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About This Role
About the Role
This is CWILL's first US\-based platform PM, and it's a P0 hire that reports directly to the CEO.
Your job is not to build the data infrastructure — our platform engineering team handles that. Your job is to turn what they've built into something US merchants actually want to use and pay for. You'll define the cross\-product customer journeys, design the AI Agent use cases, co\-own the GTM strategy, and spend real time with merchants figuring out which platform capabilities are worth building next.
The one\-line mission: *partner with CWILL's Platform Engineering team to turn our shared data, AI, and infrastructure capabilities into an integrated customer platform for global ecommerce brands.*
What You'll DoCustomer Discovery
- Go deep with US mid\-market Shopify merchants — understand why they run multiple tools in parallel, which workflows are still manual, and where they'd actually trust an AI Agent to act autonomously
- Spend time with Sales and CS, not just in internal meetings; validate use cases with real lighthouse customers before building
Cross\-Product Platform Design
- Design end\-to\-end customer journeys that span multiple CWILL products — for example: shipment delay support escalation compensation review recovery, or VIP churn risk marketing suppression human outreach
- Own the unified platform experience: information architecture, navigation, cross\-product workflow design
- Define what the AI Agent should do, what it should surface for human review, and how merchants understand what happened and why
AI Agent Product
- Define Agent tasks, tool\-calling scope, user permission and approval flows, error handling, and human escalation logic
- Design the merchant\-facing onboarding experience for AI features; set the bar for what "the Agent completed the task successfully" actually means
- Communicate clearly to the engineering team: we're not building another chat interface — we're building an Agent that completes a measurable merchant task
GTM \& Commercialization
- Own platform packaging and pricing decisions: what's included in base plans, what belongs in higher tiers, and how to sell a suite instead of individual apps
- Define the Lighthouse Customer program and expansion ARR playbook
- Partner with Sales and CS to drive cross\-product attach rate
Engineering Partnership
- Translate fuzzy merchant problems into crisp platform capability requirements the engineering team can build against
- Co\-own prioritization decisions — not by escalating, but by building shared judgment on what's a real customer problem vs. a nice\-to\-have
- Reduce information loss across time zones through clear written specs and documented decisions
Requirements
What We're Looking For* 5–8 years of product experience, with 2\+ years building AI or LLM\-powered products from 0 to 1
- Background in B2B SaaS — ideally multi\-product customer platforms (Customer 360, workflow automation, unified inbox, CRM, cross\-product journeys, or AI copilot/assistant features)
- Proven ability to do real customer discovery: talking to merchants, running pilots, and turning ambiguous feedback into a clear roadmap
- Fluent in AI application product design — agent task definition, tool calling, human\-in\-the\-loop flows, trust and explainability — without needing to build the underlying model infrastructure
- Comfortable working across time zones with a distributed engineering team; able to reduce coordination overhead through strong written communication
- Heavy user of AI tools (GPT, Claude, Gemini, etc.) — not as a technical requirement, but as a working style
Nice to Have
- Experience in the Shopify / DTC ecommerce ecosystem (Klaviyo, Yotpo, Aftership, Loop, Narvar, or similar)
- Seller perspective — has run an online store or worked directly with ecommerce merchants
- MarTech or post\-purchase SaaS background (marketing, support, reviews, retention)
- End\-to\-end B2B AI Agent product launch experience
Who You Are
- Startup mindset — you're comfortable making decisions with incomplete information and iterating fast
- You think in customer outcomes, not feature lists
- You'd rather spend a day with a merchant than a week writing specs no one's validated
- Big company or startup background doesn't matter — ability and judgment do
Benefits
Starting Pay: 150K\-200K depends on experiences, open to negotiation
- *401(k)*
- *PTO*
- *Paid Holidays*
- *Insurance*
Salary Context
This $150K-$200K range is below the median for AI Agent Developer roles in our dataset (median: $200K across 33 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Cwill, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $240,000 based on 96 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($175K) sits 27% below the category median. Disclosed range: $150K to $200K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Cwill AI Hiring
Cwill has 1 open AI role right now. They're hiring across AI Agent Developer. Based in NC, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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