GEN AIML Full Stack

Job Title Full Stack Engineer Offshore Contractor Empirical AIaaS Platform
 

Experience 6-12 Years


Evening Shift 3 30 PM - 12 30 PM IST

Role Summary
Full stack engineer to support O&M customer onboarding and feature development for a cloud-native, AI-driven OCR platform on Azure. Role requires working across production support and feature engineering in a containerised (AKS) environment, with exposure to AI/Agentic systems
Key Responsibilities
Own production support (incidents, RCA, monitoring, escalations) for distributed applications
Develop features using Python (backend) and Angular (preferred) / React (frontend)
Work on Azure platform (Container Apps, AKS, networking, storage, monitoring)
Implement observability (Azure Log Analytics, APM, alerts)
Contribute to AI-driven, agentic workflows and platform enhancements
Use customer insights and feedback to drive product improvements
Required Skills & Experience
Strong Python backend + Angular (preferred) / React frontend
Hands-on Azure ecosystem (Container Apps, AKS, networking, platform services, Azure Cognitive Search (Hybrid Search)
Strong knowledge of Containers & Kubernetes
Experience with MongoDB and SQL Server
Experience with monitoring/observability (Log Analytics, APM, alerts)
Strong secure coding and system design practices
Hands-on DevOps, CI/CD, and production O&M environments
Exposure to Linux / Red Hat environments
AI / Next-Gen Expectations
Experience with AI/ML systems (OCR, NLP, document processing)
Exposure to 
AIOps practices
Prompt engineering / LLM workflows
Soft Skills
Strong communication (global stakeholder interaction)
Ability to work with customers across varying technical expertise levels
Customer-first mindset focused on platform adoption and success
What We’re Looking For
Experience in both O&M and feature development
Strong hands-on Azure cloud-native exposure
Comfortable in customer-facing, production-critical environments
Applied Productivity Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows.
Continuous Learning Stay current with evolving AI capabilities and features, and apply them to improve delivery quality and velocity