Adoption and enablement
Recognized as an AI Champion across EPAM and Edward Jones, advising teams on prompt engineering, agent skills, GitHub Copilot, repository instructions, and secure AI adoption.
AI Success Engineer Candidate
Enterprise AI adoption, from first workflow to scaled deployment.
Customer-facing applied AI and automation engineer with 8+ years across technical delivery, quality engineering, agents, RAG, Codex, OpenAI APIs, MCP servers, connectors, and secure enterprise workflow enablement.
Personal portfolio: sami-openai-ai-success-engineer.pages.dev
- 500
- agent-skills training participants
- 100+
- repos influenced with Copilot standards
- 10+
- teams coordinated for major release testing
Role Fit
Why this maps to OpenAI AI Success Engineering
Workflow transformation
Rebuilt a failing 2,000+ line prompt process into a structured agent-and-skill workflow for enterprise dependency mapping across hundreds of applications.
Technical deployment depth
Built with OpenAI Agents SDK, Apps SDK, embeddings, RAG systems, Realtime API tests, custom GPTs, connectors, plugins, MCP servers, and Codex.
Customer trust
Led cross-team release readiness, UAT/pre-prod validation, Jira/Kanban blocker flow, performance/SRE coordination, and mission-critical quality practices.
Motivation
Why OpenAI and why AI Success Engineering
I want to work at the edge of AI technology while helping customers turn powerful models, agents, and product capabilities into real outcomes. I enjoy presenting, demonstrating, mentoring, and making complex AI concepts practical for technical and business teams.
My background in financial services shaped a strong quality and delivery mindset. I have worked on high-stakes systems supporting a firm with approximately $2T in assets, where reliability, security, requirements clarity, testing discipline, and on-time delivery matter.
OpenAI is the right next step because the role combines what I do best: hands-on AI implementation, customer-facing communication, high-pressure execution, and helping teams adopt new technology responsibly.
Evidence
Recognition-backed accomplishments
AI Champion and scaled enablement
Part of EPAM's internal AI Champions group and the Edward Jones AI Champions group. Delivered firm-wide agent-skills training to approximately 500 people and helped teams establish AI workflows across 100+ repositories.
AI-assisted migration planning
Pulled into an urgent effort as an AI Champion to map application dependencies for a major enterprise framework migration. Earned EPAM Vice President-level recognition for helping untangle dependencies that had blocked progress for 2.5 years.
Enterprise release coordination
Coordinated testing for a major Edward Jones release across 10+ teams and multiple dependent applications, owning blocker management, defect triage, dependency sequencing, test data, UAT/pre-prod validation, and performance/SRE readiness.
Mission-critical reliability
Helped sustain a near-zero production-defect record for mission-critical Edward Jones portfolio diagnostic and guideline-processing applications over approximately four years.
Selected Work
Hands-on AI systems and integrations
OS HQ AgentOS
AG-UI based AI coach runtime with tenant-scoped memory, Supabase/Postgres persistence, Cloud Run deployment boundaries, and customer-safety guardrails.
OS-AI RAG
Document ingestion, embeddings, pgvector/Postgres storage, Cloud Functions, Cloud Tasks, Cloud Run jobs, semantic retrieval, and deployment runbooks.
Codex, MCP, and OpenAI Apps
Codex workflow scaffolding, reusable skills, specialized subagents, MCP servers, Slack agent interfaces, custom Slack APIs, and an OpenAI Chat SDK app.