Senior AI Software Engineer (Architect of Autonomous Systems) at Ron Turley Associates LLC

Glendale, Arizona, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Jul, 26

Salary

220000.0

Posted On

14 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI, LLM fine-tuning, Orchestration frameworks, Multi-step reasoning, System design, TypeScript, Node.js, Vector databases, RAG pipelines, Python, Machine learning, Production reliability, Data flywheels, Prompt engineering, Elasticsearch, Vue.js

Industry

Software Development

Description

Description RTA is looking for a Senior AI Software Engineer who doesn't just use AI — you build the systems that run on their own. This is a role for someone who thinks in agents, reasons in pipelines, and has a track record of shipping AI systems that actually work in production — not just in demos. You'll be a core technical contributor on our AI platform efforts, helping Fleet360 evolve from a traditional FMIS into an intelligent, self-improving system that thinks alongside our customers. You will report directly to the VP of Innovation and work closely with our product and engineering leadership to design and deliver agentic AI features, self-improving systems, and intelligent automation that sets RTA apart in the market. This role isn't about writing wrappers around LLMs. It's about building the kind of AI systems that detect anomalies, recover from failure, orchestrate multi-step reasoning, and make fleets smarter — without someone holding their hand. We also believe deeply that the best AI engineers use AI heavily in their own workflows. We're looking for someone who has genuinely rethought how they work because of these tools — not someone who just knows how to talk about them. If you're the kind of engineer who builds things that run themselves, ships AI that scales, and uses every tool at your disposal to do it faster and better — we'd love to talk. What You'll Do Build Agentic AI Systems Design and ship multi-step AI agents that can reason, plan, and take action across Fleet360 data and workflows Build agent orchestration frameworks using patterns like ReAct, tool-calling, and multi-agent coordination Architect reliable agent pipelines with robust error handling, fallback strategies, and human-in-the-loop checkpoints where they matter Use orchestration frameworks (CrewAI, LangGraph etc.) to build, manage, and scale Agentic AI systems Design agents that don't just respond to requests, but proactively surface insights and take autonomous action on behalf of fleet operators Build Self-Improving Systems Design systems that observe their own outputs, measure quality over time, and automatically adjust based on what they learn from production Build feedback loops that close themselves — where model behavior, agent decisions, and pipeline outputs feed back into improved performance without manual intervention Implement continuous evaluation pipelines that track model and system quality in production, detect degradation early, and trigger retraining or recalibration automatically Design data flywheels where every user interaction makes the system smarter — capturing signal, labeling at scale, and feeding it back into fine-tuning and prompt optimization Architect systems with self-assessment built in — agents that know when they're uncertain, recognize the boundaries of their own competence, and route accordingly Fine-Tune and Adapt LLMs Run structured fine-tuning experiments on domain-specific datasets to improve model performance for fleet and maintenance use cases Design and manage evaluation pipelines that measure model quality reliably before and after changes Make principled decisions about when to fine-tune, when to prompt-engineer, and when to reach for a different tool entirely Maintain a clear-eyed view of model tradeoffs — latency, cost, accuracy, hallucination risk — and make decisions accordingly Automate Your Own Work (and Ours) Bring a genuine AI-native approach to your daily workflow — using agents, scripts, and AI tools to reduce repetitive work, accelerate iteration, and free up cognitive bandwidth for harder problems Build internal tooling and automation that helps the product & engineering team move faster Champion a culture where AI is a standard part of the engineering toolkit, not an occasional experiment Share what you're learning — your teammates should get smarter about AI because you're on the team Collaborate Across the Organization Partner with Product, Engineering, and Customer Success to identify high-value AI opportunities in Fleet360 Translate fuzzy product goals into concrete AI system designs with honest assessments of feasibility and risk Communicate clearly about what AI systems can and can't do — especially to non-technical stakeholders Contribute to RTA's broader AI roadmap and help shape how intelligence gets woven into the platform over time Our Technology Stack Our AI engineering work spans a modern SaaS platform built on Node.js, TypeScript, Microsoft SQL Server, Elasticsearch, and Vue.js, with AI systems layered on top using tools including LLMs via API (OpenAI, Anthropic, and others), vector databases, and agent frameworks. You don't need to have used every tool in our stack. What matters is your ability to learn fast, build things that hold up in production, and make sound architectural decisions when there's no clear playbook to follow. That said, candidates with real production experience in agentic AI systems and LLM-powered applications will stand out. Required Qualifications 5+ years of professional software engineering experience 2+ years of hands-on experience building production AI/ML systems — not just prototypes Deep experience designing and shipping agentic AI systems using orchestration frameworks, tool-calling, and multi-step reasoning pipelines Proven experience fine-tuning LLMs on domain-specific data, including dataset preparation, training runs, and rigorous evaluation Experience building self-improving or self-monitoring systems — systems that observe their own outputs, measure quality over time, and automatically adjust based on production signals Strong software engineering fundamentals: clean code, system design, testing, and production reliability A genuine track record of using AI heavily in your own day-to-day work — not just building it for others Experience with vector databases, embeddings, RAG pipelines, or semantic search in production environments Strong communication skills and ability to work across engineering, product, and business stakeholders What Makes Someone Successful in This Role You're someone who: Has shipped agentic AI systems in production and can talk in depth about what broke and what you learned Thinks about AI systems in terms of reliability, observability, and failure modes — not just accuracy metrics Has actually fine-tuned a model, evaluated its performance rigorously, and made principled decisions based on results Uses AI so heavily in your own work that you'd genuinely struggle to go back to how you worked before Builds things that are designed to run themselves — and thinks through what happens when they don't Communicates clearly and honestly about what AI can and can't do in a given context Thrives in an environment that rewards ownership, accountability, and continuously raising the bar Is curious enough to keep learning in a field that changes every few months — and has the fundamentals to adapt quickly We're looking for someone who doesn't just understand AI deeply — they've built systems with it that other engineers look at and say "how did you do that?" Our Culture At RTA, our culture is built around being Humble, Hungry, and Smart. We value engineers who: Care deeply about their craft Take ownership of outcomes Collaborate well with others Continuously improve themselves and their teams AI is not a side project here — it is core to where we are going. We are looking for someone who shares that conviction and is ready to help build the future of fleet intelligence. We believe the best AI engineers are strong engineers first, with a deep curiosity about what becomes possible when intelligence gets woven into software. Why Join RTA? RTA is a mature, stable, and growing SaaS company serving fleets across North America. Our software helps organizations manage the vehicles that move communities and critical services — from school buses and ambulances to transit systems and delivery fleets. We are currently experiencing ~30% year-over-year growth with ambitious plans for the next several years — and AI is central to that story. For the right engineer, this role offers: The opportunity to build AI systems that have a real impact on how fleets operate across North America A greenfield AI platform with the freedom to make foundational architectural decisions Genuine organizational commitment to AI — not a side initiative, but a core product strategy A stable, growing company where your work ships and matters If you want to spend your days building the kind of AI systems most engineers only read about, and you're ready to do it inside a company that is serious about AI — you'll find a lot of room to grow here. Compensation $180,000 – $220,000 base salary, depending on experience. About Us RTA has been established since 1979 and has the reputation of providing the best customer service in the market. Our purpose is to help fleets succeed. We pride ourselves on creating a caring, family-oriented atmosphere for both staff and clients, and love that our work makes a positive impact on all the lives we touch. Our clients carry kids in school buses, first responders in emergency vehicles, patients in ambulances, food and medical supplies in trucks, and people just taking the bus or train to work. We do meaningful work, and we want our clients to have the best tools available to them. Our office spaces are open, spacious, and colorful, with an abundance of natural light. We come together often as a company to enjoy freshly baked desserts or awesome lunches, and genuinely enjoy each other's company. We offer some pretty unique perks and benefits, as well as all the standard ones. However this role is a hybrid role with the following requirements: Ability to sit or stand for extended periods Ability to work at a computer for prolonged periods Ability to travel up to 10% (minimal travel based on business needs) Why Top Talent Chooses RTA We invest in our people - period. 401(k) + 6% Safe Harbor match (100% vested day one) Cigna PPO or HSA options with company contributions ($780–$1,950/year) Garner Health (HRA): up to $1,000 individual / $2,000 family Wellness rewards up to $350/year Virtual care + mental health support when you need it Access to legal plans, ID theft, EAP, STD & LTD benefits Flexible time off policy …and more perks and discounts designed to support you. The part we're most proud of 99% of employees say RTA is a Great Place to Work - Great Place to Work Certified (3 years running) We've also had 30% ARR growth — 2 years straight, and We are an AI-forward company — we build for the future Big growth. Real benefits. Strong culture. A team that actually delivers. Heading to RTA HQ? Coming from the east side? You'll enjoy waving at the traffic going the other way while never having to stare at the blinding sun. It only takes about 25 minutes to get here from downtown Scottsdale in the mornings. We are located close to Arrowhead Mall, with quick access to the 101 from multiple directions. If all of this sounds like you, and your type of company, then click apply! You've read this far — which tells us you're thorough, curious, and probably already thinking about how you'd architect the first agent. That's exactly the kind of person we need. Stop reading and start applying. We'll bring the desserts. Reasonable Accommodation RTA is committed to providing reasonable accommodations for qualified individuals with disabilities. If you need a reasonable accommodation to complete the application process or perform the essential functions of this role, please let us know. Equal Employment Opportunity RTA is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status. Requirements We cannot accept any student visas or provide sponsorship at this time.

Responsibilities

You will design and ship agentic AI systems and self-improving pipelines that enable autonomous fleet management. You will also collaborate with product and engineering teams to integrate intelligent automation into the Fleet360 platform.