HA

Services & Expertise

One practice. Four disciplines that hold each other up.

Most engineers pick one discipline and stay there. I've held four in production long enough to know how they meet - and where they break each other if you don't plan for it.

Pillar · 01

Full Stack Product Engineering

Ship the product. Own the system afterward.

Typed, tested, observable full-stack builds - from data model to interaction layer. Delivered against a real release cadence, not a demo timeline.

Deliverables

  • Greenfield SaaS platforms with multi-tenant architecture
  • Legacy modernization behind a stable façade
  • Internal tools that scale beyond one team's ownership
  • Design-system-driven front-ends with real accessibility

Representative stack

TypeScript · Node · Next.js · Postgres · Redis · Docker · CI/CD

Pillar · 02

Salesforce & CRM Architecture

Turn an org that grew by accident into a platform that scales on purpose.

Nine years inside enterprise Salesforce. I design orgs to survive audit, org-wide releases, and the fifth admin who will inherit them.

Deliverables

  • Apex service layer & governed trigger frameworks
  • Flow-first automation with clear domain boundaries
  • Platform Events & integration fabric across systems
  • SFDX + CI/CD, sandbox strategy, deployment discipline
  • CRM recovery: unwinding bypass triggers, legacy workflow, and one-off code

Representative stack

Apex · LWC · Flow · Platform Events · SFDX · Sales Cloud · Service Cloud · CPQ

Pillar · 03

AI Workflow Automation

AI that fits inside the business - not around it.

Governed LLM systems embedded inside real operations. RAG with citations, agentic pipelines with typed tools, and review consoles for anything high-stakes.

Deliverables

  • Retrieval-augmented assistants over internal knowledge
  • Agentic workers for intake, qualification, and follow-up
  • Human-in-the-loop consoles for confidence-scored actions
  • Cost, latency, and quality observability across every AI step

Representative stack

Python · LangGraph · OpenAI · Claude · pgvector · Postgres · Next.js

Pillar · 04

Cloud & Reliability Engineering

Boring cloud is good cloud.

AWS and Azure done with restraint: IaC, CI/CD, observability, and rollback that takes minutes. Zero-drama releases are a feature, not a stretch goal.

Deliverables

  • Serverless- or container-based service platforms
  • Infrastructure as code (Terraform / CDK)
  • Observability: structured logs, metrics, traces, SLOs
  • Incident response & runbooks a real on-call can use

Representative stack

AWS · Azure · Terraform · CDK · GitHub Actions · Datadog · Grafana

Engagement models

Three ways to work together.

Architect & deliver

Own a system end-to-end - from architecture to production hand-off. Typical duration: 3-9 months.

Senior technical partner

Embed alongside your existing team as the senior engineering voice on architecture, delivery, and hiring. Typical duration: 6-18 months.

Recovery engagement

Come in on a system that has stopped scaling - audit, stabilize, and rearchitect. Typical duration: 6-12 weeks scoping + delivery plan.

Availability

Two long-form engagements open for 2026.

Written brief preferred. First reply within one business day.

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