1) Engineering Strategy, Predictability & Measurability
- Deliver the AI Factory engineering strategy so teams can build high-quality agentic solutions with predictable outcomes (capacity planning, delivery metrics, quality gates, cost-to-serve tracking, platform SLAs).
2) Technical Decisions & Architecture Across Platforms
- Make complex technical decisions spanning Azure OpenAI model choices, orchestration patterns, Copilot Studio plan, ServiceNow integration patterns, and enterprise architecture.
3) Solve Strategic/Complex Problems with Leading-edge Solutions
- Resolve complex agentic issues: prompt injection, tool misuse, grounding failures, hallucinations, latency spikes, knowledge freshness, agent memory pitfalls, and secure tool execution at scale.
4) Execute & Contribute to the Technical Roadmap
- Define and execute a roadmap for:
o Azure OpenAI capability adoption (models, embeddings, content filtering, caching)
o Copilot Studio extensibility (connectors, actions, plugins)
o ServiceNow AI experiences (Virtual Agent/Now Assist patterns, strategy triggers)
o Shared runtime components (tool registry, policy engine, evaluation services)
5) Engineering & Operational Excellence (Metrics + Improvement Loops)
- Establish excellence practices: definition-of-done for AI, release criteria, evaluation regression suites, security reviews, performance baselines, and runbooks.
6) Foster Innovation with High Reliability
- Create a culture of rapid experimentation with controls: safe sandboxes, feature flags, A/B tests, prompt/version governance, and production readiness checklists.
7) Hands-on Coding, Testing & Reviews
- Write, test, and review code across agent services, middleware, connectors, and orchestration logic; refactor prompt flows and agent policies as required.
8) Resolve Escalations (Deep Technical Troubleshooting)
- Debug and troubleshoot across:
o Agent orchestration services
o Prompt strategy + evaluation failures
o ServiceNow integrations / APIs
o Copilot Studio action chains
o Identity/access issues (Entra ID)
o Observability traces and incidents
9) Drive Technical Vision & Innovation
- Contribute to the broader technical direction: new patterns for agent planning/routing, safe tool calling, RAG design, memory strategies, and cross-platform integration.
10) Tooling & Automation for Developer Productivity
- Implement and maintain CI/CD and automation:
o Prompt + flow versioning
o Automated eval pipelines
o Quality gates (groundedness, relevance, toxicity checks)
o Automated release validation
o Developer templates and scaffolding
11) Architectures & Standards for Enterprise Scale
- Define enterprise standards for:
o Agent runtime design
o RAG architecture (indexing, retrieval, citations)
o Secure tool execution patterns
o Data access boundaries
o Tenant-level governance + audit logging
o Multi-environment promotion (dev/test/prod)
12) Build New Software + Data-driven Improvements (Reduce Tech Debt)
- Research, design, and build new components, and perform deep analysis of agent telemetry to reduce tech debt and improve reliability, performance, and developer experience.
13) Mentorship & Technical Coaching
- Mentor engineers and squads via design reviews, code reviews, pairing sessions, office hours, and playbooks.
14) Knowledge Leadership & Emerging Trends
- Continuously research and share best practices in agentic AI, LLMOps, Responsible AI, evaluation techniques, and platform feature evolution.
