We are seeking a seasonedSolutions Architectwho brings deep experience in architectingenterprise-grade platformsalong with a strong track record indata products and AI solutions. This role requires a strategic thinker who can bridge business goals with scalable technology architecturesleading end-to-end solution design across cloud, data, and AI ecosystems.

You will work closely with business stakeholders, data scientists, product owners, and engineering teams to conceptualize and deliver innovative products that power modern enterprises.

Key Responsibilities

• Architectscalable and secure solutions for enterprise applications, data platforms, and AI-driven products.
• Leadtechnical design sessions, ensuring alignment with business goals and platform vision.
• Defineend-to-end architecturesacross cloud (preferably Azure), data pipelines, APIs, and AI/ML models.
• Collaborate with cross-functional teams to translate requirements intoarchitectural blueprintsand technical specifications.
• Providetechnical leadershipthroughout the product lifecyclefrom discovery and PoC to deployment and optimization.
• Evaluate and recommenddata storage, processing, and ML inferencetechnologies suited to the product needs.
• Overseesolution governance, security, performance, and scalabilitystandards.
• Support pre-sales or client discussions as the technical authority on product architecture when needed.

Required Qualifications

• Bachelor's or Masters in Computer Science, Software Engineering, or a related field.
• 8+ yearsof experience in software architecture and solution design.
• Proven experience in architectingcloud-native applications and enterprise platforms.
• At least3 years of experiencein designingdata products or AI-driven applications(ML models, data lakes, model orchestration, MLOps).
• Proficient in designing microservices, APIs, and distributed systems.
• Strong knowledge ofdata architectures(data lake, data mesh, lakehouse) andAI product workflows.
• Hands-on experience withAzure, AWS, orGCP, with a preference for Azure.
• Familiarity withmachine learning frameworks(e.g., TensorFlow, PyTorch, MLflow) and moderndata engineering stacks(Spark, Databricks, Airflow).