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Added 1 min ago
Account Development Manager
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Lead regional market development efforts for small and mid-sized water utilities, focusing on strategic growth segments.
Added 3 mins ago
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8 years of experience in software development.
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· Strong understanding of the software development lifecycle, Agile delivery, DevOps practices, production readiness, and change management.
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Added 14 mins ago
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Senior Software Quality Engineer
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Staff Technical Program Manager - AI Enablement

GA, United States

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Job details

Experience: · 8+ years of experience leading complex technical programs in software, cloud, data, platform, or AI-adjacent environments.
Posting language: English
Posted: Nov 6, 2026

Original job description

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.

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