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About This Role
Location
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Irvine, California
Employment Type
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Full time
Location Type
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Hybrid
Department
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Technology and Innovation
Compensation
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- $149\.8K – $187\.2K • Offers Equity • Offers Bonus
The posted salary represents the lowest and highest ranges RV Tech reasonably and in good faith expects to pay for the position. Any posted salary range pertains only to the estimated starting pay for the role. Actual starting pay is based on a number of factors, including, but not limited to, the candidate’s experience, skillset, qualifications, specific competencies, relevant education, and location.
About Us
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Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software\-defined vehicles around the world.
The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone.
Rivian and Volkswagen Group Technologies Canada is proud to be a Great Place To Work® Certified company — 92% of employees at RV Tech Canada say it is a great place to work, compared to 60% at a typical company.
Role Summary
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As a Senior Software Engineer specializing in agentic applications, you will be a key technical leader and influential voice in shaping our GenAI platform's architecture and strategy. You will play a pivotal role in integrating LLMs with our internal and customer\-facing applications at scale. Your focus will be on leveraging LLMs to drive cognitive automation, streamlining workflows, and enhancing decision\-making. You'll also pioneer and evangelize best practices in building resilient, scalable, and observable distributed systems, ensuring the creation of production\-grade tools that are scalable, reliable, and maintainable across the organization.
Responsibilities
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- Architect Design of Agentic Systems: Architect and lead the development of highly scalable and sophisticated intelligent agents that utilize LLMs to automate workflows, optimize operations, and elevate user experiences across our internal and customer\-facing applications.
- Shape LLM Integration Strategy: In partnership with your peers, help define and drive the technical vision and long\-term strategy for integrating LLMs with our evolving software ecosystem, ensuring robust, scalable, and maintainable communication and data exchange.
- Drive the Cognitive Automation Roadmap: Collaborate with product managers and other technical leaders to identify and prioritize high\-impact opportunities for cognitive automation. Leverage LLMs to automate complex cognitive tasks, such as information extraction, summarization, and question answering, to enhance efficiency and accuracy system\-wide.
- Champion Scalable System Design: Take ownership of the entire development lifecycle, from conceptualization and design to implementation and deployment, for our most critical machine learning\-powered tools and applications.
- Establish and Uphold Engineering Best Practices: Define, implement, and enforce industry\-leading standards for building production\-grade, distributed machine learning solutions, ensuring scalability, reliability, and maintainability.
- Drive Technical Consensus and Influence Direction: Continuously research and experiment with emerging trends in machine learning, AI agents, and distributed systems.
- Collaborate and Lead Cross\-Functionally: Work closely with Machine Learning engineers, product teams, and senior leadership to gather requirements, define project scope, and deliver impactful solutions. Drive technical alignment across multiple teams.
- Mentor and Develop Technical Talent: Share your expertise and provide guidance to senior engineers and technical leads, fostering a culture of technical excellence, innovation, and continuous learning.
Qualifications
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- Advanced Degree: Bachelor's, Master's degree or Ph.D. in Computer Science, Machine Learning, or a related field.
- Proven Experience: 8\+ years of hands\-on experience in software engineering, with a deep focus on designing and building large\-scale distributed systems. Extensive, hands\-on experience in building and deploying complex agentic applications leveraging LLMs in production environments.
- Strong Technical Skills: Expertise in Golang is strongly preferred. Proficiency in Python or similar programming languages, as well as deep expertise with cloud and container frameworks such as AWS and Kubernetes. A proven track record of designing and building highly scalable, fault\-tolerant, and observable distributed systems.
- Deep Understanding: Expert\-level grasp of machine learning principles, algorithms, and evaluation metrics, as well as software engineering best practices for distributed systems.
- Production Experience: Demonstrated success in leading the design, deployment, and operation of scalable backend software in high\-stakes production environments.
- Collaborative Spirit and Technical Leadership: Excellent communication and teamwork skills, with a proven ability to influence, build consensus with senior engineering peers, and align cross\-functional teams and senior stakeholders on complex technical decisions.
- Passion for Innovation: A genuine interest in exploring the latest advancements in machine learning and natural language processing and applying them to solve impactful business challenges at scale.
Total Rewards
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Full\-time positions include base salary, eligibility for an annual performance bonus, and eligibility for equity.
In addition to base salary, Rivian and Volkswagen Group Technologies offers benefits tailored to the local market. For more information on the benefits available for full\-time employees, check out our Global Benefits Site.
External candidates can apply for this role through the Rivian and Volkswagen Group Technologies careers site (https://rivianvw.tech/\#careers).
Equal Opportunity
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Rivian and Volkswagen Group Technologies 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, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. We are also committed to ensuring compliance with all applicable fair employment practice laws regarding citizenship and immigration status.
Rivian and Volkswagen Group Technologies is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at [email protected].
Candidate Data Privacy
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Rivian and Volkswagen Group Technologies” may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian and Volkswagen Group Technologies may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) record keeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.
Rivian and Volkswagen Group Technologies may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian and Volkswagen Group Technologies affiliates; and (iii) Rivian and Volkswagen Group Technologies’ service providers, including providers of background checks, staffing services, and cloud services.
Rivian and Volkswagen Group Technologies may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.
If you provide a mobile telephone number as part of your application or during the recruitment process, Rivian and Volkswagen Group Technologies may use that number to contact you via SMS text message for recruitment\-related purposes, including scheduling, logistics, and status updates. Message and data rates may apply. You may opt out of SMS communications at any time by replying STOP to any text message you receive from us. Consent to receive SMS messages is not a condition of applying for or being considered for employment.
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*Please note this job posting represents an open, active vacancy. Additionally, we are not currently accepting applications from third party application services.*
Salary Context
This $149K-$187K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 251 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Rivian and Volkswagen Group Technologies, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 863 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($168K) sits 27% below the category median. Disclosed range: $149K to $187K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Rivian and Volkswagen Group Technologies AI Hiring
Rivian and Volkswagen Group Technologies has 3 open AI roles right now. They're hiring across AI Software Engineer, Data Engineer. Positions span Palo Alto, CA, US, Irvine, CA, US. Compensation range: $106K - $258K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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