Solution Architect Data & AI Solutions

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. 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.
  
  

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.