AI Engineering Services

I help teams design and deliver production-grade AI systems—secure, measurable, and maintainable. Below are common engagement patterns.

1) AI Platform Architecture (Foundations)

• Architecture & roadmap: target state, phased plan, build vs buy, risk register
• RAG design: chunking, embeddings, retrieval strategy, citations, evaluation harness
• Model strategy: multi-model routing (quality vs cost), caching, prompt contracts
• Governance: RBAC, environment separation, logging, auditability

2) Agentic Workflow Automation (Outcomes)

• “Do the task” agents: take a Jira/ServiceNow request and produce a completed artifact (FAQ, SOP, report, checklist, etc.)
• Tool layer / MCP: connectors to enterprise systems with scoped permissions
• Report automation: templates, chart rendering, PDF export, approval flow

3) Engineering Delivery (Build & Ship)

• CI/CD, QA contracts, regression tests, prompt/version control
• Observability (latency, failures, quality, cost), SLOs, runbooks
• Documentation, training, and handoff

Engagement options

• 2-week sprint: prototype + architecture plan + next sprint backlog
• 6–10 week build: MVP to production-ready pilot
• Advisory: weekly architecture + cost/governance reviews

Contact me to discuss goals, constraints, and a practical first sprint.