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About This Role
Welcome to the Agentic Commerce Era
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At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI\-driven commerce ecosystem. As the parent company of BigCommerce , Feedonomics , and Makeswift , we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever\-changing market. We believe in harnessing AI responsibly to unlock new possibilities, and we’re looking for individuals who use it intentionally to solve problems, accelerate outcomes, and expand what’s possible in their role. Our purpose is to help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers who shape the future of commerce, this is the place for you.
This role is central to Commerce’s growth engine. You will sit at the heart of our most important strategic bet: becoming the essential data infrastructure layer that makes merchants discoverable and purchasable across AI\-native channels. You will own high\-impact product and commercial relationships with Google, Meta, OpenAI, Amazon, eBay, Walmart, and other leading platforms and marketplaces, while driving data syndication, feed optimization, agentic capabilities, and broader commerce ecosystem partnerships.
You will combine sharp business development instincts with strong product acumen and technical intuition to initiate product\-led discovery, shape integrations, launch GTM motions, grow pipeline, and deliver Partnership \& Services Revenue (PSR). You will also act as a trusted strategic advisor to leadership on partner roadmaps, regional dynamics, agentic opportunities, and ecosystem shifts.
You will work closely with the established agency partner team to initiate collaborations, align efforts, and drive joint go\-to\-market impact for merchants.
If you excel at the intersection of deep platform relationships, product strategy, and revenue execution \- and have a proven ability to win and scale partnerships with tech giants this is a rare opportunity to help define the future of agentic commerce.
BigCommerce, part of the Commerce brand family, helps merchants increase sales at every stage of their growth. From small startups to mid\-market businesses and large enterprises, we provide the leading e\-commerce platform. Our customers can then concentrate on what's most important: growing their businesses. We enable our customers to build, innovate, and grow, collectively reshaping the e\-commerce industry.
What You’ll Do
- Own Strategic Platform Partnerships: Lead end\-to\-end relationships with major platforms (Google, Meta, OpenAI, etc.) and marketplaces (Amazon, eBay, Walmart, etc.), driving both advanced product integrations (with strong emphasis on agentic/AI capabilities) and commercial expansion
- Accelerate Product\-Led GTM Motions: Design and execute tailored strategies that boost adoption, deepen technical integrations, and deliver outsized value for merchants across regions and verticals
- Drive Revenue \& Pipeline Growth: Consistently deliver against Partnership \& Services Revenue (PSR) targets by identifying, negotiating, and closing high\-value opportunities
- Expand Scope \& Deepen Relationships: Cultivate executive and working\-level relationships that evolve into broader collaborations, higher attach rates, and mutual growth
- New Partner Acquisition: Proactively source, qualify, and land new high\-potential partners that strengthen CMRC’s position in the data and commerce ecosystem
- Cross\-Functional Collaboration: Partner closely with Product, Engineering, Sales, Marketing, Customer Success, and the agency partner team to ensure seamless execution, high\-quality integrations, and strong merchant outcomes
- Strategic Intelligence: Deliver ongoing insights on partner roadmaps, competitive moves, agentic trends, and market dynamics to directly influence product and company strategy
- Negotiation \& Deal Execution: Lead complex negotiations and structure agreements that balance ambitious strategic value with strong commercial terms
- Performance Ownership: Track, analyze, and report on key partnership KPIs, revenue, pipeline health, and ecosystem impact
Success Metrics
- Measurable growth in Partnership \& Services Revenue (PSR) and pipeline from platform and agency relationships
- Expanded integrations and successful GTM execution with priority partners (Google, Meta,, etc.)
- High partner satisfaction, increased adoption/attach rates, and broadened scope of collaborations
- Actionable strategic insights that shape product direction and company priorities
- Reputation as a high\-performing, trusted partner to the most important platforms in AI and commerce
Who Are You
- 8–12\+ years in strategic business development, platform partnerships, or ecosystem roles at high\-growth SaaS, commerce, or data companies
- Minimum B.S. Business Management, B.S. Finance, B.S. IT Management etc…
- Proven track record building and scaling relationships with major tech platforms (Google, Meta, OpenAI, Amazon, etc.) and/or large marketplaces
- Strong product acumen and technical instincts \- able to comfortably lead product\-led discovery, navigate technical conversations, and translate partner needs into high\-value integrations and GTM motions
- Direct experience driving measurable revenue through partnerships (PSR or equivalent) with clear ownership of targets
- Exceptional negotiation and deal\-structuring skills with a win\-win mindset at scale
- Highly strategic yet execution\-focused \- thrives as a senior individual contributor who influences without authority in a fast\-moving environment
- Deep knowledge of ecommerce data feeds, syndication, marketplaces, and modern commerce/AI tech stacks is a strong plus
- Outstanding communicator and relationship builder who operates with urgency and autonomy \- the agentic window is open now.
- Ability to travel up to 20% of the time
This role offers significant autonomy, high visibility, and direct access to the biggest names in tech and commerce. You’ll help shape the next era of agentic commerce while driving real revenue impact.
If you’re a top\-tier partnerships professional who loves winning strategic deals and driving meaningful product outcomes, we’d love to hear from you.
Compensation Transparency
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The national base salary range for this role is posted above in this job post.
Final compensation will be determined based on factors such as relevant experience, skills, qualifications and geographic location. We also consider internal equity to help ensure fair and consistent pay practices across our teams.
Where applicable, this role may also be eligible for variable compensation (such as bonus or commission), equity, and benefits in accordance with local policies. Details will be shared during the hiring process. We are committed to equitable and transparent pay practices that align to market data, internal equity, and individual contribution.
Inclusion and Belonging
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At Commerce, we believe that celebrating the unique histories, perspectives and abilities of every employee makes a difference for our company, our customers and our community. We are an equal opportunity employer and the inclusive atmosphere we build together will make room for every person to contribute, grow and thrive.
We are committed to creating an inclusive and accessible hiring experience for all candidates. If you require accommodations or adjustments at any stage of the recruitment process, please let us know and we will work with you to meet your needs.
Learn more about the Commerce team, culture and benefits at https://www.commerce.com/careers/
Protect Yourself Against Hiring Scams: Our Corporate Disclaimer
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Commerce, along with many other employers, has become the subject of fraudulent job offers to hopeful prospective job seekers.
Be advised:
Commerce does not offer jobs to individuals who do not go through our formal hiring process.
Commerce will never:
- require payment of recruitment fees from candidates;
- request personally identifiable information through unsanctioned websites or applications;
- attempt to solicit money from you as part of the hiring process or as part of an employment offer;
- solicit money to complete visa requirements as part of a job offer.
If you receive unsolicited offers of employment from Commerce, we urge you to be extremely cautious and avoid engaging or responding.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Commerce, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Commerce AI Hiring
Commerce has 3 open AI roles right now. They're hiring across AI Agent Developer, AI Software Engineer, AI/ML Engineer. Based in Austin, TX, US. Compensation range: $160K - $195K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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