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About This Role
Career Area:
Technology, Digital and DataJob Description:
Your Work Shapes the World at Caterpillar Inc.
When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
*Cat Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry\-leading digital solutions for customers and dealers. With over 1\.5 million connected assets worldwide, our teams use data, technology, advanced analytics, telematics, and AI capabilities to help customers build a better, more sustainable world.*
### Job Summary:
As a Senior Software Engineer on the Salesforce AI \& Engineering team, you will be responsible for designing, developing, implementing, testing, and maintaining Salesforce and AI\-powered solutions that support Caterpillar's digital platforms, customer experiences, dealer ecosystems, and enterprise business processes. You will lead the adoption and integration of Salesforce AI technologies, including Agentforce, Einstein AI, Generative AI capabilities, intelligent automation, and enterprise AI solutions to drive innovation, operational efficiency, and business value.
This position requires knowledge of Salesforce platform technologies, Agentforce, Einstein AI, cloud\-based application development, integrations, APIs, automation frameworks, data modeling, security, Large Language Models (LLMs), AI\-assisted development practices, and enterprise software engineering principles to deliver scalable, secure, and intelligent solutions aligned with business and customer requirements.
This position qualifies as a specialty occupation because it requires at minimum a Bachelor’s degree or higher in Computer Science, Software Engineering, Information Systems, or a closely related technical field, or equivalent working experience.
### What You Will Do:
- Design, develop, implement, test, and maintain Salesforce solutions using Agile/Scrum methodologies.
- Design, develop, implement, test, deploy, and maintain scalable Salesforce and AI\-powered solutions using Agile/Scrum methodologies and modern software engineering practices.
- Configure, and customize solutions across Salesforce platforms, including Sales Cloud, Marketing Cloud, Experience Cloud, Data Cloud, Agentforce, and other enterprise capabilities.
- Develop enterprise\-grade applications and integrations using Apex, Lightning Web Components (LWC), Visualforce, JavaScript, SOQL/SOSL, Salesforce APIs, and cloud\-native development patterns.
- Design and implement declarative solutions leveraging OmniStudio, Flows, validation rules, custom objects, approval processes, record\-triggered automation to deliver scalable business capabilities.
- Develop and support integrations between Salesforce and enterprise systems using REST, SOAP, Platform Events, middleware platforms, event\-driven architectures, and modern integration frameworks.
- Leverage AI\-assisted development tools such as GitHub Copilot, Claude Code, and similar technologies to improve developer productivity, code quality, testing efficiency, and delivery speed.
- Design, build, and integrate AI\-powered capabilities including Agentforce agents, Einstein AI solutions, intelligent assistants, conversational experiences, predictive insights, and workflow automation across the Salesforce ecosystem.
- Apply Generative AI, Agentic AI technologies to solve complex business and engineering challenges, including process automation, recommendations, knowledge retrieval, decision support, customer engagement, and operational optimization.
- Evaluate, prototype, and implement emerging AI technologies, frameworks, and best practices to improve engineering efficiency, solution quality, and business outcomes.
- Champion AI\-enabled software engineering practices by establishing reusable frameworks, governance standards, development patterns, and responsible AI principles that improve scalability, security, maintainability, and operational excellence.
- Provide technical leadership and mentorship for engineering teams on Salesforce architecture, Agentforce, Einstein AI, AI\-assisted development, and modern software delivery practices.
- Collaborate with business, product, architecture, data, and platform teams to define and deliver innovative AI\-driven solutions that enhance customer experiences, employee productivity, and enterprise capabilities.
### Considerations For Top Candidates:
- Bachelor’s degree or higher in Computer Science, Software Engineering, Information Systems, or a closely related technical field, or equivalent working experience.
- 5\+ years or more of software development experience and solid working knowledge of OOP principles.
- 3\+ years or more of experience in designing and developing software applications in Python.
- Experience working with Git version control on medium to large teams.
- Exceptional communication skills with experience working on a cross functional team.
- Deploying software using CI/CD tools such as Jenkins, Github Actions, Azure Devops etc.
- Experience with AWS components such as Lambda, Event Bridge, CloudWatch, CloudFormation, Dynamo, S3, IAM and RDS.
- Hands‑on experience with GenAI developer tools: Practical usage of tools such as Github Copilot, Claude code, or similar AI coding assistants to improve developer productivity, code quality, and delivery speed.
- Experience designing, developing, or integrating Generative AI solutions using Large Language Models (LLMs), prompt engineering, Retrieval\-Augmented Generation (RAG), vector databases, and AI orchestration frameworks.
- Ability to learn and adapt in a rapidly evolving space: Demonstrates curiosity and continuous learning as GenAI tools, frameworks, and best practices evolve quickly.
- Applied knowledge of GenAI tools in real use cases: Proven experience applying GenAI to solve real business or engineering problems (e.g., data processing, automation, assistants, recommendations, or decision support).
- Knowledge of Salesforce Marketing Cloud \& Salesforce Sales Cloud.
- Knowledge of Apex, Lightning Web Components, Salesforce Flow, Salesforce Data Modeling, AMP scripting.
- Knowledge of Salesforce AI technologies, including Einstein AI, Agentforce, Prompt Builder, and Data Cloud.
- Knowledge on integrating Salesforce with enterprise applications, APIs, middleware, identity providers, and external systems.
- Understanding Salesforce governance, platform limits, release management, and scalable solution design.
What You Will Get:
Working with a Fortune 100 leader, you can build your career on a global scale and take advantage of development opportunities with emerging technologies. We’ve created an inclusive environment for you to explore your passions, make an impact and do the work that really matters. Join Us.
Additional Information:
This position will be based out of either our Chicago, IL or Peoria, IL offices.
\#LI
\#BI (used to post on Built In Chicago)
About Caterpillar
Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off\-highway diesel and natural gas engines, industrial gas turbines and diesel\-electric locomotives. For nearly 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced\-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed.
Summary Pay Range:
$112,710\.00 \- $183,140\.00
Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job\-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar.
Benefits:
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
- Medical, dental, and vision benefits\*
- Paid time off plan (Vacation, Holidays, Volunteer, etc.)\*
- 401(k) savings plans\*
- Health Savings Account (HSA)\*
- Flexible Spending Accounts (FSAs)\*
- Health Lifestyle Programs\*
- Employee Assistance Program\*
- Voluntary Benefits and Employee Discounts\*
- Career Development\*
- Incentive bonus\*
- Disability benefits
- Life Insurance
- Parental leave
- Adoption benefits
- Tuition Reimbursement
- These benefits also apply to part\-time employees
Visa Sponsorship is not available for this position.Posting Dates:
July 31, 2026 \- August 16, 2026
Any offer of employment is conditioned upon the successful completion of a drug screen.
Caterpillar is an Equal Opportunity Employer, Including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.
Not ready to apply? Join our Talent Community.
Salary Context
This $112K-$183K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Caterpillar, 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 $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($147K) sits 32% below the category median. Disclosed range: $112K to $183K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Caterpillar AI Hiring
Caterpillar has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Irving, TX, US, Peoria, IL, US. Compensation range: $183K - $258K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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