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Ai Program Manager Jobs in Pennsylvania (NOW HIRING)

ARMADA

AI Solutions Leader

Wexford, PA · On-site

This role serves as the lead for Armada's AI program, ensuring AI initiatives are intentionally ... This is a leadership role that blends technical understanding, stakeholder management, and delivery ...

ARMADA

AI Solutions Leader

Wexford, PA · Hybrid

This role serves as the lead for Armada's AI program, ensuring AI initiatives are intentionally ... This is a leadership role that blends technical understanding, stakeholder management, and delivery ...

Armada-

AI Solutions Leader

Wexford, PA · On-site

$180 - $250/hr

This role serves as the lead for Armada's AI program, ensuring AI initiatives are intentionally ... This is a leadership role that blends technical understanding, stakeholder management, and delivery ...

Stack AV

Staff Technical Program Manager

Pittsburgh, PA · On-site +1

$125K - $162K/yr

Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety ... The Technical Program Management (TPM) team at Stack is a high-caliber, close-knit group of ...

Motional

Staff Technical Program Manager

Pittsburgh, PA · On-site +1

$144K - $191K/yr

Experience & Domain Knowledge: 7+ years of experience in technical program management or a similar role, leading complex, safety-critical AI software, robotics, or systems programs. Experience ...

T&M Associates

GIS Program Manager

Philadelphia, PA · On-site

$130K - $165K/yr

Working knowledge of cloud platforms (AWS, Azure), emerging tech (AI/ML, IoT), and enterprise IT ... programs, and professional development opportunities -- all within a people-first, award-winning ...

ARMADA

AI Solutions Leader

Wexford, PA · On-site

$180 - $260/hr

This role serves as the lead for Armada's AI program, ensuring AI initiatives are intentionally ... This is a leadership role that blends technical understanding, stakeholder management, and delivery ...

Duolingo

Senior Localization Program Manager

Pittsburgh, PA · On-site

$142K - $193K/yr

You'll own the end-to-end programs that bring promising product ideas into long-term, scalable ... You are proficient in managing and scaling workloads using technology, including AI, CMSs, and CAT ...

Lincoln Financial

VP, IT AI Strategy & Programs

Radnor, PA · Hybrid

$141K - $177K/yr

... Management Committee (SMC), Board of Directors materials related to IT's AI strategy, program progress, and value realization. * Monitors regulatory, industry, and market developments impacting AI ...

Lincoln Financial

VP, IT AI Strategy & Programs

Radnor, PA · On-site

$141K - $177K/yr

... Management Committee (SMC), Board of Directors materials related to IT's AI strategy, program progress, and value realization. * Monitors regulatory, industry, and market developments impacting AI ...

Lincoln Financial

VP, IT AI Strategy & Programs

Radnor, PA · Hybrid

$141K - $177K/yr

... Management Committee (SMC), Board of Directors materials related to IT's AI strategy, program progress, and value realization. * Monitors regulatory, industry, and market developments impacting AI ...

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All JobsAi Program JobsAi Program Manager JobsAi Program Manager Jobs in Pennsylvania

Ai Program Manager information

See Pennsylvania salary details

$38.6K

$107.7K

$157.4K

How much do ai program manager jobs pay per year?

As of Sep 5, 2026, the average yearly pay for ai program manager in Pennsylvania is $107,718.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,700.00 and $132,800.00 per year, depending on experience, location, and employer.

What is an AI program manager?

An AI Program Manager is a professional responsible for overseeing and coordinating the planning, execution, and delivery of artificial intelligence projects within an organization. They work closely with data scientists, engineers, stakeholders, and business leaders to ensure AI initiatives align with business goals and are delivered on time and within budget. Their role often includes managing project timelines, resources, communication, and risk, while also keeping up with industry advancements and ensuring ethical AI practices. AI Program Managers bridge the gap between technical teams and business objectives, ensuring successful implementation of AI solutions.

What are some common challenges faced by AI program managers when coordinating cross-functional teams?

AI Program Managers often encounter challenges in aligning diverse teams—such as data scientists, engineers, product managers, and business stakeholders—toward shared project goals. Differences in technical backgrounds, communication styles, and priorities can lead to misunderstandings or delays. Successful AI Program Managers proactively facilitate clear communication, set well-defined milestones, and ensure that all team members understand the project's objectives and constraints. Building strong relationships across departments and maintaining adaptability are key strategies for overcoming these challenges.

What are the key skills and qualifications needed to thrive as an AI program manager, and why are they important?

To thrive as an AI Program Manager, you need expertise in project management, a strong understanding of AI concepts, and experience leading cross-functional teams, often supported by a degree in computer science or a related field. Familiarity with machine learning frameworks, cloud platforms, agile methodologies, and certifications such as PMP or Scrum Master are highly valuable. Excellent communication, problem-solving, and stakeholder management skills set standout professionals apart in this role. These abilities ensure projects are delivered on time, align with business goals, and effectively bridge the gap between technical and non-technical teams.

What is the difference between Ai Program Manager vs Data Scientist?

AspectAi Program ManagerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience in AI projectsBachelor's/Master's/PhD in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentOversees AI projects, collaborates with cross-functional teams, manages timelinesAnalyzes data, develops models, interprets complex datasets
Employer & Industry UsageTech companies, AI startups, R&D departmentsTech firms, finance, healthcare, research institutions

While both roles require technical expertise, the Ai Program Manager focuses on overseeing AI initiatives and project management, whereas the Data Scientist concentrates on data analysis and model development. The roles often collaborate but serve different functions within AI projects.

How much does an AI program manager make?

An AI program manager's salary typically ranges from $100,000 to $160,000 annually, depending on experience, location, and industry. Senior roles or those in high-demand areas can earn higher compensation, often including bonuses and stock options. Strong project management skills and knowledge of AI tools are important for this role.

What are popular job titles related to Ai Program Manager jobs in Pennsylvania?

For Ai Program Manager jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Ai Program Manager jobs in Pennsylvania look for?

The top searched job categories for Ai Program Manager jobs in Pennsylvania are:

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Ai Program Manager jobs near you
Infographic showing various Ai Program Manager job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $107,718 per year, or $51.8 per hour.

Tech Lead Data Scientist, AI Evaluation & Monitoring

Geisinger Health

Danville, PA • On-site, Remote

Full-time

Medical, Dental, Vision

Re-posted 9 days ago

Key responsibilities

  • Provide technical guidance to program teams on designing validation studies, monitoring plans, and evaluation methods for AI systems.

  • Design, operate, and improve evaluation tools and reusable assets such as LLM-as-Judge frameworks, golden sets, simulation harnesses, and drift detection methods.

  • Set the technical direction, review analysis work, and mentor data analysts to support AI evaluation and monitoring activities.

Geisinger Health rating

6.9

Company rating: 6.9 out of 10

Based on 450 frontline employees who took The Breakroom Quiz

453rd of 898 rated healthcare providers

Job description

Location:
Work from home (Pennsylvania)
Shift:
Days (United States of America)
Scheduled Weekly Hours:
40
Worker Type:
Regular
Exemption Status:
Yes
Job Summary:
The Tech Lead Data Scientist, AI Evaluation & Monitoring is the principal technical expert for how Geisinger evaluates, monitors, and optimizes AI systems in production. This is a hands-on technical leadership role. The Tech Lead sets the technical direction for AI evaluation across a large and growing portfolio, provides technical leadership to a team of data analysts who execute evaluation work, and partners directly with AI program teams to raise the quality of how AI is validated, monitored, and improved over time.
The role exists because AI at Geisinger has scaled past the point where oversight can be a document-review exercise. We need a technical leader who can guide program teams toward better-designed evaluations up front, instrument meaningful production monitoring, and continually advance the methods we use, from LLM-as-Judge frameworks to simulation-based testing to pragmatic experiment design that actually scales in healthcare.
Job Duties:
What You Will Own:
  • The technical evaluation methodology applied to AI programs across the enterprise, pre-production validation, production monitoring, and ongoing optimization
  • Hands-on guidance to program teams as they design validation studies, equity audits, monitoring plans, and escalation playbooks for their AI systems
  • Instrumentation of production monitoring: translating program-specific failure modes into concrete, measurable metrics
  • The evaluation toolkit: LLM-as-Judge frameworks, golden sets, simulation harnesses, experimental study designs, drift detection, subgroup fairness analysis
  • Reusable evaluation playbooks and templates that let each new program move faster than the last
  • Technical direction, design review, and mentorship for a team of data analysts supporting the evaluation function

What You Will Not Own:
  • People management, HR administration, or formal performance evaluations for the analyst team (those sit with the analysts' line manager; the Tech Lead provides technical input)
  • Program-level product strategy or go/no-go decisions
  • Final clinical validation judgment on whether a given AI is safe for a given clinical use
  • The software infrastructure behind the evaluation and monitoring tooling (built by the AI Platform team - the Tech Lead defines what's measured and how; Platform builds the backend)

Shape of the Work:
This is a role that lives at three altitudes at once:
With program teams (hands-on advisory). Partner with program owners early, before evaluations are designed, to shape study approach, sample size, stratification, gold-standard definition, and decision thresholds. Translate ambiguous failure modes into concrete, defensible evaluation designs. Coach teams through the technical work so that what arrives at governance review is rigorous, not performative.
With the evaluation toolkit (hands-on build). Design and operate the reusable assets that let evaluation scale: LLM-as-Judge rubrics and calibration methods, golden sets, simulation harnesses, A/B and shadow-mode study templates, subgroup fairness analyses, and drift monitors. Keep a pragmatic eye on what actually works in a clinical environment versus what works in a paper.
With the analyst team (technical leadership). Set technical direction, assign work across active evaluations, review analysis code and study designs, and raise the technical bar. Mentor analysts on methodology, statistical rigor, and the domain knowledge that makes evaluation credible. Grow them from execution into independent evaluation design.
Methods You'll Use:
  • Experimental and quasi-experimental design for production AI systems
  • LLM and generative AI evaluation: golden sets, judge-based evaluation, hallucination and grounding checks
  • Fairness and equity evaluation across patient and stakeholder subgroups
  • Production monitoring design: drift detection, performance decay, adoption, and outcome metrics
  • Causal inference methods appropriate to healthcare settings where full RCTs are often impractical
  • Simulation and adversarial testing for pre-production stress testing
  • Python, SQL, modern ML and evaluation tooling, cloud-native data platforms

Work is typically performed in an office or remote environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job.
*Relevant experience may be a combination of related work experience and degree obtained (Master's Degree = 2 years; PHD = 4 years ).
Position Details:
Required Skills & Qualifications:
  • 6+ years in data science, statistics, ML engineering, or applied quantitative research, with demonstrated experience as the senior technical voice on cross-functional projects

  • Strong foundation in experimental design and causal inference - and judgment about which method fits which situation

  • Hands-on experience designing and running model evaluation studies in real production settings

  • Experience evaluating LLM or generative AI systems, or comparable experience evaluating complex ML systems where ground truth is messy

  • Proven ability to translate ambiguous failure modes into concrete, defensible evaluation designs and monitoring metrics

  • Strong fluency in Python and SQL; working comfort with modern ML tooling and cloud-native data environments

  • Experience with fairness and equity evaluation for ML systems

  • Track record of providing technical leadership and mentorship without formal people-management authority

  • Clear written communication - the role produces evaluation memos and specifications that non-technical decision-makers rely on

  • Healthcare, clinical, or regulated-industry experience strongly preferred

  • MS or PhD in a quantitative field preferred; equivalent experience accepted

Education:
Bachelor's Degree-Related Field of Study (Required)
Experience:
Minimum of 6 years-Relevant experience* (Required)
Certification(s) and License(s):
Skills:
Analyzing, processing and building AI/ML solutions from Clinical and Operational data sources, such as Epic Clarity, HL7, DICOM, or ECG data, Clinical Databases, Communication, Critical Thinking, Data Analysis, Data Presentations, Group Collaboration, Leadership, Machine Learning Methods, Programming Languages, Structured Query Language (SQL)
OUR PURPOSE & VALUES: Everything we do is about caring for our patients, our members, our students, our Geisinger family and our communities.
  • KINDNESS: We strive to treat everyone as we would hope to be treated ourselves.
  • EXCELLENCE: We treasure colleagues who humbly strive for excellence.
  • LEARNING: We share our knowledge with the best and brightest to better prepare the caregivers for tomorrow.
  • INNOVATION: We constantly seek new and better ways to care for our patients, our members, our community, and the nation.
  • SAFETY: We provide a safe environment for our patients and members and the Geisinger family.

We offer healthcare benefits for full time and part time positions from day one, including vision, dental and domestic partners. Perhaps just as important, we encourage an atmosphere of collaboration, cooperation and collegiality.
We know that a diverse workforce with unique experiences and backgrounds makes our team stronger. Our patients, members and community come from a wide variety of backgrounds, and it takes a diverse workforce to make better health easier for all. We are proud to be an affirmative action, equal opportunity employer and all qualified applicants will receive consideration for employment regardless to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or status as a protected veteran.

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