AI/ML Architect, Java Architect / Solution Architect

Location: Chennai/Bangalore/Pune/Hyderabad

• Design and review machine learning architecture pipelines end-to-end
  

• Architect scalable models using tools like TensorFlow, PyTorch, Scikit-learn
  

• Drive data strategy, feature stores, model lifecycle (training, deployment, monitoring)
  

• Collaborate with data engineering and product teams to align technical goals
  

• Define standards for MLOps, model governance, and responsible AI
  

• 8+ years in ML/DL, data science, or AI-related roles
  

• Expertise in Python, ML frameworks, distributed computing (Spark, Dask)
  

• Cloud-native ML deployment on AWS SageMaker, Azure ML, GCP Vertex AI
  

• Knowledge of Kubeflow, MLFlow, Airflow, Docker/K8s for ML pipelines
  

• Strong grasp of ML lifecycle management, monitoring, and retraining
  

• Own the technical design for backend systems built on Java / Spring Boot
  

• Create solution blueprints, architecture documents, and design patterns
  

• Guide teams on microservices, containerization, API design, and DevOps
  

• Conduct code reviews, architecture assessments, and risk mitigation
  

• Collaborate with product and infrastructure teams for seamless delivery
  

• Proficiency in Java 11+/Spring Boot, RESTful APIs, ORM frameworks
  

• Experience with Kubernetes, Docker, messaging systems (Kafka, RabbitMQ)
  

• Strong grasp of cloud-native development (AWS, Azure, GCP)
  

• In-depth understanding of microservices, DDD, clean architecture
  

• Performance tuning, scalability, and reliability design
  

• Analyze requirements and design technical solutions across platforms
  

• Create architecture roadmaps for applications, integrations, and cloud infrastructure
  

• Lead POCs, architecture evaluations, and tech selection
  

• Align solutions with enterprise architecture standards and security best practices
  

• Act as a technical bridge between stakeholders, developers, and leadership
  

• Strong experience in application architecture, APIs, and system integration
  

• Familiarity with cloud platforms (Azure, AWS, GCP)
  

• Solid understanding of data architecture, DevOps practices, CI/CD pipelines
  

• Experience with design patterns, scalability, and resilience planning
  

• Great communication, documentation, and stakeholder management skills