Architect - Data & AI
BengaluruOn-siteStaff/Principal
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The post's words + ASAI's dataOn-site in Bengaluru.
OK with that?Staff/Principal level, usually 8-12 years.
You have them?No pay range in the post.
Not a repost. None of Exponentia.ai's last 15 posts was; 1 of its 18 open roles are here.
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The job post
304 words · from Exponentia.ai's careers siteKey Responsibilities
· Translate business objectives and propensity-model use cases into a target-state solution architecture and phased implementation roadmap.
· Design AWS architecture for data ingestion, storage, transformation, feature engineering, model training, batch and real-time scoring, and consumption of outputs.
· Define integration patterns, APIs, environment strategy, CI/CD approach, observability, resiliency, and disaster-recovery considerations.
· Establish architectural guardrails for IAM, encryption, networking, data access, auditability, lineage, and responsible model use.
· Guide technology selection and ensure designs meet performance, scalability, reliability, maintainability, and cost objectives.
· Lead design reviews and provide technical direction to Data Scientists, ML Engineers, Data Analysts, and client engineering teams.
· Own architecture documents, solution diagrams, interface specifications, non-functional requirements, and key technical decisions.
· Identify architecture risks, dependencies, assumptions, and mitigations; support issue resolution through build and deployment.
Skills Required
AWS,Glue,Athena,Eventbridge,Etl / Elt,Ci/Cd,Python,SQL,Containerization,Model Lifecycle Management
Role
Required Skills and Experience
| Area | Requirements |
|---|---|
| AWS architecture | Strong hands-on design experience with S3, Glue, Athena, Redshift, SageMaker, Lambda, IAM, Lake Formation, CloudWatch, EventBridge, and related AWS services. |
| Data and ML platforms | Data lake/lakehouse patterns, ETL/ELT, feature engineering, model lifecycle, batch and real-time inference, model registry, and monitoring. |
| Engineering | Python and SQL awareness, APIs, containerization, Git-based delivery, CI/CD, infrastructure-as-code concepts, and distributed systems. |
| Architecture practices | Security by design, high availability, scalability, integration architecture, performance engineering, governance, and cost optimization. |
| Leadership | Strong stakeholder management, workshop facilitation, decision-making, documentation, mentoring, and executive communication. |
Preferred Qualifications
· AWS Certified Solutions Architect certification or equivalent practical expertise.
· Experience delivering customer analytics, propensity, churn, cross-sell, upsell, next-best-action, or recommendation solutions.
· Experience in BFSI, insurance, or another regulated industry.
· Exposure to explainable AI, model risk management, and responsible AI controls.
Education/Qualification
B.Tech , M.B.A, B.E, B.CA. M.CA, MSc- Science , MSc- Data & AI , B.BA, B.E,
Job Code
11071
Designation
Architect - Data & AI
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