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Sr. Engineer - AIML Backend 20514 Pune, NA 8/5/2025 7:38:00 PM

Engineering
FTE - IntraEdge

Job Description

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 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
 Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience)

 

Job Requirements

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 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
 Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience)