Source description
About the role
You will play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.
- Build & Ship AI Applications (Primary Focus)
Design, develop, and deploy AI-powered applications and workflows
Write production-quality code across:
Backend services and APIs
AI orchestration layers and agents
Enterprise integrations
Rapidly prototype solutions and iterate them into scalable production systems
Own delivery end-to-end: build, test, deploy, monitor, and improve
- Design Practical, Scalable AI Systems
Translate use cases into clear, implementable system designs
Make architecture decisions that balance:
Speed of delivery
Scalability and reliability
Cost and operational efficiency
Define patterns for:
API-first integrations
AI orchestration and workflows
Reusable services and components
Ensure systems are simple enough to build quickly , but structured enough to scale
- Integrate AI into Real Enterprise Workflows
Embed LLM capabilities into products, internal tools, and business processes
Build and maintain APIs and system integrations
Implement agent workflows and orchestration logic that solve real operational problems
Optimize systems for performance, resilience, and cost efficiency
- Partner with Business & Deliver Outcomes
Work directly with stakeholders to understand problems and validate solutions
Translate requirements into working software quickly (days/weeks, not months)
Iterate based on feedback and usage to drive measurable impact
- Contribute to Engineering Standards & Reuse
Build and contribute to shared libraries, templates, and services
Establish practical patterns based on real implementations
Help evolve internal platforms through code and working solutions , not just design artifacts
- Build Within a Governed AI Environment
Implement secure and reliable AI solutions in practice , including:
Prompt safety and validation
Injection/misuse prevention
Observability and traceability
Align implementations with enterprise security, privacy, and compliance requirements
Technology Environment
Cloud & Platform: Microsoft ecosystem (Azure)
AI Models: Claude and other enterprise-approved LLMs
Architecture Style: API-first, event-driven, and modular services
Core Focus:
AI application engineering
Orchestration and agent workflows
Enterprise integrations
More at EQ Bank