Member of Technical Staff, Enterprise Data Boundary

Dipp AI Technologies, Inc.

New York (NY)

Presencial

USD 120.000 - 180.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Equity (4-year vest)
Medical, dental, and vision coverage
401(k) with company contribution
Hardware budget
Learning & certification budget

Descripción de la vacante

Dipp Intelligence seeks a senior data security engineer to architect controls ensuring enterprise data never trains external models. You will implement classification, egress policies, tokenisation, redaction, and provider-eligibility checks, building private-tenant inference paths and evidence pipelines to show boundary enforcement.

You'll collaborate with security reviewers and design the Dipp Intelligence layer that preserves tenancy while enabling governed inference.

Formación

  • Experience with data governance, DLP, or privacy engineering in production systems.
  • Strong distributed-systems fundamentals and streaming/pipeline experience.
  • Knowledge of GDPR, HIPAA, or sector data-handling rules and how they translate into architecture.
  • Experience with tokenisation, encryption in use, or privacy-preserving techniques.

Responsabilidades

  • Build data classification and tagging that follows payloads through the control plane.
  • Implement egress policy, redaction, tokenisation, and provider-eligibility enforcement.
  • Design private-tenant inference paths for restricted workloads.
  • Produce customer-facing evidence of boundary enforcement, not just assurances.
  • Work with security reviewers to validate the boundary under adversarial questioning.

Conocimientos

Data governance
DLP
Privacy engineering
Distributed systems
Streaming pipelines
Tokenisation
Encryption-in-use
Security reviews

Educación

BS/MS in CS or Information Security

Descripción del empleo

Guarantee architecturally that enterprise data never trains anyone else's model.

The Data Control Gateway is where enterprise data meets model inference. Its promise is architectural, not contractual: restricted data does not leave the tenant boundary, and it is never used to train a third-party model.

You will build classification, egress control, tokenisation and redaction, and the provider-eligibility logic that enforces this before a request is made. You will also build the proof: telemetry and evidence showing a customer exactly where their data went and where it could not go.

The counterpart is Dipp Intelligence — the compounding operational value an enterprise gets from its own governed usage, kept inside its own boundary.

What you will do
  • Build data classification and tagging that follows payloads through the control plane.
  • Implement egress policy, redaction, tokenisation, and provider-eligibility enforcement.
  • Design private-tenant inference paths for restricted workloads.
  • Produce customer-facing evidence of boundary enforcement, not just assurances.
  • Work with security reviewers to validate the boundary under adversarial questioning.
  • Build the Dipp Intelligence aggregation layer without compromising tenant isolation.
What we look for
  • Experience with data governance, DLP, or privacy engineering in production systems.
  • Strong distributed-systems fundamentals and streaming or pipeline experience.
  • Knowledge of GDPR, HIPAA, or sector data-handling rules and how they translate into architecture.
  • Experience with tokenisation, encryption in use, or privacy-preserving techniques.
  • Ability to explain a boundary guarantee precisely, without overstating it.
  • Comfort in enterprise security reviews.
Experience
  • 6+ years in data platform, security, or backend engineering.
  • Has shipped a data governance or egress-control capability that passed external review.
  • Experience with multi-tenant isolation in a regulated environment is a strong plus.
Education
  • BS or MS in Computer Science, Data Engineering, Information Security, or a related field.
  • Equivalent professional experience is accepted in place of a degree.
Compensation and benefits
  • Meaningful equity with a standard four-year vest.
  • Full medical, dental, and vision coverage.
  • 401(k) with company contribution and a hardware budget.
  • Annual learning and certification budget.
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