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About This Role
Job Description
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Austin TX IT Innovation Center 3\-4 days per week (T\-W\-Th)
Who We Are
We are the Brands \& Marketing Software Engineering Team within the Digital Products Engineering (DPE) organization at GM. Our team collaborates closely with marketing leaders from across GM to build easy\-to\-use tooling that powers engaging and innovative customer experiences at scale — including AI\-powered discovery and search experiences — while providing meaningful value to our customers through a seamless customer journey.
Our mission is to rapidly and relentlessly ideate, iterate, and launch the next generation of innovative solutions to connect GM with current and future customers, increasingly leveraging Google Cloud Platform (GCP) and Vertex AI Search to deliver intelligent, personalized digital experiences.
Our team comprises industry\-leading software and quality engineers, who utilize a variety of innovative development methodologies and technologies to achieve breakthrough results, drive innovation, and delight customers.
The Role
We are looking for an exceptional Senior Software Engineer (Full Stack Web) who is excited about building high\-impact web products across General Motors and designing intelligent search and discovery capabilities on Google Cloud Platform using Vertex AI Search .
You will be responsible for helping lead our engineering efforts across planning, design and architecture, execution, and ramp — with a particular emphasis on:
- Building modern web applications that integrate with GCP\-native services
- Designing and implementing AI\-powered search experiences leveraging Vertex AI Search
- Collaborating with product, marketing, and data/ML partners to experiment, measure, and continuously improve search relevance and customer engagement
- As a technical leader on the team, you will mentor less experienced engineers, build strong relationships with technical leaders on other teams, and help evolve our engineering culture and best practices.
What You’ll Do
- Develop competency across our complete web technologies stack (client, framework, and services).
- Produce high quality software that is unit tested, reviewed, and checked in regularly for continuous integration and deployment.
- Serve as a tech lead , actively mentoring other engineers on the team and helping drive technical decisions and tradeoffs.
- Investigate and resolve performance bottlenecks across the full stack, including browser, edge, and cloud services.
- Lead efforts to automate testing, quality gates, and delivery pipelines , with a strong focus on reliability and observability.
- Work on API , Content Management , edge , and cloud systems that power GM brand and marketing experiences.
- Leverage your technical leadership to ensure we adhere to engineering best practices and evangelize opportunities to improve engineering productivity, and craftsmanship.
With a specific focus on Google Cloud Platform and Vertex AI Search , you will:
- Design and build web applications and services on GCP , leveraging services such as Cloud Run, GKE, Cloud Functions, Pub/Sub, Cloud Storage, Cloud SQL/Spanner, and BigQuery where appropriate.
- Implement and integrate Vertex AI Search to power intelligent search, semantic retrieval, and content discovery across GM’s digital products (e.g., marketing sites, owner experiences, support content).
- Define and evolve search schemas, indexing pipelines, and relevance signals (e.g., metadata, event telemetry, personalization signals) to continuously improve search quality and user satisfaction.
- Collaborate with data science and ML partners to productionize and iterate on search and recommendation models using Vertex AI, including experimentation frameworks and A/B tests.
- Build robust, secure APIs and backend services that expose search and recommendation capabilities to web and mobile clients.
- Partner with product and UX to design search\-centric user experiences (autocomplete, facets, filters, recirculation modules, recommendations, etc.) informed by analytics and experimentation.
- Lead the design and development of an enterprise\-wide search platform that unifies discovery across brands, channels, and content sources, starting with a Vertex AI Search–based implementation.
- Define clear abstraction layers, contracts, and interfaces (query models, result schemas, relevance and signals APIs) so that the core search capabilities can be swapped or extended to other search engines in the future (e.g., alternate cloud search services or self\-hosted vector search) with minimal impact to client applications and user experience.
Your Skills \& Abilities (Required Qualifications)
- Bachelor’s degree in Computer Science or related field, or equivalent experience
- 5\+ years of web application development experience
- Strong frontend and backend development skills, including HTML, CSS, JavaScript , and Java, Python, and/or server\-side JavaScript
- Hands\-on experience designing and operating production workloads on GCP , including services such as Cloud Run, GKE, Cloud Functions, Pub/Sub, Cloud Storage, Cloud SQL/Spanner, and BigQuery
- Experience with AI\-powered search or recommendation systems , ideally Vertex AI Search or similar semantic/vector search platforms
- Experience with system design, testing, debugging, automation, and performance optimization
What Will Give You a Competitive Edge (Preferred Qualifications)
- Master’s degree in Computer Science or related field
- 7\+ years of experience building scalable, high\-traffic web applications and services
- Experience with ReactJS
- Experience with Adobe Experience Manager , Akamai , and/or Microsoft Azure
- Experience with Helm, Terraform, and ArgoCD
- Direct experience with Vertex AI Search , including schemas, indexing, ingestion pipelines, tuning, and evaluation
- Experience with LLM/embedding\-based retrieval , RAG , experimentation, and personalization.
\#LI\-CK1
*Gm does not provide immigration\-related sponsorship for this role. Do not apply for this role if you will need gm immigration sponsorship (e.g., h\-1b, tn, stem opt, etc.) Now or in the future.*
This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.
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About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well\-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources .
Non\-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non\-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role\-related assessment(s) and/or a pre\-employment screening prior to beginning employment. To learn more, visit How we Hire .
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1\-800\-865\-7580\. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,824 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At General Motors (GM), this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $213,800 based on 518 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
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.
General Motors (GM) AI Hiring
General Motors (GM) has 11 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Research Scientist, Data Engineer. Positions span Sunnyvale, CA, US, Austin, TX, US, Warren, MI, US. Compensation range: $261K - $347K.
Location Context
AI roles in Austin pay a median of $218,800 across 493 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
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: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
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 Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
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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