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About This Role
Since our founding in 2012, Lotlinx has consistently pioneered advancements in the automotive landscape. We specialize in empowering automobile dealers and manufacturers by providing cutting\-edge data and technology, delivering a distinct market advantage for every single vehicle transaction. Today, we stand as the foremost automotive AI and machine learning powered technology, excelling in digital marketing, risk management, and strategic inventory management.
Lotlinx provides employees with a dynamic work environment that is challenging, team\-oriented, and full of passionate people. We offer great incentives to our employees, such as competitive compensation and benefits, flex time off, and career development opportunities.
### Job Summary
Our CRM team has spent years building a Salesforce foundation that is incredibly rare: clean data models, well\-architected automation, and rock\-solid processes across Sales, Marketing, and Finance.
Instead of scaling our operations through linear, traditional headcount, we are building an AI\-first RevOps engine. We are looking for a Admin \& AI Architect to step into this custom\-built environment and build specialized, autonomous AI agents that handle complex Salesforce administration, data analysis, and custom development. These agents will serve as a digital workforce, empowering our RevOps team by automating complex tasks in Salesforce administration, data analysis, and custom development. This is a rare opportunity to pioneer a self\-governing system within a clean CRM environment. You are not just building tools; you are architecting a digital workforce that acts as a massive force multiplier for our entire organization.
### Key Responsibilities
You will be the architect and admin of Lotlinx's autonomous RevOps engine, focused on designing, deploying, and governing a fleet of AI agents in addition to administration of our Salesforce platform.
- Define the AI integration strategy across the full RevOps stack, identifying where multi\-step agent workflows can completely automate heavy manual processes.
- Serve as the absolute authority on AI and Salesforce architecture, ensuring our org design is optimized for LLMs and agentic interaction.
- Establish rigorous guardrails and evaluation frameworks to ensure AI\-generated configurations, code, and documentation meet a flawless production bar before deployment.
- Lead the evaluation of bespoke third\-party agent frameworks versus native AI tooling with a strong preference for external agents to ensure Lotlinx leads the industry in autonomous operations.
### Qualifications
- Bachelor’s degree or equivalent professional experience.
- Deep Salesforce fluency (2\+ years in admin/developer type roles) where you've written complex Apex, navigated metadata APIs, and understand what breaks an enterprise org. We care about depth of knowledge over years on a resume (admin/architect certs preferred).
- You have hands\-on experience building autonomous multi\-agent systems using frameworks like LangGraph, CrewAI, or AutoGen.
- Deep understanding of prompt engineering, RAG architectures, and routing logic using the OpenAI or Anthropic APIs.
- You see the whole board. You know how to break down a complex RevOps problem into discrete, automatable tasks that a digital worker can execute safely.
- Comfort writing and reviewing code across Python (for AI orchestration) and Apex/JavaScript (for Salesforce).
- Bonus points for candidates who are actively excited about utilizing Claude / Claude Code for complex multi\-agent logic and code generation, rather than just general framework users.
*A Note on Experience:* *We value production scars over a list of certifications. We want the person who has actually tried to put an autonomous agent into a production environment, broke things, learned from it, and knows how to build the necessary guardrails.*
### How Success is Measured
- Is the RevOps engine shipping faster and more reliably because your agents are handling the heavy development and administrative load?
- Your agents operate behind robust human\-in\-the\-loop guardrails and automated test coverage that you designed. Regressions don't reach production because your review architecture catches them first.
- Are Finance, Marketing, Sales, Account Management and Product Operations getting compounding value from Salesforce via the intelligent systems you’ve deployed?
The salary range for this position is $110,000 \- $120,000 with an annual target bonus.
Lotlinx provides a comprehensive benefits package.
Lotlinx is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Lotlinx is not currently able to offer sponsorship for employment visa status.
Lotlinx is headquartered in Peterborough, NH and has locations in Holmdel NJ, Manitoba, Ontario and British Columbia, Canada in addition to a large team spanning from the US to Canada.
Our success relies heavily on our customers but also our dedicated talent that continuously moves our platform forward. We value our employees, their abilities and seek to foster an open, cooperative, dynamic environment where the team and company alike can thrive.
Salary Context
This $110K-$120K range is in the lower quartile for AI Architect roles in our dataset (median: $180K across 25 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 3,824 AI roles we're tracking, AI Architect positions make up 1% of the market. At LotLinx, Inc., this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $220,000 based on 92 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($115K) sits 48% below the category median. Disclosed range: $110K to $120K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
LotLinx, Inc. AI Hiring
LotLinx, Inc. has 1 open AI role right now. They're hiring across AI Architect. Based in Chandler, AZ, US. Compensation range: $120K - $120K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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