Solution Architect ML- Lead II - ML Engineering

Role Description

Solution Architect with strong experience in enterprise delivery and architecture ownership. Works across business, application, data, and platform layers. Known for structured thinking, delivery alignment, and leadership in complex environments. Increasing focus on AI enabled architectures and platform modernization.

Core Skills

Solution Architecture

Enterprise & Platform Architecture

AIready Application Design

Cloudnative and Hybrid Systems

API and Integration Architecture

Datacentric Design

Architecture Governance

Technical Leadership

Delivery Alignment

Stakeholder Communication

Programming, Platforms & Tools

Cloud Platforms: AWS / Azure (architecture and design level)

Architecture Styles: Microservices, Event driven, Layered, Platform based

Integration: REST APIs, Messaging, Service orchestration

Data: Relational and NoSQL concepts, analytics ready data flows

AI & Modern Tech: GenAI awareness, ML ready system design, automation patterns

Dev Practices: CI/CD concepts, DevOps collaboration, environment strategy

Documentation: Architecture diagrams, decision records, solution blueprints

AI & Modern Architecture Focus

Designs systems that are AI ready, not AI bolted

Ensures clean separation of data, models, and application layers

Evaluates GenAI and automation use cases with enterprise constraints in mind

Focuses on scalability, observability, security, and cost awareness

Guides responsible and sustainable AI adoption

AI & Innovation

Handson experience using GenAI tools (ChatGPT like LLMs, Copilot style assistants) for:

Test case design

Code review assistance

Faster debugging and RCA

Participated in AI POCs / pilots focused on improving QA productivity and observability insights.

Advocated responsible AI testing practices, including output validation, data sensitivity, and reliability checks.

Skills

agentic ai,solution architecture,integration architecture,application design,