Jobs in United States

Program Manager in United States

2,417 active opportunities · Updated October 2026

Explore current program manager jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

Hiring demand

44/100

watch · 162 related jobs

Hiring trend

-67.2%

Job postings compared with the previous 30 days

Remote options

22.8%

Share of matching jobs listed as remote

Typical salary

$145.7K – $145.7K/yr

Based on 12 salary observations

S
📍 Menlo Park, California, United States· Full-time
✓ Quality checkedCompany trend -93.3%

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is seeking an Enablement Business Partner to serve as the Chief Activation Officer for our Solution Engineering team. Embedded within key leadership teams, you will accelerate field capability tied to business outcomes, owning the full spectrum of how SEs learn, from structured programs to in-the-moment performance support. You translate business problems into capability solutions, designing systems that make the field more capable when and where it matters most. IN THIS ROLE YOU WILL GET TO: Act as the strategic enablement partner for SE leadership, diagnosing skill gaps tied to business outcomes, prescribing targeted interventions, and measuring whether capability actually changed Curate and quality-gate enablement content: validate AI outputs for accuracy and audience fit, maintain a source of truth for your domains (theater and product), and feed evidence-based quality signals back to PM and PMM Diagnose field needs through signals (Gong, Salesforce, theater-level data analysis, leadership conversations, steer co themes, PM roadmap changes, etc), then classify and prioritize gaps with data Design activation experiences, picking the right modality (hands-on or self-serve lab, AI skill, peer learning, coaching nudge), and measuring behavior change, not just comp

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S
📍 Menlo Park, California, United States· Full-time
✓ Quality checkedCompany trend -93.3%

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As a Senior Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures

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