Platform Engineer (Solution Architect - AI & Full Stack Platforms)

Request ID: 110730-1
Title: Platform Engineer (Solution Architect - AI & Full Stack Platforms)
Locations: - Alpharetta, GA (Need to work from office 3 Days a week and Face 2 Face Round of Interview)
Duration: 06 Months
Pay Range: $45 - $50/ Hour on W2/C2C (All inclusive)

We are seeking a highly skilled Platform Engineer (Solution Architect) with strong full-stack software engineering, platform development, cloud-native architecture, and AI engineering experience to join our Platform Engineering & Architecture team.

This role combines hands-on software development with architecture ownership. The ideal candidate will design, build, deploy, and support scalable platform solutions, developer self-service capabilities, AI-powered automation, and enterprise engineering tools that enhance application reliability, resiliency, and delivery speed.

The successful candidate will collaborate with Platform Engineering, Application Development, SRE, Infrastructure, Cybersecurity, and Operations teams to transform architectural standards into reusable engineering solutions and intelligent platform services.

Key Responsibilities

Full Stack Application & Platform Engineering

• Design, build, test, and support enterprise-grade APIs, web applications, and platform services.
• Develop scalable backend systems using Java, Python, C#/.NET, or equivalent technologies.
• Build modern front-end applications using React, Angular, TypeScript, and contemporary UI frameworks.
• Develop reusable platform components, service catalogs, developer portals, and automation frameworks.
• Integrate enterprise applications with databases, messaging systems, API gateways, and engineering platforms.
• Drive code quality through testing, code reviews, performance optimization, and secure coding practices.
• Own the complete software delivery lifecycle including development, CI/CD, deployment, monitoring, and production support.

AI Engineering & Intelligent Automation

• Design and implement AI-powered applications, agents, and engineering automation solutions.
• Build Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories.
• Develop AI-driven workflows for architecture analysis, compliance validation, remediation planning, and knowledge discovery.
• Integrate AI agents with enterprise platforms and APIs using secure interfaces and protocols.
• Implement AI governance, monitoring, evaluation frameworks, auditability, and safety controls.
• Establish guardrails for responsible AI deployment including access controls, human approvals, and fallback mechanisms.

Platform Reliability & Resilience

• Design highly available, fault-tolerant, and scalable platform architectures.
• Implement resiliency patterns including:
  • Circuit Breakers
  • Bulkheads
  • Retry Mechanisms
  • Backpressure Controls
  • Graceful Degradation
  • Failover and Disaster Recovery
• Collaborate with SRE teams on observability, monitoring, troubleshooting, and incident management.
• Conduct performance engineering, load testing, failure testing, and recovery validation.

Architecture Governance

• Translate architecture standards into reusable frameworks, templates, guardrails, and engineering accelerators.
• Develop platform governance solutions and architecture compliance automation.
• Maintain platform catalogs, technical standards, best practices, and architecture decision records.
• Promote API standardization, security-by-design, platform reuse, and operational excellence.
• Mentor engineering teams through architecture reviews and knowledge-sharing sessions.

Required Skills

Backend Technologies

• Java
• Spring Boot
• Python
• C# / .NET
• REST APIs
• Microservices
• Distributed Systems
• Event-Driven Architecture

Front-End Technologies

• ReactJS
• Angular
• TypeScript
• JavaScript
• HTML5
• CSS3

AI & Machine Learning

• Generative AI
• LLM Applications
• AI Agents
• RAG (Retrieval-Augmented Generation)
• Vector Databases
• AI Orchestration Frameworks
• Prompt Engineering
• AI Evaluation and Monitoring

Cloud & DevOps

• Kubernetes
• Docker
• CI/CD Pipelines
• Infrastructure as Code (Terraform/Ansible)
• AWS / Azure / GCP
• GitHub Actions
• Jenkins

Data Technologies

• SQL
• PostgreSQL
• Oracle
• NoSQL Databases
• Distributed Caching
• Data Integration

Security

• OAuth
• Authentication & Authorization
• Secrets Management
• Secure Coding Practices
• Identity and Access Management

Observability

• Monitoring
• Logging
• Distributed Tracing
• Alerting
• Performance Tuning

Preferred Skills

• Wealth Management Platforms
• Banking & Financial Services
• Trading Platforms
• Kafka
• IBM MQ
• Apigee
• Service Mesh Technologies
• MCP (Model Context Protocol)
• AI Agent Orchestration
• Multi-Region Architecture
• Policy as Code
• Internal Developer Platforms
• Site Reliability Engineering (SRE)

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
• 8+ years of software engineering experience.
• 3+ years of architecture, platform engineering, or cloud solution design experience.
• Proven experience developing and operating production-grade distributed applications.
• Demonstrated experience with AI-enabled applications and intelligent automation.