Sr. Engineer - AIML Backend

Job highlights

• 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 (GitHub Actions,Jenkins,Argo CD,or similar)

• 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 GitHub 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 (e.g. RESTful ML APIs, TensorFlow Serving or Vertex AI Endpoints)
• Experience working with structured and unstructured data (e.g. Rx Claim metadata, 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 (GitHub 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 (e.g. LangChain, 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
Bachelors degree or equivalent experience (High School Diploma and 4 years relevant experience)