Lead presales solution architecture for data and AI platforms: design client demos/PoCs, architect scalable distributed and event-driven systems, enforce observability/security/compliance, collaborate cross-functionally, evaluate vendors, create technical artifacts, and mentor presales engineers.
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.
ResponsibilitiesKey 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.
QualificationsKey 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.
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