We are looking for a highly versatile and experienced Technical Architect who can design, build, and scale end-to-end technology solutions across multiple domains including Data Platforms, Application Development, Cloud, Machine Learning, and Generative AI.
The ideal candidate is a multi-domain architect with strong fundamentals and the ability to architect across technologies, drive modernization initiatives, and guide teams in delivering scalable, secure, and high-performance systems.
Key Responsibilities
1. Enterprise Architecture & Solution Design
- Design end-to-end architectures spanning applications, data platforms, AI/ML systems, and cloud ecosystems.
- Define architecture principles, standards, and best practices.
- Create HLD/LLD design artifacts.
- Ensure solutions are scalable, resilient, secure, and cost-efficient.
2. Multi-Domain Technology Architecture
- Architect solutions across:
- Application Development (monoliths, microservices, APIs)
- Data Platforms (Data Lakes, Lakehouse, Data Warehouses)
- Cloud-native systems (AWS / Azure / GCP)
- AI/ML & Generative AI solutions
- Enable seamless integration across systems and domains.
3. Application Architecture & Development
- Design modern application architectures (microservices, event-driven, API-first).
- Define integration patterns (REST, GraphQL, messaging, streaming).
- Ensure best practices in performance, scalability, and reliability.
4. Data & Analytics Architecture
- Architect data ecosystems including ingestion, processing, storage, and consumption.
- Support batch, streaming, and real-time processing.
- Define data modeling, governance, lineage, and quality frameworks.
5. AI/ML & Generative AI Enablement
- Design and integrate ML and GenAI solutions into enterprise platforms.
- Define architectures for:
- Model lifecycle (training, deployment, monitoring)
- LLM integration and AI pipelines
- Ensure responsible, scalable AI implementations.
6. Cloud & Platform Engineering
- Architect and implement solutions on AWS / Azure / GCP.
- Leverage cloud-native services for applications, data, and AI workloads.
- Drive platform engineering, scalability, and cost optimization (FinOps).
7. Modernization & Transformation
Lead application and data modernization initiatives:
Legacy
- Cloud-native
Monolith- Microservices
Traditional DW- Modern Data Platforms
- Define and execute migration strategies (rehost, replatform, refactor, rebuild).
8. DevOps, Automation & Observability
- Implement CI/CD pipelines across application, data, and ML workflows.
- Promote Infrastructure as Code (IaC) and automation.
- Define monitoring, logging, and observability frameworks.
9. Security, Governance & Compliance
- Implement end-to-end security architecture.
- Define identity, access control, and data protection mechanisms.
- Ensure compliance with enterprise and regulatory standards.
10. Leadership & Collaboration
- Provide technical leadership and mentorship.
- Collaborate with stakeholders, product teams, and engineering teams.
- Contribute to solutioning, pre-sales, and innovation initiatives.
- Drive adoption of modern engineering and architectural best practices.
