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. 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 . 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. 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 . Technical Expertise 6–12+ years as a Senior Data Engineer , Forward Deployment Engineer, or Platform Engineer. Strong hands-on experience with at least one hyperscaler (AWS or Azure or GCP). Deep expertise in: PySpark , SQL, Python Databricks / Snowflake (one mandatory, both preferred) Cloud data services (Kinesis, Glue, Redshift, Synapse, BigQuery, DataProc, etc.) Kubernetes, Docker, CI/CD IAM, VPC, private networking, secrets, API management Delivery & Client Facing Skills Demonstrated ability to work directly with client engineering teams . Comfortable running design discussions, debugging sessions, and deployment workshops. Strong communication skills; able to simplify technical topics for business audiences. Ability to operate independently with a consulting mindset and ownership mentality . GenAI & Multi-Agent Curiosity Exposure to LLMs, agent tooling (LangChain, LangGraph, CrewAI, etc.), or willingness to learn fast. Strong interest in how AI can automate data engineering and governance. Mindset & Attributes “Can-do” attitude; thrives in ambiguity. Fast learner; bias for action. Team player who collaborates across product, engineering, and client teams. Customer-first orientation and passion for delivering measurable outcomes.