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.