Senior AI Engineer

Ford Motor Company

. Design, build, and maintain key components of Ford Credit's AI platform, including agent frameworks, platform services, developer tools, and deployment pipelines .

Posted 9/15/2026full-timeChennai • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining AI platforms, with a strong focus on cloud-native application development, governance, and compliance in regulated environments. Proficient in Python and Java, with a solid understanding of software engineering best practices and experience in developing internal tools and platforms.

Highest-signal resume keywords

Python ProgrammingJava ProgrammingGoogle Cloud PlatformAI GovernanceSoftware Engineering Best Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringCloud-Native Application DevelopmentLarge Language Models (LLMs)Agent FrameworksRetrieval SystemsCI/CD AutomationAPIs DevelopmentTesting and Code QualityObservabilityMaintainability

Soft Skills

Excellent Communication Skills

Tools & Technologies

Developer PlatformsSDKsInternal ToolingCommand-Line Tools

Certifications & Qualifications

Google Cloud Certifications

Industry Keywords

Financial ServicesRegulated IndustriesResponsible AI PracticesModel Risk ManagementData Governance

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformJavaPython

About the role

Key responsibilities & impact

Design, build, and maintain key components of Ford Credit's AI platform, including agent frameworks, platform services, developer tools, and deployment pipelines
Build and enhance enterprise knowledge and context capabilities such as retrieval services, knowledge systems, shared memory, and agent integration services
Partner with internal customers to deliver and support AI-powered solutions from concept through production
Embed governance, security, observability, and compliance controls into the platform to support responsible AI development
Create reusable templates, tools, documentation, and best practices that enable engineers to build and deploy AI solutions efficiently
Contribute to architectural decisions, code reviews, and engineering standards to promote high-quality software development
Collaborate with vendor and partner teams to ensure solutions align with Ford Credit standards and can be effectively operated and extended internally
Work closely with product management, architecture, security, site reliability engineering (SRE), and developer enablement teams to deliver platform capabilities
Build solutions that meet the requirements of a regulated financial services environment, including security, privacy, auditability, and data governance
Help establish best practices for combining deterministic business processes with AI-driven capabilities in a transparent and auditable manner

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field, or equivalent practical experience
5+ years of software engineering experience delivering production-grade applications and services
Strong programming skills in Python and/or Java
Experience developing cloud-native applications on Google Cloud Platform or comparable cloud environments
Hands-on experience building applications using large language models (LLMs), agent frameworks, retrieval systems, and tool integration
Experience building developer platforms, SDKs, APIs, internal tooling, or CI/CD automation
Strong understanding of software engineering best practices, including testing, code quality, observability, and maintainability
Excellent written and verbal communication skills
Preferred: Master's degree in a related technical field
Preferred: Experience designing and operating AI agents in production environments
Preferred: Experience with Retrieval-Augmented Generation (RAG), knowledge graphs, semantic search, or enterprise knowledge systems
Preferred: Experience in financial services or other regulated industries
Preferred: Experience with AI governance, model risk management, or responsible AI practices
Preferred: Experience building internal developer platforms, SDKs, or command-line tools
Preferred: Google Cloud certifications

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Ford Motor Company Website LinkedIn All Job Openings 10,000+ employees Founded 1903 📦 Logistics 💼 Consulting 📣 Marketing 💰 Post-IPO Debt on 2023-08 Logistics
Consulting
Marketing Ford Motor Company is a globally renowned automotive company based in the United States, established by Henry Ford. The company is committed to building a better world where every individual has the freedom to move and follow their dreams. Ford is dedicated to innovation, with a focus on services, experiences, and software alongside its traditional vehicle manufacturing. The company is actively involved in sustainability initiatives and aims to meet ambitious environmental targets. Ford values service, community impact, and strives to combine business success with social and environmental responsibility. With a rich history of over 121 years, Ford continues to adapt and lead in the evolving automotive landscape. Senior AI Engineer 🔥 1 hour ago 🏢🏡 Chennai – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer 👻 Ghost score 10% Cloud Google Cloud Platform Java Python Apply Now Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Design, build, and maintain key components of Ford Credit's AI platform, including agent frameworks, platform services, developer tools, and deployment pipelines
Build and enhance enterprise knowledge and context capabilities such as retrieval services, knowledge systems, shared memory, and agent integration services
Partner with internal customers to deliver and support AI-powered solutions from concept through production
Embed governance, security, observability, and compliance controls into the platform to support responsible AI development
Create reusable templates, tools, documentation, and best practices that enable engineers to build and deploy AI solutions efficiently
Contribute to architectural decisions, code reviews, and engineering standards to promote high-quality software development
Collaborate with vendor and partner teams to ensure solutions align with Ford Credit standards and can be effectively operated and extended internally
Work closely with product management, architecture, security, site reliability engineering (SRE), and developer enablement teams to deliver platform capabilities
Build solutions that meet the requirements of a regulated financial services environment, including security, privacy, auditability, and data governance
Help establish best practices for combining deterministic business processes with AI-driven capabilities in a transparent and auditable manner 🎯 Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field, or equivalent practical experience
5+ years of software engineering experience delivering production-grade applications and services
Strong programming skills in Python and/or Java
Experience developing cloud-native applications on Google Cloud Platform or comparable cloud environments
Hands-on experience building applications using large language models (LLMs), agent frameworks, retrieval systems, and tool integration
Experience building developer platforms, SDKs, APIs, internal tooling, or CI/CD automation
Strong understanding of software engineering best practices, including testing, code quality, observability, and maintainability
Excellent written and verbal communication skills
Preferred: Master's degree in a related technical field
Preferred: Experience designing and operating AI agents in production environments
Preferred: Experience with Retrieval-Augmented Generation (RAG), knowledge graphs, semantic search, or enterprise knowledge systems
Preferred: Experience in financial services or other regulated industries
Preferred: Experience with AI governance, model risk management, or responsible AI practices
Preferred: Experience building internal developer platforms, SDKs, or command-line tools
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