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Ai Program Manager Jobs in Atlanta, GA (NOW HIRING)

Technical Program Manager

Atlanta, GA · On-site

$124K - $160K/yr

NexusOne is a converged data platform for the AI era, focused on delivering sovereign data and interoperable systems. The Technical Program Manager will own solution delivery for strategic accounts ...

DevOps Platform Engineer

Duluth, GA · On-site

$48.50 - $66.50/hr

The DevOps Engineer is a prerequisite for the AI program - without reliable infrastructure, no agent or model can be deployed to production. Responsibilities * Provision and manage the agentic AI ...

Senior Manager, Business Transformation (Transaction) Pay Range: $125,000 - $155,000/year + 15 ... AI improvements to simplify end-user workflows. * Drive cultural transformation by promoting ...

Experience with cloud data/AI ecosystems (Azure, AWS, or GCP) and common platforms/tools (e.g ... Program/project management certification (PMP, PRINCE2) and/or agile certification (CSM/PSM, SAFe)

As a Program Manager at Google, you'll lead complex, multi-disciplinary projects from start to ... The AI and Infrastructure team is redefining what's possible. We empower Google customers with ...

Business Program Manager - SLED

Atlanta, GA · On-site

$48K - $53K/yr

The Public Sector Program Management & Operations Manager will lead and strengthen our Public ... Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently ...

Showing results 41-60

Ai Program Manager information

See Atlanta, GA salary details

$37K

$103.3K

$151K

How much do ai program manager jobs pay per year?

As of Aug 8, 2026, the average yearly pay for ai program manager in Atlanta, GA is $103,340.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,500.00 and $127,400.00 per year, depending on experience, location, and employer.

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.

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 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 popular job titles related to Ai Program Manager jobs in Atlanta, GA? For Ai Program Manager jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Ai Program Manager jobs in Atlanta, GA look for? The top searched job categories for Ai Program Manager jobs in Atlanta, GA are:
What cities near Atlanta, GA are hiring for Ai Program Manager jobs? Cities near Atlanta, GA with the most Ai Program Manager job openings:
Infographic showing various Ai Program Manager job openings in Atlanta, GA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $103,340 per year, or $49.7 per hour.

Technical Program Manager

NexusOne

Atlanta, GA • On-site

$124K - $160K/yr

Full-time

Re-posted 20 days ago


Job description

Job Summary:
NexusOne is a converged data platform for the AI era, focused on delivering sovereign data and interoperable systems. The Technical Program Manager will own solution delivery for strategic accounts, translating customer needs into actionable requirements and ensuring successful engagement outcomes.
Responsibilities:
• A portfolio of 2–4 strategic NX1 accounts, $5–10M each in delivery / managed services revenue
• Gross margin management for the portfolio. You own the unit economics: cost-to-serve per account, scope discipline, hero-engineer-attrition risk, custom work that doesn't generalize. Margin is not finance's job to track — it's yours to manage, with finance providing the books
• The P&L for those accounts — drive against deliverables AND against gross margin; surface risk on both before it's a number on the dashboard
• The customer-side executive relationship: their VP of Data / CDO / CTO knows you by name and treats you as a peer, not a vendor
• Renewal and expansion strategy, in partnership with the CRO — you don't carry quota, but you shape the conditions under which the customer grows
• Stand up the delivery program on day 1 of a new engagement: roadmap, milestones, dependencies, governance, communication cadence
• Run the weekly operating rhythm — internal stand-ups, customer syncs, exec readouts, escalation reviews — and build the artifacts that keep them grounded in reality, not theater
• Own the documentation surface for each engagement: program plan, decision log, RAID register, exec status, runbooks, the customer-facing roadmap view
• Own the bidirectional translation between the customer's business problem and NX1's engineering reality — surface the right requirements into the org, surface engineering trade-offs back to the customer, without distorting either side
• This is the craft of the role: customers don't hand you a requirements doc that's correct. You build it together, in conversation, by knowing what to ask and what to push back on
• Pull in Solution Architects when the work needs architecture depth; pull in FDEs / engineers when the work needs to be built
• Hold the line on technical commitments: what's in scope, what's a roadmap ask, what's a one-off custom build the engagement can't absorb
• Be the person who reads the architecture doc, asks the sharp question, and writes the one-page summary the customer's CTO actually reads — and the one-page brief the engineering team uses to scope the work
• Define what 'winning' looks like for each customer in writing within the first 60 days of an engagement — and instrument it
• Build the customer-health signal that catches problems 60 days before they become escalations: usage trajectory, executive sentiment, milestone slippage, support ticket pattern, roadmap dependency drift
• Run quarterly business reviews that the customer's exec team treats as the most useful meeting of the quarter
• Convert customer pain back into product roadmap input — and close the loop when it lands
• Partner with the CRO on expansion conversations — you bring the technical credibility and the lived relationship; they bring the commercial framing
• Hold the cost-to-serve number for your engagements: what's in scope of the managed service vs. what's a paid one-off vs. what's a roadmap ask
• Spot the early signals of churn risk and escalate them before they harden
• Write the renewal narrative: not the deck the CRO uses to close, but the substance — what we delivered, what changed for the customer, what's next
• This is a builder seat, not a maintainer seat. You will define the engagement playbook for NX1, not inherit it
• Codify what works across your portfolio into reusable artifacts the next FDEM hire benefits from
• Influence the operating model between Forward Engineering, the MSO function, and Sales — where the seams are, who owns what at each phase, how handoffs actually work
Qualifications:
Required:
• 5–8 years in a customer-facing solution delivery, consulting, or forward-deployed role: Forward Deployed Engineer, Engagement Manager (consulting or product), Solutions Architect with delivery scope, strategic-level Technical Account Manager, Customer Engineering Lead, Implementation Lead, or equivalent
• Operationally rigorous. Strong track record of delivering against customer needs — not activity-shaped ('I ran the program') but outcome-shaped ('the customer got X and here's specifically how I made it land')
• Has personally owned a customer's outcome end-to-end at an enterprise account — not just 'contributed to' or 'supported'
• Communicates with precision across levels. Same person can hold the engineer's whiteboard conversation, the VP-level steering committee, and the C-suite QBR without changing who they are — only the register
• Bidirectional translator. Has owned the act of translating customer requirements into something the engineering org can actually build, and engineering trade-offs into something the customer's exec team can actually decide on
• Problem ownership mindset. Reflex when something breaks is to own it until it's not, regardless of whose 'job' it is
• Consulting EM intrinsics paired with founding mindset. Carries the structural muscle of a top-tier consulting engagement manager (McKinsey / BCG / Bain / Palantir lineage — client management, structured thinking, exec presence, written clarity) and the entrepreneurial streak of a founder — builds the playbook rather than follows one
• Has worked inside a startup or scale-up engineering organization (Series A through D) — knows what it looks like to operate when the org chart is still being drawn
• Fluent enough technically to read an architecture doc, ask the right questions, and not need a translator in an engineering room. Data, cloud, or platform infrastructure background strongly preferred
• Has run modern program tooling — Linear and Notion specifically, or has switched to them from Jira/Asana/Confluence and can articulate why
• Strong written communication. Status updates that move decisions. Postmortems people read. Memos that change minds
• High agency. Will close their own loops, will not wait for someone else to define the playbook, will push back constructively when the company is wrong
Preferred:
• Has worked at Palantir (FDE), Anthropic / OpenAI (FDE / Solutions), Databricks (Field Eng / CE), Stripe (Implementation / Solutions), Ramp / Mercury (Solutions), Scale AI (FDE), or a comparable forward-deployed environment
• Has carried direct gross margin or P&L responsibility on accounts — not just hit milestones
• Engineering background somewhere in their history (CS degree, eng IC role, or a credible technical foundation built on the job)
• Has been the person who wrote the playbook, not just executed someone else's
Company:
NexusOne is the composable data architecture for the AI era — the first product to deliver a universal control plane across the entire data estate. Founded in 2019, the company is headquartered in Addison, USA, with a team of 51-200 employees. The company is currently Growth Stage.