Senior AI Engineer

Job ID: AIENG- 1125

Job Location: Chennai, Coimbatore, Bangalore India

Work Mode: Hybrid

Years of Experience: 7-10 Yrs

Educational qualifications: Bachelors in computer science engineering, AI/ ML, Electrical

Engineering, or related field (Masters or PhD often preferred)

Joining Bonus for Immediate joiners

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

7+ total experience in software development in the areas of Java, AI/ML/LLM, Agentic Ai.

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)

Experience in Healthcare domain, preferably targeting USA

Experience handling US clients independently, very good communication and interpersonal skills

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 (5+ years relevant experience). Master’s in engineering with focus on AI/ML is highly preferred

Benefits

Industry Competitive Compensation package

Exposure to work on advanced technologies and excellent career growth opportunities both technical

and organization level

Paid Time off (EL, SL, CL) , Health Insurance coverage

Hybrid /Remote Work From Home

Yearly Bonus and Performance Incentives

Joining Bonus for Immediate joiners

About us

At Deevita, we believe in Intelligent Solutions. Better Care. Healthier Lives. Our journey began with a vision

to transform healthcare, pharmacy, and life sciences through secure, intelligent, and scalable technology.

Today, we deliver end-to-end digital transformation solutions that empower organizations to innovate, adapt,

and thrive in a rapidly evolving world.

From AI and advanced analytics to data engineering, SaaS platforms, visualization, and cloud

modernization, we help startups, healthcare providers, and pharma companies unlock the full potential of

their data and technology. For enterprises, we go further – enabling Agentic AI solutions that create

intelligent agents, train models for specific business needs, and manage the complete machine learning lifecycle. Our mission is simple yet powerful: to improve decision-making, accelerate innovation, and

reimagine care delivery – creating healthier lives for all