Full Stack Software Engineer - AI Applications

$85K - $232K Palo Alto, CA, US Mid Level AI Software Engineer

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Skills & Technologies

EmbeddingsGcpJavascriptPythonRagTypescript

About This Role

AI job market dashboard showing open roles by category

Job ID

67240

Category

Enterprise Technology

Location

Palo Alto, California

Work Type

On\-site

Who You Are

---------------

An agent orchestrator, not a typist. You don't want to be a faster keyboard. You want to be a manager of agents — handing off the heavy lifting, reviewing the output, and keeping your hands on the architecture. The IDE is a cockpit for orchestration, not a text editor.

Productively lazy. Your dream workflow: describe the requirement, let the agent build it, verify, ship, next. You automate anything a human shouldn't be doing twice. Your biggest bottleneck should be deciding *what* to build — while AI executes the *how*.

Fundamentals first. Data structures, algorithms, distributed systems, networking — you understand the machine, not just the library that wraps it. When a framework breaks, you fix it. When AI gives you the wrong answer, you catch it. Orchestrating agents only works if you can tell good output from garbage.

First\-principles thinker with vision. You break problems to their core, question the assumptions, and rebuild. A software engineer's job is to architect solutions, not wrestle with syntax. You don't copy an architecture because "that's how it's done" — you ask why and decide if there's a better way.

High agency. You don't wait for perfect specs or permission. You find a path, propose it, and move. Large organizations have walls; you figure out which ones to go through, around, or remove — and you do it constructively.

Bias for action. Requirements will be messy and priorities will shift. You ship v1, learn, and iterate instead of living in design review.

What You'll Do

------------------

  • Orchestrate agents to build. Use AI as your default way of working — agents do the heavy lifting, you direct, review, and harden. You set the bar for how the team builds with AI.
  • Build the AI use cases. Design and ship AI\-powered applications and agents — RAG pipelines, LLM integrations, agentic workflows. Understand what's happening under the hood and make it work in production, at scale.
  • Ship cloud\-native systems on GCP. Design, deploy, operate. You own the architecture, the infrastructure\-as\-code, and the CI/CD pipeline. No throwing code over the wall.
  • Connect systems that don't want to be connected. Build the integration layer across enterprise SaaS platforms. Expect messy APIs, legacy constraints, and creative problem\-solving.
  • Automate what shouldn't be manual. If a human repeats it, you write the code — or point an agent at it — to stop it.
  • Make other engineers faster. Build the tools, agent workflows, and guardrails that remove friction. Developer productivity is a multiplier.

What You Bring

------------------

  • Python — deep. You write production systems, not just scripts.
  • JavaScript / TypeScript — React, Node.js, or equivalent. A real frontend and a real API. Front\-end strength is a big plus.
  • AI engineering — LLMs, embeddings, vector stores, RAG. Comfortable building agents and evaluation pipelines. Bonus for fine\-tuning or eval work.
  • AI\-assisted development — fluent with modern AI coding tools and agent workflows, and clear\-eyed about where they help and where they don't.
  • GCP — Cloud Run, Cloud Functions, GKE, BigQuery, Cloud Storage. Deployed and operated, not just tutorials.
  • Databases — relational and NoSQL. You know when to use what, and why.
  • APIs \& microservices — designed and built RESTful services at scale.
  • Git, IaC \& CI/CD — Terraform, Cloud Build, or equivalent. Reproducible, version\-controlled infrastructure and disciplined code review.

Requirements

----------------

  • BS in Computer Science, Electrical Engineering, or a related field. MS is a plus, not a substitute for shipping software.
  • 2\+ years building and deploying full\-stack applications in production.
  • 2\+ years on cloud\-native platforms (GCP preferred).
  • Demonstrable experience building AI agents or applications — show us what you've built, not what you've read.

Why This Role

-----------------

Ford is a 120\-year\-old company moving fast on AI, and that's the real challenge: building world\-class AI applications inside a large enterprise with real constraints — security, compliance, legacy systems. The engineers who thrive here treat those constraints as problems to solve, not reasons to stop. If you want a place where everything is already figured out, this isn't it. If you're a 10x thinker who wants to build something that matters — and have the grit to push through the hard parts — let's talk.

*

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

  • Immediate medical, dental, vision and prescription drug coverage
  • Flexible family care days, paid parental leave, new parent ramp\-up programs, subsidized back\-up child care and more
  • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
  • Vehicle discount program for employees and family members and management leases
  • Tuition assistance
  • Established and active employee resource groups
  • Paid time off for individual and team community service
  • A generous schedule of paid holidays, including the week between Christmas and New Year's Day
  • Paid time off and the option to purchase additional vacation time

For a detailed look at our benefits, click here: https://fordcareers.co/GSR

This position ranges from salary grade 6\-8 and ranges from $85,400\-$232,700\.

Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1\-888\-336\-0660\.

\#LI\-Onsite \#LI\-DS2

Salary Context

This $85K-$232K range is below the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).

Role Details

Title Full Stack Software Engineer - AI Applications
Location Palo Alto, CA, US
Category AI Software Engineer
Experience Mid Level
Salary $85K - $232K
Remote No

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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Ford Motor Company, 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

Embeddings (6% of roles) Gcp (17% of roles) Javascript (6% of roles) Python (51% of roles) Rag (23% of roles) Typescript (7% of roles)

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 $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($159K) sits 27% below the category median. Disclosed range: $85K to $232K.

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.

Ford Motor Company AI Hiring

Ford Motor Company has 7 open AI roles right now. They're hiring across Data Scientist, AI Product Manager, AI Software Engineer, AI/ML Engineer. Positions span Dearborn, MI, US, Palo Alto, CA, US. Compensation range: $192K - $250K.

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 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 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 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 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

Based on 424 roles with disclosed compensation, the median salary for AI Software Engineer positions is $219,250. Actual compensation varies by seniority, location, and company stage.
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.
About 14% of the 3,708 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Ford Motor Company is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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