I'm a builder-CEO and principal engineer who designs and ships production systems end-to-end.
I build AI/ML SaaS platforms, FastAPI backends, RAG and agentic workflows, ML risk scoring and forecasting systems, security automations, and DevSecOps-ready infrastructure.
My current private company is a production multi-tenant AI/ML SaaS built solo across FastAPI, Flutter, Next.js, PostgreSQL, Redis, Celery, Stripe, RAG, ML detection, DevSecOps, and observability.
Through Lumen Maximus Consulting, I work with select founders, SaaS teams, agencies, and security teams that need production-grade systems they can ship, run, and maintain.
- Building and operating a private production multi-tenant AI/ML SaaS solo
- Taking 1–2 select consulting clients for production AI/ML, backend, SaaS, DevSecOps, and security-automation builds
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On-prem LangGraph agent that inspects systems, researches vendor patches through guarded network access, generates structured patch plans with rationale, and exports full decision traces through OpenTelemetry → Jaeger. Client relevance: Security automation, vulnerability workflows, patch governance, DevSecOps, analyst handoff.
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Async, SIEM-agnostic SOC triage service with concurrent enrichments, ETS forecasting, TF-IDF case retrieval, deterministic TP/FP classification, and ranked action proposals with Jinja Markdown reports. Client relevance: SOC triage, alert reduction, security operations, incident response, analyst workflow acceleration.
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Multi-agent Emergency Department triage assistant producing structured Immediate / Monitor / Escalate recommendations with rationale and follow-up checklists. Designed to augment — never replace — clinical judgment. Client relevance: Decision support, human-in-the-loop AI, safety-sensitive workflows, structured triage.
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Four-agent LangGraph company-research assistant: Clarity → Research → Validator → Synthesis. Includes confidence-gated routing, human-in-the-loop interrupts, bounded retries, multi-turn memory, and pluggable web search. Client relevance: Research automation, diligence workflows, AI analysts, agentic orchestration, validation loops.
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Public repos are sanitized POCs and reference implementations. Production company work remains private.
I design and ship production AI/ML systems, backend platforms, and security automations in Python.
My strongest work sits at the intersection of:
- AI agents and RAG
- ML risk scoring, forecasting, and classification
- FastAPI backend systems
- SOC and vulnerability automation
- DevSecOps and observability
- Multi-tenant SaaS architecture
- Flutter / React product frontends
- Stripe billing, auth, and production handoff
I have 10+ years across fintech, security, backend engineering, AI, and cloud systems. I've built agentic workflows that automate SOC triage, vulnerability patching, ServiceNow change requests, Slack incident response, and governance-ready GenAI workflows.
I'm the solo founder and principal engineer behind a private production multi-tenant AI/ML SaaS.
The system demonstrates end-to-end product engineering across:
| Layer | Scope |
|---|---|
| Backend | Async FastAPI, SQLAlchemy 2.0, PostgreSQL, Redis, Celery worker fleets, multi-tenant patterns |
| Frontend | Flutter application, OpenAPI-first client, WebSockets, passkeys, charting, typed API contracts |
| Marketing | Next.js / React front end, internationalization, conversion-oriented product flow |
| AI / ML | LLM orchestration, RAG, pgvector, classical ML, risk scoring, forecasting, NLP, image similarity |
| Security | JWT, argon2, TOTP 2FA, WebAuthn/passkeys, SAML/OIDC patterns, signed requests |
| Billing | Stripe subscriptions, package billing, top-ups, customer portal, webhooks |
| Platform | Docker, GitHub Actions, SOPS/age, gitleaks, semgrep, OpenTelemetry, Sentry, OpenSearch, Grafana |
| Process | Spec-driven development, contract testing, end-to-end journey testing, production release discipline |
Architecture case study available on request.
| Role | Scope | Highlights |
|---|---|---|
| Founder & Principal Engineer | Private Production AI/ML SaaS | Solo-built multi-tenant SaaS · FastAPI + Flutter + Next.js · Postgres/Redis/Celery · RAG/ML detection · Stripe · DevSecOps · OpenTelemetry |
| Generative AI Engineer | Fortune 50 Financial Services | Python/FastAPI GenAI on GCP · Vertex AI + Gemini + OpenAI · LangChain RAG · agentic workflows · production telemetry |
| Cybersecurity Engineer | Enterprise Banking | Vulnerability pipelines · AWS ECS Fargate · Qualys + Veracode + ServiceNow · executive reporting automation |
| Python Developer | Financial Services | Secure Python services · REST APIs · trading platform applications · governance and audit trails |
| Independent Consulting | AI & Security Automation | Agentic patch automation · LLM SOC triage · ML risk scoring · Slack IR bot · ServiceNow automation · FHIR/HL7 on GCP |
10+ years building production Python systems across fintech, security, AI, and SaaS.
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| Package | Starting | Outcome |
|---|---|---|
| 🧱 Production AI SaaS Blueprint | from $1,500 | Architecture, data model, API contract, AI/RAG/ML design, auth/billing plan, DevSecOps roadmap, and implementation quote |
| 📊 ML Risk Scoring / Forecasting API | from $3,500 | Scoring, classification, forecasting, or anomaly detection shipped as a FastAPI endpoint with evals, model card, and handoff |
| 🚀 RAG / AI Agent Pilot | from $5,000 | Production-minded LangGraph/LangChain workflow with retrieval, evals, grounded outputs, and observability |
| 🛡️ Security Automation Sprint | from $5,000 | SOC triage, vulnerability workflow, Slack IR, ServiceNow/SIEM integration, audit trails, and documentation |
| 🔧 DevSecOps / Observability Sprint | from $3,500 | CI/CD, SAST, secret scanning, OpenTelemetry/Sentry, deployment hardening, and production-readiness improvements |
| 🤝 Fractional AI/Security Engineer | $2,500–$8,000/mo | Ongoing architecture and implementation support for AI/backend/security teams |
Every engagement is scoped around clear outcomes, documentation, observability, and handoff.
I'm a strong fit for:
- Founders building AI SaaS products
- SaaS teams adding AI, ML, or automation
- Security teams automating SOC, vulnerability, or incident workflows
- Agencies needing senior technical delivery
- Operators with messy manual workflows that need reliable automation
- Teams that want production-ready systems they can run and build on
I'm not the right fit for:
- Cheap chatbot clones
- Vague app ideas with no budget
- One-off scripts with no maintenance expectations
- AI demos with no plan for data, evaluation, security, or handoff
I use AI coding tools like Claude Code and GitHub Copilot to move faster — but senior judgment still owns the architecture, safety, tests, evaluation, and production handoff.
Clients get faster iteration without sacrificing maintainability, traceability, or governance.
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Clarify the business problem, users, constraints, budget, and success criteria. |
Design the backend, AI/ML workflow, API contract, data model, security controls, and deployment path. |
Ship iteratively with demos, tests, observability, and documented decisions. |
Deliver docs, walkthroughs, deployment notes, and a next-step roadmap. |
🇺🇸 NYC · ET · Remote · Select availability
