Staff Technical Program Manager Visa Sponsorship Jobs in Georgia
Staff technical program manager visa sponsorship jobs in Georgia cluster around Atlanta's technology corridor, with major employers including Google, Microsoft, NCR Voyix, and Cox Enterprises actively hiring. Georgia's fintech, logistics, and cloud infrastructure sectors generate consistent demand, and international candidates with H-1B visa sponsorship history increasingly target the metro Atlanta market.
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Get Access To All JobsINTRODUCTION
Candescent is a forward-thinking technology company transforming how financial institutions deliver Intelligent Banking experiences. We unite digital banking, account opening, and branch solutions that power and connect digital banking, account opening, and branch solutions—creating seamless engagement across digital, remote, and in-person channels.
Our Experience-Led, Intelligence-Driven approach combines human-centered design with data, automation, and cloud-based innovation. Built on an API-first architecture, our extensible ecosystem enables institutions to adapt quickly, integrate easily, and unlock new opportunities for growth—turning every customer interaction into a moment of clarity, confidence, and connection.
As a Principal Technical Program Manager - AI Enablement at Candescent, you will lead the enterprise-wide evaluation, rollout, adoption, and operationalization of artificial intelligence capabilities. You will translate AI strategy into executable technical programs and serve as a primary execution bridge across engineering, platform teams, IT, security, privacy, legal, procurement, risk, and business stakeholders.
You will guide initiatives from intake and proof of concept through production readiness and scaled adoption, while ensuring that delivery plans, governance controls, vendor decisions, and measurable outcomes remain aligned with business objectives, architectural standards, and the expectations of a regulated environment.
Key Responsibilities
AI Program Leadership & Delivery
- Own the end-to-end lifecycle of complex AI enablement programs, from intake, discovery, and proof of concept through production rollout, adoption, and ongoing operationalization.
- Translate enterprise AI strategy into clear roadmaps, milestones, program plans, dependencies, success measures, and delivery commitments.
- Define program scope, goals, technical and operational readiness criteria, and measurable outcomes in collaboration with engineering and business stakeholders.
- Drive prioritization across concurrent AI initiatives based on business value, technical readiness, risk, capacity, and organizational impact.
- Develop and maintain integrated schedules, risk assessments, issue logs, decision records, and mitigation plans for high-impact programs.
Cross-Functional Technical Execution
- Serve as a primary coordination point across engineering, platform teams, IT, security, privacy, legal, procurement, risk, and business stakeholders.
- Identify cross-team dependencies, resolve blockers, clarify ownership, and drive timely decisions and delivery across multiple workstreams.
- Ensure technical implementation, platform integration, deployment strategy, and operational readiness remain aligned with business objectives.
- Communicate program status, outcomes, risks, trade-offs, and decisions clearly to executive leadership and key stakeholders.
- Provide program-level guidance on architecture, integration, release planning, deployment, and support readiness without displacing engineering ownership.
AI Governance, Risk & Compliance
- Embed responsible AI practices into AI evaluation, implementation, rollout, and day-to-day enablement activities.
- Partner with Risk, Privacy, Security, and Legal teams to align AI initiatives with internal standards and applicable regulatory expectations.
- Coordinate alignment of AI tools and operating practices with recognized frameworks such as the NIST AI Risk Management Framework and ISO/IEC 42001.
- Maintain audit-ready program documentation, control evidence, risk decisions, approvals, and traceability for AI initiatives.
- Ensure governance requirements are incorporated into delivery plans early enough to support speed, accountability, and production readiness.
Vendor, Tool & Platform Enablement
- Lead the structured evaluation, onboarding, and operationalization of third-party AI tools, platforms, and services.
- Coordinate technical, security, privacy, data-handling, procurement, licensing, access-control, and architectural-fit assessments.
- Define pilot objectives and evaluation criteria, synthesize findings, and drive recommendations for broader adoption, remediation, or exit.
- Coordinate production-readiness activities, support models, ownership transitions, and rollout dependencies for approved AI capabilities.
Operating Model, Adoption & Measurement
- Define and maintain the AI enablement operating model, including intake processes, evaluation workflows, decision gates, ownership, and escalation paths.
- Drive adoption through enablement planning, stakeholder engagement, training coordination, reusable guidance, and transparent communications.
- Establish and report KPIs that measure AI usage, adoption, value realization, delivery health, and risk posture.
- Introduce scalable program-management practices, templates, tools, and continuous-improvement mechanisms across the AI portfolio.
- Champion a culture of accountability, transparency, responsible experimentation, and measurable innovation.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- 8+ years of experience leading complex technical programs in software, cloud, data, platform, or AI-adjacent environments.
- Proven track record of managing large-scale, cross-functional programs spanning multiple teams, technologies, and stakeholder groups.
- Strong technical fluency and the ability to engage credibly with engineering, platform, architecture, security, privacy, and operations teams.
- Strong understanding of the software development lifecycle, Agile delivery, DevOps practices, production readiness, and change management.
- Experience defining roadmaps, success metrics, integrated plans, dependency models, risk controls, and executive-level program reporting.
- Demonstrated ability to operate effectively in regulated, high-risk, or control-oriented environments.
- Excellent written and verbal communication, executive presence, and stakeholder-management skills.
- Ability to adapt strategy and execution in fast-moving, ambiguous environments while maintaining clear accountability and governance.
Preferred Qualifications
- Experience leading enterprise AI enablement, generative AI, machine learning platform, data, cloud, or developer-productivity programs.
- Working knowledge of responsible AI practices and AI governance frameworks, including NIST AI RMF and ISO/IEC 42001.
- Experience evaluating and onboarding third-party technology vendors, including security, privacy, data handling, licensing, access, architecture, and operational-readiness considerations.
- Familiarity with cloud platforms such as Google Cloud, Microsoft Azure, or AWS; modern platform architectures; APIs; and enterprise integration patterns.
- Experience defining adoption strategies, enablement programs, training coordination, and outcome-based metrics for new technology capabilities.
- PMP, PgMP, Scrum, SAFe, or comparable program-management certification.
- AI governance, security, privacy, or risk certification such as AIGP, CISM, CDPSE, or an equivalent credential.
Success in This Role
- AI initiatives move from evaluation to production through a clear, repeatable, and well-governed delivery model.
- Cross-functional stakeholders have transparent ownership, timely decisions, actionable plans, and clear visibility into progress and risk.
- AI tools and platforms are evaluated consistently for business value, technical fit, security, privacy, data handling, and operational readiness.
- Responsible AI controls and governance evidence are integrated into program execution rather than treated as late-stage approvals.
- Approved AI capabilities achieve measurable adoption and value, supported by meaningful KPIs and stakeholder feedback.
- Program risks, blockers, dependencies, and trade-offs are surfaced early, resolved decisively, and communicated effectively.
- AI enablement processes become more standardized, scalable, measurable, and sustainable as Candescent expands its AI portfolio.
Statement to Third Party Agencies
To ALL recruitment agencies: Candescent only accepts resumes from agencies on the preferred supplier list. Please do not forward resumes to our applicant tracking system, Candescent employees, or any Candescent facility. Candescent is not responsible for any fees or charges associated with unsolicited resumes.
INTRODUCTION
Candescent is a forward-thinking technology company transforming how financial institutions deliver Intelligent Banking experiences. We unite digital banking, account opening, and branch solutions that power and connect digital banking, account opening, and branch solutions—creating seamless engagement across digital, remote, and in-person channels.
Our Experience-Led, Intelligence-Driven approach combines human-centered design with data, automation, and cloud-based innovation. Built on an API-first architecture, our extensible ecosystem enables institutions to adapt quickly, integrate easily, and unlock new opportunities for growth—turning every customer interaction into a moment of clarity, confidence, and connection.
As a Principal Technical Program Manager - AI Enablement at Candescent, you will lead the enterprise-wide evaluation, rollout, adoption, and operationalization of artificial intelligence capabilities. You will translate AI strategy into executable technical programs and serve as a primary execution bridge across engineering, platform teams, IT, security, privacy, legal, procurement, risk, and business stakeholders.
You will guide initiatives from intake and proof of concept through production readiness and scaled adoption, while ensuring that delivery plans, governance controls, vendor decisions, and measurable outcomes remain aligned with business objectives, architectural standards, and the expectations of a regulated environment.
Key Responsibilities
AI Program Leadership & Delivery
- Own the end-to-end lifecycle of complex AI enablement programs, from intake, discovery, and proof of concept through production rollout, adoption, and ongoing operationalization.
- Translate enterprise AI strategy into clear roadmaps, milestones, program plans, dependencies, success measures, and delivery commitments.
- Define program scope, goals, technical and operational readiness criteria, and measurable outcomes in collaboration with engineering and business stakeholders.
- Drive prioritization across concurrent AI initiatives based on business value, technical readiness, risk, capacity, and organizational impact.
- Develop and maintain integrated schedules, risk assessments, issue logs, decision records, and mitigation plans for high-impact programs.
Cross-Functional Technical Execution
- Serve as a primary coordination point across engineering, platform teams, IT, security, privacy, legal, procurement, risk, and business stakeholders.
- Identify cross-team dependencies, resolve blockers, clarify ownership, and drive timely decisions and delivery across multiple workstreams.
- Ensure technical implementation, platform integration, deployment strategy, and operational readiness remain aligned with business objectives.
- Communicate program status, outcomes, risks, trade-offs, and decisions clearly to executive leadership and key stakeholders.
- Provide program-level guidance on architecture, integration, release planning, deployment, and support readiness without displacing engineering ownership.
AI Governance, Risk & Compliance
- Embed responsible AI practices into AI evaluation, implementation, rollout, and day-to-day enablement activities.
- Partner with Risk, Privacy, Security, and Legal teams to align AI initiatives with internal standards and applicable regulatory expectations.
- Coordinate alignment of AI tools and operating practices with recognized frameworks such as the NIST AI Risk Management Framework and ISO/IEC 42001.
- Maintain audit-ready program documentation, control evidence, risk decisions, approvals, and traceability for AI initiatives.
- Ensure governance requirements are incorporated into delivery plans early enough to support speed, accountability, and production readiness.
Vendor, Tool & Platform Enablement
- Lead the structured evaluation, onboarding, and operationalization of third-party AI tools, platforms, and services.
- Coordinate technical, security, privacy, data-handling, procurement, licensing, access-control, and architectural-fit assessments.
- Define pilot objectives and evaluation criteria, synthesize findings, and drive recommendations for broader adoption, remediation, or exit.
- Coordinate production-readiness activities, support models, ownership transitions, and rollout dependencies for approved AI capabilities.
Operating Model, Adoption & Measurement
- Define and maintain the AI enablement operating model, including intake processes, evaluation workflows, decision gates, ownership, and escalation paths.
- Drive adoption through enablement planning, stakeholder engagement, training coordination, reusable guidance, and transparent communications.
- Establish and report KPIs that measure AI usage, adoption, value realization, delivery health, and risk posture.
- Introduce scalable program-management practices, templates, tools, and continuous-improvement mechanisms across the AI portfolio.
- Champion a culture of accountability, transparency, responsible experimentation, and measurable innovation.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- 8+ years of experience leading complex technical programs in software, cloud, data, platform, or AI-adjacent environments.
- Proven track record of managing large-scale, cross-functional programs spanning multiple teams, technologies, and stakeholder groups.
- Strong technical fluency and the ability to engage credibly with engineering, platform, architecture, security, privacy, and operations teams.
- Strong understanding of the software development lifecycle, Agile delivery, DevOps practices, production readiness, and change management.
- Experience defining roadmaps, success metrics, integrated plans, dependency models, risk controls, and executive-level program reporting.
- Demonstrated ability to operate effectively in regulated, high-risk, or control-oriented environments.
- Excellent written and verbal communication, executive presence, and stakeholder-management skills.
- Ability to adapt strategy and execution in fast-moving, ambiguous environments while maintaining clear accountability and governance.
Preferred Qualifications
- Experience leading enterprise AI enablement, generative AI, machine learning platform, data, cloud, or developer-productivity programs.
- Working knowledge of responsible AI practices and AI governance frameworks, including NIST AI RMF and ISO/IEC 42001.
- Experience evaluating and onboarding third-party technology vendors, including security, privacy, data handling, licensing, access, architecture, and operational-readiness considerations.
- Familiarity with cloud platforms such as Google Cloud, Microsoft Azure, or AWS; modern platform architectures; APIs; and enterprise integration patterns.
- Experience defining adoption strategies, enablement programs, training coordination, and outcome-based metrics for new technology capabilities.
- PMP, PgMP, Scrum, SAFe, or comparable program-management certification.
- AI governance, security, privacy, or risk certification such as AIGP, CISM, CDPSE, or an equivalent credential.
Success in This Role
- AI initiatives move from evaluation to production through a clear, repeatable, and well-governed delivery model.
- Cross-functional stakeholders have transparent ownership, timely decisions, actionable plans, and clear visibility into progress and risk.
- AI tools and platforms are evaluated consistently for business value, technical fit, security, privacy, data handling, and operational readiness.
- Responsible AI controls and governance evidence are integrated into program execution rather than treated as late-stage approvals.
- Approved AI capabilities achieve measurable adoption and value, supported by meaningful KPIs and stakeholder feedback.
- Program risks, blockers, dependencies, and trade-offs are surfaced early, resolved decisively, and communicated effectively.
- AI enablement processes become more standardized, scalable, measurable, and sustainable as Candescent expands its AI portfolio.
Statement to Third Party Agencies
To ALL recruitment agencies: Candescent only accepts resumes from agencies on the preferred supplier list. Please do not forward resumes to our applicant tracking system, Candescent employees, or any Candescent facility. Candescent is not responsible for any fees or charges associated with unsolicited resumes.
Staff Technical Program Manager Job Roles in Georgia
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Search Staff Technical Program Manager Jobs in GeorgiaStaff Technical Program Manager Jobs in Georgia: Frequently Asked Questions
Which companies sponsor visas for staff technical program managers in Georgia?
Atlanta-headquartered and metro-area employers with active H-1B LCA filing histories for program management roles include Google's Atlanta offices, Microsoft, NCR Voyix, Cox Enterprises, Equifax, and Global Payments. Financial technology and cloud infrastructure companies in Midtown and Buckhead frequently sponsor at the staff and principal levels, where the technical depth of the role clearly satisfies specialty occupation requirements.
Which visa types realistically apply to staff technical program manager roles in Georgia?
Staff technical program manager roles qualify as specialty occupations because they require a bachelor's degree or higher in computer science, engineering, or a related technical field. H-1B is the primary path, with initial status up to three years, extendable to six, and subject to the annual cap and selection process. H-1B1 visa applies to Chilean and Singaporean nationals, and E-3 visa applies to Australian nationals. EB-2 or EB-3 employment-based green cards are also viable for long-term sponsorship.
Which cities in Georgia have the most staff technical program manager sponsorship jobs?
Atlanta accounts for the overwhelming majority of staff technical program manager sponsorship activity in Georgia, particularly in Midtown, Buckhead, and the Technology Square corridor near Georgia Tech. Alpharetta and Roswell, both part of the northern suburbs, host significant fintech and enterprise software campuses. Smaller concentrations exist in Duluth and Peachtree City near manufacturing and logistics technology operations.
How to find staff technical program manager visa sponsorship jobs in Georgia?
Migrate Mate lists Georgia employers with verified H-1B and other LCA sponsorship history, searchable by role and city, so you can focus on companies already demonstrating a track record of sponsoring technical program managers. This is especially useful for narrowing down Atlanta's large employer pool to those with active filings at the staff level, where sponsorship decisions differ from more junior program management roles.
What state-specific factors affect staff technical program manager sponsorship in Georgia?
Georgia's concentration of fintech, supply chain technology, and media companies creates sustained demand for staff technical program managers who can bridge engineering and business functions. Georgia Tech's graduate pipeline produces strong local talent competition, which means sponsored candidates typically need demonstrated experience leading cross-functional programs at scale. Atlanta's lower cost of operations compared to Bay Area or Seattle markets can also make employers more willing to absorb sponsorship costs at senior levels.
What is the prevailing wage for sponsored staff technical program manager jobs in Georgia?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.