Design and present scalable, resilient data and AI platform architectures and presales demo environments. Lead multi-model AI orchestration, event-driven systems, observability, security/compliance, and collaborate cross-functionally to build industry-specific demos 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.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.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.
QualificationsTechnical 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.
EXL Pune, Mahārāshtra, IND Office
Pune, India
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What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
