The Role
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.
Summary Generated by Built In
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.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 15+ years in software architecture, presales engineering, or enterprise data/AI platform design
- Hands-on expertise in at least two hyperscaler platforms (Azure, AWS, GCP) and their data/AI services
- 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 (Kafka, Pulsar, SQS, etc.)
- Hands-on experience with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK)
- Advanced programming in Python (async), TypeScript/JavaScript, or Go
- Familiarity with Kubernetes, service mesh (Istio), and serverless design patterns
- Experience with CI/CD automation, GitOps, Terraform, and Helm
- Strong presentation, storytelling, and client engagement skills
- Cloud and Kubernetes/CNCF certifications
- Architecture frameworks (TOGAF, SAFe)
- Experience with multi-tenant SaaS platforms, data mesh, knowledge graphs, frontend architecture, or presales demo environments
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The Company
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
