Job Opportunities

Solution Architect- Python

1. Solution Architect (1 Position)
Experience
10–15 Years
Role Summary
Lead the overall solution architecture for the PCK Platform, VA Dashboard, and Workers & Fatigue Dashboard, ensuring a scalable, cloud-native, secure, and AI-ready architecture aligned with AWS best practices. Own the end-to-end technical design, integration strategy, data architecture, and governance across all workstreams.
Key Responsibilities
1. Enterprise Solution Architecture
• Define the end-to-end architecture for all three workstreams.
• Design scalable cloud-native enterprise applications.
• Prepare High-Level Design (HLD) and review Low-Level Designs (LLD).
• Define application architecture, service decomposition, and integration patterns.
• Establish architectural standards, design principles, and development guidelines.
• Conduct architecture reviews and technical governance.

2. Application Architecture
• Design enterprise web application architecture.
• Design microservices and REST API architecture.
• Define workflow orchestration and business services.
• Design notification, scheduling, and event-driven components.
• Define authentication, authorization, and RBAC architecture.
• Ensure application scalability, availability, and maintainability.
3. Cloud & Integration Architecture
• Design AWS cloud-native architecture.
• Define integration architecture with CEreal, acCEss, CCTV systems, and enterprise services.
• Design API Gateway strategy and integration security.
• Define deployment architecture and environment strategy.
• Review cloud security, networking, monitoring, and logging architecture.
• Ensure compliance with AWS best practices.

4. Data & Analytics Architecture
• Design operational database architecture.
• Define Amazon Redshift analytics repository.
• Review metadata repository and data models.
• Define ETL integration strategy.
• Design data flows for AWS QuickSight dashboards.
• Review performance, scalability, and data governance.

5. AI & Intelligent Services Architecture
• Define the AI-ready architecture aligned with the overall solution.
• Guide the implementation of Knowledge Repository and Vector Database.
• Review RAG architecture proposed by AI Engineers.
• Define integration patterns between enterprise applications and AI services.
• Provide architectural guidance for future AI agents and conversational services.
• Ensure secure, scalable, and maintainable AI integration.

Technical Skills
Enterprise Architecture
• Enterprise Application Architecture
• Microservices Architecture
• RESTful API Design
• Event-Driven Architecture
• Domain-Driven Design (DDD)
• Integration Architecture
• Secure Application Design
Backend Technologies
• Python FastAPI
• REST APIs
• OAuth2 / JWT
• API Gateway Design
Cloud Technologies
• AWS Lambda
• Amazon API Gateway
• Amazon Cognito
• Amazon S3
• Amazon Redshift
• CloudWatch
• IAM
• VPC
• SNS / SQS
Database Technologies
• PostgreSQL
• Amazon Aurora PostgreSQL
• Amazon Redshift
• SQL Performance Optimization
• Database Design
• Data Modelling
Analytics
• AWS QuickSight
• Dashboard Architecture
• Reporting Data Models
• Data Warehousing Concepts
AI (Working Knowledge)
• Retrieval-Augmented Generation (RAG)
• Large Language Models (LLMs)
• Vector Databases (pgVector/OpenSearch)
• LangChain or equivalent AI orchestration frameworks
• Prompt Engineering concepts
• AI service integration using APIs
• AWS Bedrock or OpenAI services (preferred)

Good to Have
• Bedrock
• OpenSearch
• pgVector
• LangChain
• RAG
• GenAI Architecture
• EventBridge
• SQS
• SNS