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About This Role
Location
Remote - EMEA
Employment Type
Full time
Location Type
Remote
Department
ProductProduct Design
About Us
Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we’ve built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We’re passionate about maintaining this and work on the bleeding edge of AI to do so.
Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco.
We’re a passionate team who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things.
Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today.
About You
You're a product designer who owns problems, not screens. You're comfortable with ambiguity, can partner with PMs to shape direction, and know how to translate research insights into production-ready interfaces, working closely with engineers. You ship work that matters.
The Team
Our AI Agent Tools team is building a new category of e-commerce experience: intelligent agents that guide shoppers, learn from merchandiser expertise, and drive real business outcomes. This is one of the most consequential design problems in retail right now, and it's wide open.
Requirements
The Role
You'll be designing the future of product discovery: the moment a shopper goes from intent to purchase, reimagined through AI.
- You'll define what agentic shopping looks like — Not just chatbots bolted onto search, but genuinely new interaction patterns where AI understands what a shopper wants and helps them get there. There's no established playbook here. The patterns you set will shape how the rest of the industry approaches it.
- You'll shape how merchandisers control it — You will collaborate with Agent Orchestrators—professionals blending data analysis, design, and shopper psychology—to design the dashboard tools that allow them to configure, train, and optimize new shopping journeys without engineering support.
- You'll prove it works in the real world — From running UI experiments on live retailer sites to validating new shopping experiences with actual shopper data, your designs ship and get measured.
What You'll Own
- Research & validation — Conducting shopper research and running experiments alongside product and data teams to validate hypotheses with real input.
- Interaction design for agentic experiences — Mapping novel user flows where AI/LLMs drive the shopping journey, for both shoppers and the merchandisers who orchestrate them.
- Visual strategy — Defining a bold design direction that represents what product discovery looks like in 2027.
- High-fidelity delivery — Producing final mockups and assets across key surfaces: homepage, search, PDP, filtering, guided shopping, and agent configuration.
- UX patterns — Ensuring designs scale within Constructor's evolving design system and component library.
What We Value Beyond Craft
Beyond being a thoughtful designer, user advocate, and strong collaborator, here are a few things we really value:
- A goal-oriented, iterative mindset — You focus on solving high-impact problems and are comfortable learning, improving, and shipping quickly.
- Practical experience with research — You’ve led user interviews, usability tests, and data analysis.
- Experience designing for unfamiliar problems — You’ve worked on products where you had to understand complex workflows outside your own experience—especially in B2B contexts.
- Systems thinking — You spot patterns, define systems, and design scalable, reusable solutions.
Benefits
- Work with smart and empathetic people who will help you grow and make a meaningful impact.
- Regular team offsite events to connect and collaborate.
- Fully remote team - choose where you live.
- ️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year.
- ️ Work from home stipend! We want you to have the resources you need to set up your home office.
- Apple laptops provided for new employees.
- Training and development budget for every employee, refreshed each year.
- Maternity & Paternity leave for qualified employees.
- Stock options - offered in addition to the base salary
Diversity, Equity, and Inclusion at Constructor
At Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group.
Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications.
How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice. After that period your data will be deleted or anonymized.
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 9,653 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Constructor, 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 $214,400 based on 180 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Constructor AI Hiring
Constructor has 7 open AI roles right now. They're hiring across AI Agent Developer, AI/ML Engineer. Based in Remote, US. Compensation range: $120K - $130K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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