Senior Solution Architect - Data Science & AI

Job highlights

• 15+ years in software engineering and solution architecture with expertise in cloud-native SaaS, AI/ML integration, microservices, and data platforms like Azure, Databricks, BigQuery
• Design and deliver scalable AI-driven cloud-native digital products, lead architecture for SaaS solutions, implement CI/CD pipelines, and mentor technical teams

Job Summary

We are looking for a Senior Solution Architect with strong hands-on expertise in designing, building, and delivering scalable Data and AI-driven Digital products on cloud and data platforms.

This is a hands-on technical leadership role and you will be part of Data Science and AI Team and work closely with engineering and product teams to architect robust, scalable, and production-ready systems, and play a key role in scaling AI-based solutions to the enterprise level.

What you can look forward as Senior Solution Architect - Data Science AI:

Responsibilities Solution Architecture, Design and Delivery

• Design end-to-end architecture for cloud-native Digital products powered by AI/ML.

• Define scalable, secure, and high-performance system architectures.

• Create architecture blueprints, design patterns, and technical specifications.

• Ensure solutions are aligned with best practices for multi-tenancy, scalability and robustness.

• Drive the technical design and implementation of SaaS products from concept to production.

• Provide hands-on guidance in critical components and complex problem-solving.

• Ensure robust integration across services, APIs, and data systems.

Cloud Platform Expertise

• Architect and implement solutions on Azure/AWS with strong cloud-native principles.
• Design and optimize microservices, containerized deployments (Docker/Kubernetes), and serverless architectures.
• Establish CI/CD pipelines and DevOps practices for continuous delivery.

Data AI Platform Integration

• Design and integrate scalable data platforms (data lakes, warehouses, lakehouses).
• Enable efficient data pipelines and feature engineering workflows.
• Support deployment and integration of AI/ML models into production (MLOps practices).
• Work with structured and unstructured data at scale.

Team Building

• Build and Mentor the team to deliver high quality technical solutions meeting the organizations expectations
• Actively participate in reskilling of the team to the changing technical landscapes
• Support the management during goal setting, performance reviews and appraisal processes

Required Qualifications

• 15+ years of experience in software engineering and solution architecture.
• Proven track record of designing and delivering SaaS products in production environments.
• Strong expertise in cloud platforms (Azure or AWS) and cloud-native architectures.
• Solid experience with microservices, REST APIs, distributed systems design.
• Hands-on experience with data platforms (e.g., Azure, Databricks, BigQuery, Redshift).
• Experience deploying and integrating AI/ML solutions into applications.
• Proficiency in Python, Java, or similar programming languages.
• Strong understanding of DevOps, CI/CD, Docker, Kubernetes.

Preferred Qualifications

• Experience in Applied AI / Generative AI / LLM-based applications.
• Familiarity with MLOps frameworks and tools (MLflow, Kubeflow, Airflow).
• Experience with real-time/streaming data systems (Kafka, Spark Streaming, Flink).
• Exposure to multi-tenant SaaS architecture and subscription-based models.
• Understanding of data governance, compliance, and security frameworks.

Contact

Veerabrahmam Darukumalli