using Vertex AI or Kubeflow on GCP-Enable observability and reliability of AI decisions by logging model predictions,



confidence scores and fallbacks into data lakes or monitoring tools Required Qualifications-5+ years of backend development experience with Java and Spring Boot-2+ years working with APIs (GraphQL and REST) in microservices architectures-2+ years' experience integrating or consuming ML/AI models in production environments (, Tensor

Flow Serving or Vertex AI Endpoints) -Experience working with structured and unstructured data (, clinical documents, NLP processing). -Familiarity with ML model lifecycle - from data ingestion, training, deployment, to real-time inference (MLOPS) -2+ years hands-on experience with GCP, AWS, or Azure-2+ years working with pub/sub tools like Kafka or similar-2+ years' experience with databases (Postgres or similar)-2+ years' experience with CI/CD tools (Git

Hub Actions, Jenkins, Argo CD, or similar)Preferred Qualifications-Hands-on experience with Google Cloud Platform-Familiarity with Kubernetes concepts; experience deploying services on GKE is a plus-Robust understanding of microservice best practices and distributed systems-Familiarity with Vertex AI, Kubeflow or similar AI platforms on GCP for model training and serving -Understanding of GenAI use cases, LLM prompt engineering and agentic orchestration (, transformers) -Experience deploying Python-based ML Services into Java microservice ecosystems (via REST, gRPC or sidecar patterns) -Knowledge of claim adjudication, Rx domain logic or healthcare specific workflow automation Education Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience)

📌 Sr. Engineer - AIML Backend (India)
🏢 IntraEdge
📍 India