Lead Software Engineer (Autonomy Services)

Caterpillar Inc.•Irving, TX

2d•$128,470 - $208,770•Onsite

About The Position

The Lead Software Engineer provides technical leadership for critical platform investments that enable a broad portfolio of digital applications. This role is an opportunity to shape architecture, influence engineering direction, and accelerate delivery of secure, scalable services on AWS while mentoring other engineers. You will drive high-impact technical decisions, establish strong development practices including secure AI-assisted and agentic engineering workflows, and help the team build platform capabilities that create meaningful business outcomes at scale.

Requirements

Software Product Design/Architecture: Knowledge of software product design; ability to convert market requirements into software product design and strategic technical direction.
Software Product Technical Knowledge: Knowledge of technical aspects of software products; ability to design, configure, and integrate technical aspects of software products.
Software Integration Engineering: Knowledge of software integration processes and functions; ability to design, develop, and maintain interfaces and linkage to alternative platforms and software packages.
Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment.
Effective Communications: Understanding of effective communication concepts, tools, and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through appropriate communication behaviors.
Strong backend engineering capability with Java 17+ and Spring Boot to design and deliver RESTful APIs using microservices principles.
Proven ability to build secure, scalable platform services in a cloud environment such as AWS or Azure.
Experience deploying backend services in cloud-native environments.
Knowledge of AI-assisted and agentic software development workflows
Ability to review, validate, test, and refine AI-generated code and pull requests for correctness, maintainability, performance, security, and alignment with established engineering standards.
Knowledge of responsible AI usage and secure coding practices in AI-assisted development

Nice To Haves

Experience building production AI agents using Python
Experience with agent orchestration frameworks such as LangChain or LangGraph
Experience integration LLMs with external tools, APIs, databases, and retrieval systems
Experience designing evals, guardrails, and monitoring for agent reliability
Multi-agent workflow design and memory/context management
Prompt optimization, latency reduction, and cost control
MLOps or model deployment experience

Responsibilities

Lead design, development, testing, and deployment of backend RESTful API services using Java, Spring Boot, and microservices architecture.
Act as a technical leader for development and support groups by providing architectural guidance, engineering direction, and hands-on problem solving.
Own complex application and platform challenges from discovery through delivery, balancing speed, quality, security, and long-term maintainability.
Set and reinforce high standards for software quality through design reviews, code reviews, testing strategy, operational readiness, and best practices.
Mentor and develop engineers across the team, helping raise technical capability and consistency in execution.
Lead adoption of AI-assisted and agentic software development practices across the team by defining effective repository guidance, approval workflows, validation standards, and secure development guardrails that improve delivery speed while preserving quality, architecture integrity, and human accountability.
Influence full-stack architecture patterns across UI, API, and service layers while maintaining primary ownership of scalable backend microservice and platform architecture.
Drive delivery of business-value features with cross-functional Agile teams while aligning implementation choices to product, platform, and enterprise needs.
Guide the team in building structured application and interface code, technical documentation, and reusable patterns that improve scalability and developer productivity.