Lead Architect – Full-Stack, Cloud, Data & AI Engineering
Tasks
- Break scope into buildable increments
- Build deployment capability using IaC modules pipeline templates runbooks and environment checklists
- Define identity networking environments and non functional targets in Azure
- Design Python services front end patterns SQL and NoSQL data design and APIs
- Direct data pipeline architecture using PySpark and Databricks
- Establish engineering standards and reusable deployment assets
- Guide design work and conduct code reviews
- Implement layered data design quality controls and performance standards
- Lead CI CD and DevOps practice
- Lead design walkthroughs and enforce coding testing release documentation standards
- Mentor engineers to independently build deploy and operate client solutions
- Monitor drift and production performance for agent quality availability latency and cost
- Own agent and orchestration design evaluation harnesses guardrails human approval flows tracing and versioning
- Own architecture and security posture through client reviews
- Own target state cloud architecture and service selection
- Prototype high risk components and unblock critical path issues
- Set technical direction for enterprise agentic AI solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AI orchestration | AIOps | API Design | Agent Orchestration | Azure | Azure Architecture | CI/CD | Data Quality | Data pipeline | Databricks | DevOps | Drift monitoring | Evaluation | Guardrails | Human-in-the-loop | IaC | IaC modules | Identity | Infrastructure as Code | JavaScript | Model versioning | Networking | NoSQL | Performance Tuning | PySpark | Python | Runbooks | SQL | The Loop | Tracing | TypeScript | “as-code”
Education
N/A
Roles
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