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 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.

• 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).
• 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, Verte
• 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.
• 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.
• 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).
• 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, Verte
• 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.