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Privacy Engineer Jobs in Virginia (NOW HIRING)

Pncpl Software Engineer

Herndon, VA · Remote

$91K - $160.75K/yr

11-May-2026 Principal Software Developer US (Remote) 10965BR Company Summary As the recognized ... Applicant Privacy Notice Deltek is committed to the protection and promotion of your privacy. In ...

As a Senor Test Engineer with AMERICAN SYSTEMS, you will: * Serve as the Test Manager for a ... Ensure testing activities address applicable compliance requirements, including security, privacy ...

New

AI/ML ENGINEER Location: Reston,VA Duration: 12+ Months Visa: USC, GC, H1B and EAD Contract Type ... Knowledge of data privacy and security best practices in cloud environments. * Familiarity with ...

Applicant Privacy Notice Deltek is committed to the protection and promotion of your privacy. In ... Business Summary The Deltek Engineering and Technology team builds best-in-class solutions to ...

AI Data Engineer - Senior Consultant

Richmond, VA · On-site

$103.80K - $141K/yr

Deloitte's Human Capital team is seeking an AI Engineer Senior Consultant to build and operate the ... privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy ...

AI Data Engineer - Senior Consultant

Mclean, VA · On-site

$107.40K - $145.90K/yr

Deloitte's Human Capital team is seeking an AI Engineer Senior Consultant to build and operate the ... privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy ...

AI/ML Engineer

Reston, VA

$123.56K - $167.17K/hr

... Engineer who loves wrestling with large language models (LLMs) and building useful products. You ... Ensure privacy and compliance with HIPAA, including encryption, PHI protection, and vendor due ...

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Showing results 1-20

Privacy Engineer information

See Virginia salary details

$18

$66

$119

How much do privacy engineer jobs pay per hour?

As of May 29, 2026, the average hourly pay for privacy engineer in Virginia is $66.35, according to ZipRecruiter salary data. Most workers in this role earn between $46.76 and $77.15 per hour, depending on experience, location, and employer.

What does a Privacy Engineer do?

A Privacy Engineer designs, implements, and maintains systems that protect user data and ensure compliance with privacy regulations. They work closely with legal, security, and engineering teams to embed privacy controls into products and services. Their responsibilities include data protection assessments, privacy-preserving technologies, and automating compliance processes.

What are the key skills and qualifications needed to thrive in the Privacy Engineer position, and why are they important?

A Privacy Engineer typically needs a solid foundation in computer science, data security principles, and privacy regulations such as GDPR and CCPA, often supported by a relevant degree or certification. Familiarity with tools such as data loss prevention (DLP) systems, encryption protocols, and privacy impact assessment (PIA) frameworks is highly valued, as well as certifications like CIPP or CIPT. Strong communication, analytical thinking, and cross-functional collaboration are essential soft skills that help Privacy Engineers navigate complex requirements and work effectively with legal, IT, and product teams. These competencies are crucial for ensuring that privacy is embedded into systems and processes, mitigating risks, and maintaining compliance in a rapidly evolving digital landscape.

What are the typical day-to-day responsibilities of a Privacy Engineer?

Privacy Engineers regularly assess and implement technical solutions to protect sensitive data, such as designing privacy-preserving architectures and conducting risk assessments. They often work cross-functionally, collaborating with product, legal, and IT teams to integrate privacy by design principles into new features or systems. Additional daily tasks may include responding to privacy incidents, automating privacy workflows, and keeping up-to-date with regulatory changes to ensure ongoing compliance. This role is both proactive and dynamic, focused on safeguarding user data while enabling business objectives.
What are the most commonly searched types of Privacy Engineer jobs in Virginia? The most popular types of Privacy Engineer jobs in Virginia are:
What job categories do people searching Privacy Engineer jobs in Virginia look for? The top searched job categories for Privacy Engineer jobs in Virginia are:
What cities in Virginia are hiring for Privacy Engineer jobs? Cities in Virginia with the most Privacy Engineer job openings:
Infographic showing various Privacy Engineer job openings in Virginia as of May 2026, with employment types broken down into 80% Full Time, 16% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $138,018 per year, or $66.4 per hour.
Forward Deployed Engineer (AI/Agentic Engineer)

Forward Deployed Engineer (AI/Agentic Engineer)

Deloitte

Richmond, VA • On-site

Other

Posted 27 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

Role summary

Zora AI is Deloitte's AI agent platform delivering role-/function-specific agents that integrate with enterprise systems and workflows. As the Lead, Forward Deployed Engineering (FDE), you will define and run the global FDE organization-setting the charter, operating model, standards, and capacity needed to deliver successful deployments at scale. You will lead multiple FDE teams across US, EMEA, and APAC, oversee critical client engagements, and partner with Product, Engineering, Cyber, and Risk to turn field learnings into repeatable delivery patterns and durable platform improvements.

Recruiting for this role ends on May 31, 2026.

What you'll do (responsibilities)

  • Define the FDE charter and operating model: Establish mission, engagement model, intake/prioritization, team structure, and ways of working across regions and time zones.
  • Lead multiple FDE teams globally: Recruit, coach, and performance-manage FDE managers/leads and individual contributors across US, EMEA, and APAC; build coverage models and on-call/escalation paths.
  • Own delivery excellence and repeatability: Create standardized implementation playbooks, reference architectures, quality gates, and reusable assets to reduce bespoke work and improve time-to-value.
  • Be accountable for successful deployments: Oversee multiple concurrent client implementations, ensuring scope clarity, environment readiness, risk controls, and predictable outcomes.
  • Participate in key client engagements: Serve as executive technical lead on priority accounts-leading workshops, shaping solution approach, handling escalations, and building trusted client relationships.
  • Translate field signals into product improvement: Create closed-loop mechanisms to convert recurring deployment friction into structured requirements; influence roadmap, connector strategy, observability, and governance features.
  • Establish best practices for agent deployments: Standardize patterns for human-in-the-loop approvals, exception handling, evaluation/monitoring, security/privacy, and auditability in enterprise contexts.
  • Partner across Deloitte and alliances: Coordinate with Sales, Delivery, Alliances, and Global teams to support pursuits, packaging, and scalable rollout across industries and geographies.
  • Run governance and metrics: Track delivery KPIs (time-to-value, success rates, incident trends), manage capacity planning, and drive continuous improvement via retrospectives and post-implementation reviews.
  • Risk, security, and compliance leadership: Ensure implementations align to Deloitte/client security requirements, data handling standards, and AI governance expectations; lead resolution of high-severity risks.

What you'll need (required qualifications)

  • 10-15+ years in software engineering, solutions/forward deployed engineering, platform delivery, or technical program leadership in enterprise environments; including leadership of multi-team organizations.
  • Demonstrated experience leading complex customer deployments involving cloud infrastructure, identity/SSO, data access, and integration with enterprise systems.
  • Strong understanding of GenAI/LLM application delivery (agent workflows, tool orchestration, retrieval-augmented generation), including operational risks and controls.
  • Proven ability to establish standards and operating rhythm (playbooks, quality gates, escalation models, delivery KPIs) across distributed teams.
  • Executive-level stakeholder management: able to communicate with client IT/security leaders and business owners; adept at navigating ambiguity and driving decisions.
  • Experience working across US and global clients, including delivery coordination across time zones and regional constraints (data residency, security, procurement).
  • Limited immigration sponsorship may be available.
  • Ability to travel 0-10%, on average, based on the work you do.

Nice to have

  • Experience building or scaling an FDE/solutions engineering organization globally.
  • Familiarity with enterprise ecosystems such as SAP, Oracle, ServiceNow, Salesforce, and common integration approaches.
  • Background in regulated industries and governance-heavy environments (auditability, privacy, retention, model risk).
  • Experience partnering with product teams on platformization (turning bespoke work into reusable product capabilities).
  • Prior enterprise delivery leadership experience driving multi-workstream execution, program governance, and executive steering across complex stakeholder environments.

Key deliverables

  • FDE organization charter: mission, engagement model, service catalog, RACI (Responsible/Accountable/Consulted/Informed), regional coverage, escalation and support model.
  • Global delivery playbook: reference architectures, environment readiness checklist, security/privacy patterns, evaluation/monitoring standards, and go-live criteria.
  • Reusable implementation assets: deployment templates, connector/config patterns, runbooks, observability dashboards, and troubleshooting guides.
  • Operating cadence: intake triage, delivery governance, performance reporting, post-mortems, and continuous improvement loop.
  • Client engagement outcomes: successful pilots scaled to production; documented value realization and adoption plan.
  • Product feedback pipeline: prioritized backlog of field-driven platform gaps with business case and impact metrics.

How success will be measured (example outcomes)

  • Time-to-value at scale: consistent reduction in time from kickoff to first successful end-to-end workflow; faster pilot-to-production conversion.
  • Deployment reliability and quality: higher workflow success rates, lower incident volume, faster MTTR (mean time to resolution), fewer repeat defects across clients.
  • Repeatability and efficiency: decreasing custom engineering per deployment; increased reuse of standard assets; improved throughput per FDE team.
  • Client outcomes and satisfaction: improved client CSAT/NPS-style feedback, referenceable successes, fewer escalations, stronger renewal/expansion pull-through (where applicable).
  • Operational maturity: clear governance, predictable capacity planning, strong cross-geo collaboration, and consistent adherence to security/privacy and AI governance controls.
  • Team health and retention: strong hiring, onboarding, development, and retention of high-performing FDE talent across regions.

Working model & stakeholders (edit as needed)

  • Working model: Hybrid with travel for priority client workshops, escalations, and go-lives; leads a distributed team across US, EMEA, APAC with follow-the-sun collaboration.
  • Core stakeholders:
    • Product Management (roadmap, requirements, prioritization)
    • Platform & Application Engineering (core capabilities, connectors, releases)
    • Applied AI / Data Science (agent behavior, evaluation, tuning)
    • Cybersecurity & Privacy (security controls, reviews, data protection)
    • Risk / Legal / Compliance (AI governance, auditability)
    • Sales, Alliances, and Delivery leaders (pursuits, packaging, rollout)
    • Client IT, Security, and Process Owners (environments, access, adoption)
    • Global stakeholders (regional delivery leaders, COEs, enablement)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $137,000 to $282,000.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

EA_ExpHire

#LH-1

Qualifications:

Role summary

Zora AI is Deloitte's AI agent platform delivering role-/function-specific agents that integrate with enterprise systems and workflows. As the Lead, Forward Deployed Engineering (FDE), you will define and run the global FDE organization-setting the charter, operating model, standards, and capacity needed to deliver successful deployments at scale. You will lead multiple FDE teams across US, EMEA, and APAC, oversee critical client engagements, and partner with Product, Engineering, Cyber, and Risk to turn field learnings into repeatable delivery patterns and durable platform improvements.

Recruiting for this role ends on May 31, 2026.

What you'll do (responsibilities)

  • Define the FDE charter and operating model: Establish mission, engagement model, intake/prioritization, team structure, and ways of working across regions and time zones.
  • Lead multiple FDE teams globally: Recruit, coach, and performance-manage FDE managers/leads and individual contributors across US, EMEA, and APAC; build coverage models and on-call/escalation paths.
  • Own delivery excellence and repeatability: Create standardized implementation playbooks, reference architectures, quality gates, and reusable assets to reduce bespoke work and improve time-to-value.
  • Be accountable for successful deployments: Oversee multiple concurrent client implementations, ensuring scope clarity, environment readiness, risk controls, and predictable outcomes.
  • Participate in key client engagements: Serve as executive technical lead on priority accounts-leading workshops, shaping solution approach, handling escalations, and building trusted client relationships.
  • Translate field signals into product improvement: Create closed-loop mechanisms to convert recurring deployment friction into structured requirements; influence roadmap, connector strategy, observability, and governance features.
  • Establish best practices for agent deployments: Standardize patterns for human-in-the-loop approvals, exception handling, evaluation/monitoring, security/privacy, and auditability in enterprise contexts.
  • Partner across Deloitte and alliances: Coordinate with Sales, Delivery, Alliances, and Global teams to support pursuits, packaging, and scalable rollout across industries and geographies.
  • Run governance and metrics: Track delivery KPIs (time-to-value, success rates, incident trends), manage capacity planning, and drive continuous improvement via retrospectives and post-implementation reviews.
  • Risk, security, and compliance leadership: Ensure implementations align to Deloitte/client security requirements, data handling standards, and AI governance expectations; lead resolution of high-severity risks.

What you'll need (required qualifications)

  • 10-15+ years in software engineering, solutions/forward deployed engineering, platform delivery, or technical program leadership in enterprise environments; including leadership of multi-team organizations.
  • Demonstrated experience leading complex customer deployments involving cloud infrastructure, identity/SSO, data access, and integration with enterprise systems.
  • Strong understanding of GenAI/LLM application delivery (agent workflows, tool orchestration, retrieval-augmented generation), including operational risks and controls.
  • Proven ability to establish standards and operating rhythm (playbooks, quality gates, escalation models, delivery KPIs) across distributed teams.
  • Executive-level stakeholder management: able to communicate with client IT/security leaders and business owners; adept at navigating ambiguity and driving decisions.
  • Experience working across US and global clients, including delivery coordination across time zones and regional constraints (data residency, security, procurement).
  • Limited immigration sponsorship may be available.
  • Ability to travel 0-10%, on average, based on the work you do.

Nice to have

  • Experience building or scaling an FDE/solutions engineering organization globally.
  • Familiarity with enterprise ecosystems such as SAP, Oracle, ServiceNow, Salesforce, and common integration approaches.
  • Background in regulated industries and governance-heavy environments (auditability, privacy, retention, model risk).
  • Experience partnering with product teams on platformization (turning bespoke work into reusable product capabilities).
  • Prior enterprise delivery leadership experience driving multi-workstream execution, program governance, and executive steering across compl...

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