About Exponentia.ai :

Exponentia.ai is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the US, UK, UAE, India, and Singapore, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations.

We are proud partners with global technology leaders such as Databricks, Microsoft, AWS, and Qlik, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.

Awards & Recognitions :

- Innovation Partner of the Year - Databricks, 2024

- Digital Impact Award, UK - 2024 (TMT Sector)

- Rising Star - APJ Databricks Partner Awards 2023

- Qlik's Most Enabled Partner - APAC

About the Role :

We are seeking a Solution Architect - AWS AI/ML to lead the end-to-end architecture of an enterprise-scale Propensity Model Development Platform on AWS. The role involves designing scalable data and ML architectures, defining MLOps and governance frameworks, and guiding cross-functional teams to deliver secure, reliable, and business-impacting AI solutions.

The ideal candidate will combine strong AWS architecture expertise with data engineering, machine learning, stakeholder management, and solution governance capabilities to drive successful platform implementation.

Key Responsibilities :

Solution Architecture & Design :

- Translate business objectives and propensity-model use cases into scalable solution architectures and implementation roadmaps.

- Define target-state architecture covering data ingestion, transformation, feature engineering, model training, deployment, and consumption.

- Design secure, scalable, and cost-optimized AWS-based AI/ML platforms.

AWS Data & ML Platform Architecture :

- Architect solutions using AWS S3, Glue, Athena, Redshift, SageMaker, Lambda, IAM, Lake Formation, CloudWatch, EventBridge, and related services.

- Define architecture for batch and real-time model scoring, feature stores, model registries, and monitoring frameworks.

- Establish integration patterns, APIs, and environment management strategies.

MLOps, Security & Governance :

- Define CI/CD and MLOps approaches for model development, deployment, and lifecycle management.

- Establish architectural guardrails for security, IAM, encryption, networking, auditability, lineage, and compliance.

- Ensure adherence to responsible AI, governance, and data management best practices.

Technical Leadership & Stakeholder Engagement :

- Lead architecture reviews and provide technical direction to Data Scientists, ML Engineers, Data Analysts, and client engineering teams.

- Own architecture blueprints, solution diagrams, interface specifications, and technical documentation.

- Facilitate workshops, align stakeholders, and drive technical decision-making across teams.

Risk Management & Delivery Support :

- Identify architectural risks, dependencies, assumptions, and mitigation strategies.

- Support implementation, deployment, troubleshooting, and performance optimization activities.

- Ensure solutions meet reliability, scalability, maintainability, and cost objectives.

Ideal Candidate Profile :

- 6 - 8 years of experience in Cloud Architecture, Data Engineering, AI/ML Solutions, or Analytics Platforms.

- Strong expertise in AWS architecture and cloud-native AI/ML solutions.

- Experience designing enterprise-scale data lakes, MLOps platforms, and machine learning ecosystems.

- Strong understanding of data governance, security, scalability, and performance optimization.

- Excellent communication, stakeholder management, and leadership skills.

Preferred Qualifications :

- Bachelor's or master's degree in computer science, Engineering, Information Technology, Data Science, or a related discipline.

- AWS Certified Solutions Architect or equivalent AWS certification.

- Experience delivering customer analytics, propensity, churn, recommendation, cross-sell, upsell, or next-best-action solutions.

- Exposure to BFSI, Insurance, or other regulated industries.

- Knowledge of Explainable AI, Model Risk Management, and Responsible AI frameworks.

- Experience working in Agile/Scrum delivery environments.

Why Join Exponentia.ai?

- Innovate with Purpose : Opportunity to create pioneering AI solutions in partnership with leading cloud and data platforms.

- Shape the Practice : Build a marquee capability from the ground up with full ownership.

- Work with the Best : Collaborate with top-tier talent and learn from industry leaders in AI.

- Global Exposure : Be part of a high-growth firm operating across US, UK, UAE, India, and Singapore.

- Continuous Growth : Access to certifications, tech events, and partner-led innovation labs.

- Inclusive Culture : A supportive and diverse workplace that values learning, initiative, and ownership.