Solution Architect – Data & AI Solutions
Skills
About the role
Job Description: Key Responsibilities:
Presales & Client Engagement
Partner with sales and industry teams to design client-ready demos, proof-of-concepts, and technical solution blueprints .
Present complex architectures in a clear, business-outcome-driven manner to both executive and technical stakeholders.
Contribute to RFP/RFI responses, solution proposals, and deal shaping .
Act as a trusted advisor in client conversations, highlighting differentiators of Data & AI Solutions.
Solution Architecture & Demo Environments
Architect distributed, scalable, and resilient data and AI platforms for presales demonstrations.
Design abstraction layers for multi-model AI orchestration , including fallback logic, dynamic model switching, and cost control.
Lead implementation of event-driven architectures using messaging frameworks (Kafka, Pulsar, SQS, etc.) and state machines.
Build reusable, industry-specific demo environments leveraging hyperscaler services and data platforms.
Observability, Security & Compliance
Define and enforce observability standards for demo and enterprise environments (logging, tracing, telemetry, real-time alerting).
Implement zero-trust security models (RBAC/ABAC, IAM, OAuth2, encryption, API gateways).
Ensure all demo and client environments meet compliance standards such as HIPAA, GDPR, SOC2 .
Cross-Functional Collaboration
Work with Product, Data Science, Engineering, and Governance teams to align demos with business/regulatory needs.
Collaborate with IMUs (verticals) to build domain-specific demo templates (e.g., Insurance claims, Healthcare payment integrity, Banking KYC/fraud, Retail personalization).
Provide hands-on support to engineering teams during delivery, troubleshooting, and performance tuning .
Innovation & Technical Leadership
Stay ahead of hyperscaler advancements, AI/ML frameworks, and orchestration patterns .
Drive technical due diligence, PoCs, and vendor/platform evaluations .
Create technical artifacts (architecture diagrams, design patterns, runbooks).
Mentor presales engineers and junior architects in solution design and client presentation skills.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Certifications preferred:
Cloud (AWS, Azure, GCP).
Kubernetes / CNCF ecosystem.
Architecture frameworks (TOGAF, SAFe).
Skills & Experience
Must-Have Skills & Experience
15+ years in software architecture, presales engineering, or enterprise data/AI platform design.
Hands-on expertise in at least two hyperscaler platforms :
Azure (Fabric, Synapse, Data Factory, Azure ML, Power BI).
AWS (Redshift, Glue, S3, SageMaker, Lake Formation).
GCP (BigQuery, Dataplex, Vertex AI, Pub/Sub).
Proven experience architecting distributed systems, microservices, and scalable AI/ML platforms .
Strong knowledge of Data Governance, Data Quality, Metadata, Lineage, and DataOps .
Expertise in event-driven systems and asynchronous workflows.
Hands-on with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK).
Advanced programming with Python (async), TypeScript/JavaScript, or Go .
Familiarity with Kubernetes, service mesh (Istio), serverless design patterns .
Experience with CI/CD automation, GitOps, Terraform, Helm .
Strong presentation, storytelling, and client engagement skills.
Preferred Skills
Experience with multi-tenant SaaS platforms and usage-based billing.
Familiarity with data mesh, knowledge graphs, and semantic interoperability .
Knowledge of frontend architecture patterns (micro-frontends, data visualizations).
Experience building presales demo or sandbox environments .
Exposure to agentic AI concepts and LLM-based orchestration .
Responsibilities: Key Responsibilities:
Presales & Client Engagement
Partner with sales and industry teams to design client-ready demos, proof-of-concepts, and technical solution blueprints .
Present complex architectures in a clear, business-outcome-driven manner to both executive and technical stakeholders.
Contribute to RFP/RFI responses, solution proposals, and deal shaping .
Act as a trusted advisor in client conversations, highlighting differentiators of Data & AI Solutions.
Solution Architecture & Demo Environments
Architect distributed, scalable, and resilient data and AI platforms for presales demonstrations.
Design abstraction layers for multi-model AI orchestration , including fallback logic, dynamic model switching, and cost control.
Lead implementation of event-driven architectures using messaging frameworks (Kafka, Pulsar, SQS, etc.) and state machines.
Build reusable, industry-specific demo environments leveraging hyperscaler services and data platforms.
Observability, Security & Compliance
Define and enforce observability standards for demo and enterprise environments (logging, tracing, telemetry, real-time alerting).
Implement zero-trust security models (RBAC/ABAC, IAM, OAuth2, encryption, API gateways).
Ensure all demo and client environments meet compliance standards such as HIPAA, GDPR, SOC2 .
Cross-Functional Collaboration
Work with Product, Data Science, Engineering, and Governance teams to align demos with business/regulatory needs.
Collaborate with IMUs (verticals) to build domain-specific demo templates (e.g., Insurance claims, Healthcare payment integrity, Banking KYC/fraud, Retail personalization).
Provide hands-on support to engineering teams during delivery, troubleshooting, and performance tuning .
Innovation & Technical Leadership
Stay ahead of hyperscaler advancements, AI/ML frameworks, and orchestration patterns .
Drive technical due diligence, PoCs, and vendor/platform evaluations .
Create technical artifacts (architecture diagrams, design patterns, runbooks).
Mentor presales engineers and junior architects in solution design and client presentation skills.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Certifications preferred:
Cloud (AWS, Azure, GCP).
Kubernetes / CNCF ecosystem.
Architecture frameworks (TOGAF, SAFe).
Skills & Experience
Must-Have Skills & Experience
15+ years in software architecture, presales engineering, or enterprise data/AI platform design.
Hands-on expertise in at least two hyperscaler platforms :
Azure (Fabric, Synapse, Data Factory, Azure ML, Power BI).
AWS (Redshift, Glue, S3, SageMaker, Lake Formation).
GCP (BigQuery, Dataplex, Vertex AI, Pub/Sub).
Proven experience architecting distributed systems, microservices, and scalable AI/ML platforms .
Strong knowledge of Data Governance, Data Quality, Metadata, Lineage, and DataOps .
Expertise in event-driven systems and asynchronous workflows.
Hands-on with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK).
Advanced programming with Python (async), TypeScript/JavaScript, or Go .
Familiarity with Kubernetes, service mesh (Istio), serverless design patterns .
Experience with CI/CD automation, GitOps, Terraform, Helm .
Strong presentation, storytelling, and client engagement skills.
Preferred Skills
Experience with multi-tenant SaaS platforms and usage-based billing.
Familiarity with data mesh, knowledge graphs, and semantic interoperability .
Knowledge of frontend architecture patterns (micro-frontends, data visualizations).
Experience building presales demo or sandbox environments .
Exposure to agentic AI concepts and LLM-based orchestration .
Qualifications: Key Responsibilities:
Presales & Client Engagement
Partner with sales and industry teams to design client-ready demos, proof-of-concepts, and technical solution blueprints .
Present complex architectures in a clear, business-outcome-driven manner to both executive and technical stakeholders.
Contribute to RFP/RFI responses, solution proposals, and deal shaping .
Act as a trusted advisor in client conversations, highlighting differentiators of Data & AI Solutions.
Solution Architecture & Demo Environments
Architect distributed, scalable, and resilient data and AI platforms for presales demonstrations.
Design abstraction layers for multi-model AI orchestration , including fallback logic, dynamic model switching, and cost control.
Lead implementation of event-driven architectures using messaging frameworks (Kafka, Pulsar, SQS, etc.) and state machines.
Build reusable, industry-specific demo environments leveraging hyperscaler services and data platforms.
Observability, Security & Compliance
Define and enforce observability standards for demo and enterprise environments (logging, tracing, telemetry, real-time alerting).
Implement zero-trust security models (RBAC/ABAC, IAM, OAuth2, encryption, API gateways).
Ensure all demo and client environments meet compliance standards such as HIPAA, GDPR, SOC2 .
Cross-Functional Collaboration
Work with Product, Data Science, Engineering, and Governance teams to align demos with business/regulatory needs.
Collaborate with IMUs (verticals) to build domain-specific demo templates (e.g., Insurance claims, Healthcare payment integrity, Banking KYC/fraud, Retail personalization).
Provide hands-on support to engineering teams during delivery, troubleshooting, and performance tuning .
Innovation & Technical Leadership
Stay ahead of hyperscaler advancements, AI/ML frameworks, and orchestration patterns .
Drive technical due diligence, PoCs, and vendor/platform evaluations .
Create technical artifacts (architecture diagrams, design patterns, runbooks).
Mentor presales engineers and junior architects in solution design and client presentation skills.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Certifications preferred:
Cloud (AWS, Azure, GCP).
Kubernetes / CNCF ecosystem.
Architecture frameworks (TOGAF, SAFe).
Skills & Experience
Must-Have Skills & Experience
15+ years in software architecture, presales engineering, or enterprise data/AI platform design.
Hands-on expertise in at least two hyperscaler platforms :
Azure (Fabric, Synapse, Data Factory, Azure ML, Power BI).
AWS (Redshift, Glue, S3, SageMaker, Lake Formation).
GCP (BigQuery, Dataplex, Vertex AI, Pub/Sub).
Proven experience architecting distributed systems, microservices, and scalable AI/ML platforms .
Strong knowledge of Data Governance, Data Quality, Metadata, Lineage, and DataOps .
Expertise in event-driven systems and asynchronous workflows.
Hands-on with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK).
Advanced programming with Python (async), TypeScript/JavaScript, or Go .
Familiarity with Kubernetes, service mesh (Istio), serverless design patterns .
Experience with CI/CD automation, GitOps, Terraform, Helm .
Strong presentation, storytelling, and client engagement skills.
Preferred Skills
Experience with multi-tenant SaaS platforms and usage-based billing.
Familiarity with data mesh, knowledge graphs, and semantic interoperability .
Knowledge of frontend architecture patterns (micro-frontends, data visualizations).
Experience building presales demo or sandbox environments .
Exposure to agentic AI concepts and LLM-based orchestration .
Questions about this role
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