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About This Role
*7\-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation — working hard to be the customer's first choice. 7\-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.*
Job Description
7\-Eleven is looking for a Staff Engineer \- Agents to join the Enterprise AI Team!
At 7\-Eleven Enterprise AI Team, we’re creating the next generation of convenience, and we know that the best way to do that is with great people. If you get excited about working on challenging problems and owning a solution from concept to implementation, read on.
About the job:
You’ll be joining a multidisciplinary team of scientists, researchers and engineers who research and innovate on latest technology to create awesome AI products that millions of people will experience every day.
Staff Engineers at 7\-Eleven have a large amount of experience across multiple areas and lead system architecture, guiding developers and communicate progress against the technical roadmap and backlog. They can plan, coordinate, and deliver large tasks spanning multiple systems, and are strong communicators. They actively coach and mentor developers on their development team and can identify and resolve issues with technology and software development processes.
As a Staff Engineer, you will not only help teams navigate technical problems but grow and coach developers on your team to write scalable, resilient, and robust software and systems. Note that most engineers will typically spend up to 30\-50% of their time designing and building software, with their remaining time being committed to architecting/planning, mentoring, and technical exploration.
Key Responsibilities:
As a Staff AI Engineer specializing in Agents and LLMs, you will:
- Lead the design, development, and implementation of advanced agentic systems and algorithms.
- Architect, design, develop, and deploy AI models across traditional and agentic solutions.
- Build and deploy high\-impact, robust AI pipelines, including data extraction, feature development, model training, testing, and deployment
- Conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across multiple regions and product areas.
- Ability to conduct thorough exploratory data analysis, identify patterns and trends, and draw meaningful insights.
- Learn and partner with peers across multiple disciplines, such as Data Engineering, Product and Platform.
- Monitor and maintain production models, ensuring their continued performance and reliability.
- Evaluate and grow technical talent throughout the AI team, with a focus on subject matter expertise.
- Represent the Enterprise AI teams in cross\-functional meetings with other technical teams.
- Stay up to date with emerging technologies and learn new technologies/libraries/frameworks.
- Deliver on time with a high bar on quality of research, innovation and engineering
Basic Qualifications:
- 6\+ years of experience working in a technical AI role, with 2 to 3 years in a senior technical AI role.
- 4\+ years of experience building AI models and solutions from research to production, using common ML frameworks like scikit\-learn, TensorFlow, PyTorch, LangChain/LangGraph etc.
- 2\+ years of experience building LLM based Chat and Agentic Assistants, and building scalable products for 1000\+ users.
- 2\+ years of experience reviewing and refining AI architecture and conducting code reviews.
- 2\+ years of experience leading a team of engineers in a technical lead capacity.
- Experience with major cloud platforms (AWS/GCP/Azure), building and deploying scalable AI systems.
- Strong understanding of LLM models, LLM Engineering architecture and ecosystem, including context, tools, skills, harness etc, with demonstrated delivery.
- Bachelor’s Degree or higher in Computer Science/Engineering/Math, or relevant experience.
Preferred Qualifications:
- MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
- Experience with Databricks.
- Experience building and scaling custom Chatbots and Multi\-Agent systems successfully.
- Experience training and evaluating AI models.
- Experience delivering production quality systems leveraging emerging technologies.
*If an hourly or salary range is included in this ad it represents the range 7\-Eleven in good faith believes is the range of compensation for this role at the time of this posting. The Company may ultimately pay more or less than the posted range. This range is only applicable for jobs to be performed in this state. This range may be modified in the future. No amount is considered to be wages or compensation until such amount is earned, vested, and determinable under the terms and conditions of the applicable policies and plans. The amount and availability of any bonus, commission, long\-term incentive compensation, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.*
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 3,708 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At 7-Eleven, 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 $238,500 based on 58 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000.
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.
7-Eleven AI Hiring
7-Eleven has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer. Based in Irving, TX, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 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).
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 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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