AI Platform Architect

1. Architecture & Design Define and own the HLD and LLD documentation for the AI platform on AWS and Databricks. Design scalable, secure, and cost-optimized architectures for data processing, feature engineering, model training, and inference pipelines. Establish standards, patterns, and best practices for platform components including Lakehouse architecture, MLOps, and data governance.

2. Platform Engineering Architect and guide implementation of Databricks workspace setup, clusters, Unity Catalog, Delta Lake, workflows, and model serving. Lead the integration of the platform with key internal systems such as Radar, EDP (Enterprise Data Platform), and other upstream/downstream applications. Define API, event, and data exchange patterns for cross-system interactions.

3. Cloud & Infrastructure Design cloud-native solutions leveraging AWS services such as S3, IAM, Lambda, EMR, Glue, ECS/EKS, Step Functions, CloudWatch, and networking components. Ensure platform scalability, reliability, observability, and high availability. Oversee IAM policies, security controls, and data protection mechanisms.

4. MLOps & AI Capabilities Define architecture for end-to-end ML life cycle including model development, experiment tracking, CI/CD, deployment, and monitoring. Evaluate technologies and frameworks for versioning, lineage, feature stores, and ML governance. Guide teams in implementing reusable ML workflows and enterprise-grade AI components.

5. Stakeholder Collaboration Work closely with engineering teams, product owners, data scientists, and security/infra teams to align technical design with business goals. Provide architectural guidance during development, testing, and production rollout. Review technical deliverables and ensure adherence to architectural guidelines.

6. Documentation & Governance Produce detailed and clear technical documentation (HLDs, LLDs, architecture diagrams, integration specs). Participate in architecture review boards and ensure compliance with enterprise standards. Support capacity planning, cost optimization, and risk assessments.

We are seeking an experienced AI Platform Architect to lead the design and architecture of our next-generation AI platform built on AWS and Databricks. This role involves defining the High-Level Design (HLD) and Low-Level Design (LLD) for the end-to-end platform, driving integration with enterprise systems such as Radar, EDP, and other data/AI services within the ecosystem. The ideal candidate brings a strong blend of cloud architecture, data engineering, and AI/ML platform experience, along with the ability to translate business requirements into scalable and secure technical solutions., 8-12+ years of experience in data/AI engineering or cloud architecture roles. Strong expertise with Databricks (Delta Lake, Unity Catalog, MLflow, Workflows). Deep understanding of AWS cloud architecture and services relevant to data/AI workloads. Hands-on experience designing large-scale distributed data systems and AI/ML pipelines. Demonstrated ability to create HLD/LLD documents and architecture diagrams. Experience integrating platforms across complex enterprise ecosystems. Strong knowledge of data governance, security, and best practices for cloud-native systems. Proficiency in Python/SQL and familiarity with CI/CD, Terraform/IaC is a plus., Databricks Architect or AWS Solutions Architect certification. Experience with enterprise-scale AI platforms and MLOps frameworks. Knowledge of event-driven architectures and service mesh patterns. Experience collaborating in multi-disciplinary, global teams.

Soft Skills Strong communication and documentation skills. Ability to work independently and influence architectural decisions. Problem-solving mindset with attention to detail. Ability to balance long-term vision with immediate business priorities.

If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often Shortlisted within 48 hours.