AI Implementation Engineer

MAGNETO & DIESEL INJECTOR SERVICE INC•Humble, TX

12h

About The Position

For over 80 years, M&D has been a leader in remanufacturing innovation, adapting to technological advancements and evolving customer needs. They have expanded beyond their remanufacturing origins to form close partnerships with leading OEMs and manufacturers such as Bosch, Garrett, Federal Mogul, Cummins, and others. These collaborations have enhanced their remanufacturing capabilities and broadened their product offerings to include new and remanufactured parts like fuel injectors, fuel pumps, diesel engine cylinder heads, blocks, crankshafts, connecting rods, turbos, overhaul kits, filtration, and aftertreatment parts. With strong remanufacturing roots, 41+ branch locations, a nationwide sales team, and key OEM partnerships, M&D possesses unique expertise in diesel engine failure analysis and parts. The AI Implementation Engineer is responsible for transforming AI-powered prototypes into production-ready, scalable, and maintainable systems for deployment across M&D. This role focuses on hardening, deploying, and scaling AI applications to deliver measurable business value in areas such as pricing, sales, ecommerce, and marketing.

Requirements

4+ years of experience in software engineering, data engineering, or related field
Strong Python development skills with experience building structured, production-quality applications
Experience with web frameworks such as FastAPI, Flask, or Streamlit
Experience with data processing tools and libraries (pandas, requests, web scraping frameworks)
Hands-on experience deploying and managing applications in AWS environments (EC2, Linux systems)
Experience building and consuming APIs and integrating with third-party systems
Familiarity with LLM-based application development (OpenAI, Claude, or similar APIs)
Understanding of prompt engineering, structured outputs, and AI application reliability considerations
Experience designing and building data pipelines and working with SQL databases
Ability to read, understand, and refactor existing prototype code into production-ready systems
Strong problem-solving skills and ability to work independently in an unstructured environment
Strong documentation and communication skills
Successful completion of pre-employment background and drug screening
Fosters good coworker citizenship and contributes to a positive work environment

Responsibilities

Refactor and productionize existing AI prototypes built in Python into reliable, scalable applications
Design and implement production-ready architectures with proper structure, logging, error handling, and testing
Deploy and manage AI applications in cloud environments (AWS), including EC2-based systems
Build and maintain APIs and services to support internal tools such as pricing intelligence systems, parts lookup tools, and analytics platforms
Develop and manage data pipelines (scrape → clean → normalize → store → serve) across multiple data sources
Integrate AI systems with internal platforms (e.g., ERP, ecommerce systems) and third-party APIs
Implement and optimize web scraping solutions at scale, including rate limiting, proxy management, and data normalization
Build and maintain AI-powered features using LLM APIs (e.g., OpenAI, Claude), including prompt engineering and structured outputs
Implement retrieval-augmented generation (RAG) and other AI patterns for business applications
Ensure security, reliability, and maintainability of deployed systems (IAM, environment variables, access control)
Document systems, workflows, and code to support long-term scalability and team adoption
Collaborate with business stakeholders to translate functional needs into technical solutions
Continuously improve system performance, scalability, and usability
Perform other duties as assigned by supervisor