About

Building AI systems enterprises can trust.

I’m Joseph Bisaccia — a Lead AI Engineer working at the intersection of applied machine learning, security engineering, and technical program leadership.

I design and operate enterprise AI systems where governance, compliance, and infrastructure are first-class concerns: HIPAA-aware agentic workflows, PHI-safe RAG over sensitive corpora, and evaluation harnesses that make model behavior auditable. My focus is quiet, durable AI — the kind regulated organizations can actually put in production.

Role
Lead AI Engineer
Focus
Governance · Security · Infrastructure
Domains
Healthcare · Regulated Enterprise
Based
United States · Remote
Portrait of Joseph Bisaccia
Joseph BisacciaFounder · Intelligent Integrations

Experience

Selected roles.

  1. [00] 2025 — Present

    Lead AI Engineer

    Behavior Frontiers

    Leading enterprise AI engineering across clinical and operations teams. Architecting HIPAA-compliant agentic workflows, PHI-safe RAG systems, and audit-ready evaluation harnesses for regulated healthcare.

  2. [01] 2024 — Present

    Independent AI Engineer

    Intelligent Integrations · Handshake AI · Outlier AI · Mercor

    Production LLM systems for enterprise clients and contract model-training work for frontier AI labs. Agentic workflows, RAG platforms, and evaluation infrastructure.

  3. [02] 2022 — 2024

    AI Implementation Lead

    Capital Energy

    Led enterprise AI adoption across sales and operations — production deployments of custom assistants, automations, and data pipelines with measurable operational impact.

Capabilities

What I bring to engagements.

  • [00]Production AI systems from architecture through operations
  • [01]Enterprise AI governance, policy, and compliance frameworks
  • [02]Security-first design for LLM applications and agentic systems
  • [03]RAG and retrieval infrastructure over sensitive corpora
  • [04]Agentic workflow development with structured evaluation
  • [05]Technical program leadership across engineering and business teams
  • [06]Change management and cross-functional AI adoption
  • [07]LLM evaluation, benchmarking, and continuous quality monitoring