We are seeking a highly experienced Solution Architect (15+ years) to join the Data & AI Solutions Presales Technology Team. This role will bridge client-facing presales engagements with deep technical solution design, enabling our teams to deliver scalable, event-driven, AI/ML-ready platforms in live demonstration and proof-of-concept environments. The ideal candidate brings: Strong technical expertise in distributed systems, microservices, cloud-native architectures, and hyperscaler platforms (Azure, AWS, GCP – at least two required). Experience in AI/ML system integration and multi-model orchestration. The ability to engage senior stakeholders, influence technical decisions, and guide cross-functional engineering teams. This is a senior, client-facing role that shapes demo environments, presales technical narratives, and enterprise-grade platform architecture to align with business outcomes across industries such as Insurance, Healthcare, Banking, and Retail.
Key Skills for This Role
awsazurebigquerydatabricksdockerelk-stack
Full Job Posting
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.
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Mentor presales engineers and junior architects in solution design and client presentation skills.
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.
Qualifications:
Exposure to agentic AI concepts and LLM-based orchestration.
Qualifications
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.
Responsibilities
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).
About EXL
Professional Services10,001+Founded 1999
EXL is a global data and AI company that provides analytics, digital operations, and industry-specific services to enterprises in insurance, healthcare, banking, retail, media, and energy.
