Pay Pay not listed Work setting Hybrid — work setting source Employment Full-time — employment source Architect scalable data and AI platforms for presales demonstrations
Lead event-driven architecture implementations using messaging frameworks
Build reusable industry-specific demo environments on hyperscaler services
From the employer’s posting Architect distributed, scalable, and resilient data and AI platforms for presales demonstrations. 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. Core experience 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. 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. 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. Preferred experience Experience with multi-tenant SaaS platforms and usage-based billing. Experience with multi-tenant SaaS platforms and usage-based billing. Experience with multi-tenant SaaS platforms and usage-based billing. Familiarity with data mesh, knowledge graphs, and semantic interoperability. Qualification wording 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. Experience with multi-tenant SaaS platforms and usage-based billing. Familiarity with data mesh, knowledge graphs, and semantic interoperability. Education & alternatives Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- Certifications preferred: Open 3 months We first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records Live
First seen by us Aug 12, 202693 days ago
Recorded sightings 346
Last seen by us Nov 13, 2026
Employer says posted Jun 29, 2026 These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares Time since we first saw it Day 93
4 77
Up longer than most. Similar jobs usually come down between day 4 and day 77.
Well past EXL Service’s usual: its jobs come down by about day 21.
From 51 similar postings that came down, and 281 of EXL Service’s. Coming down is not always a hire.
EXL Service is hiring 211 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Has EXL Service posted this job before? Yes. We’ve followed one other Solution Architect – Data & AI Solutions job there since August 2026. It is still up.
Bengaluru Still up after 93 days, first seen Aug 12 This job Up 93 days so far, first seen Aug 12 Aug 12 Today
About EXL Service
People About 65,000 in 2025, up 9% from the year before.Annual report (SEC Form 10-K)
Company Listed as EXLS. Demand for AI Engineer roles New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65. August 17 Last week Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description View original posting ↗
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 .
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 .
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 .
AI Engineer jobs More jobs at EXL Service Source details View original posting ↗
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Location & working pattern Hyderabad, Telangana, India
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