Supply Chain and Manufacturing AI Product Engineer

**Job Description:** We are seeking an energetic and technically sharp Junior Forward Deployed AI Engineer to support the rapid prototyping, discovery, and proof-of-concept (PoC) delivery of AI-powered solutions across our global Supply Chain and Manufacturing functions. This is a dynamic, fast-paced role where you will work alongside senior engineers to bridge the gap between AI development and real-world shop floor operations. You will spend time embedding directly with frontline teams—visiting manufacturing sites and warehouses—to understand their day-to-day challenges, and then turn those insights into working, AI-enabled software prototypes. The ideal candidate is a proactive builder who is comfortable working with Python, eager to learn cutting-edge GenAI frameworks, and excited about collaborating directly with operational business teams. **Key Responsibilities** **Frontline Engagement & Discovery** * Frontline Shadowing: Participate in site visits and shadow frontline teams (Logistics, Manufacturing, Procurement) to understand operational bottlenecks first-hand. * Requirements Translation: Support senior engineers in translating user feedback and "messy" real-world problems into structured user stories, functional specs, and process flows. * Active Scrum Participant: Maintain and update the team's agile backlog, actively participate in daily standups, and assist in coordinating sprint planning. **Rapid AI Prototyping & Development** * Hands-on Coding: Write clean, documented, and functional Python code to build, refine, and test AI-enabled prototypes. * Support RAG & Agentic Systems: Work under the guidance of senior engineers to construct and tune Retrieval-Augmented Generation (RAG) pipelines, semantic search indices, and multi-agent system workflows. * Iterate & Refine: Actively modify prototypes based on immediate feedback from factory floor workers and warehouse operators. * Adopt Best Practices: Learn and apply enterprise software development standards to ensure prototype code is structured for eventual production handoff. **Systems Integration & Data Engineering** * API Configuration: Assist in building and configuring APIs to connect AI applications to shop floor platforms (e.g., Poka, Weaver) and document repositories. * Data Wrangling: Clean, structure, and prepare unstructured documents, telemetry feeds, and SQL database exports for ingestion into AI systems. **Typical Use Cases** * Standard Operating Procedure (SOP) Assistants designed to help operators look up technical guidelines hands-free. * Manufacturing Knowledge Assistants that index equipment manuals to speed up machine maintenance. * Procurement Intelligence Tools that extract and summarize key terms from supplier contracts. * Workflow Automation Tools to help administrative logistics teams auto-generate shift handover reports. **Career Growth:** This role will be an excellent fit for someone who: * Enjoys solving varied, real-world problems. * Likes interacting with customers and understanding business needs. * Wants to work on cutting-edge AI applications rather than purely research. * Thrives in fast-paced environments where you own projects from design to deployment. **Required Qualifications** * **Education:** Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related technical discipline. * **Experience:** 1–3 years of professional experience in software engineering, data engineering, or digital technology delivery. * **Coding Foundation:** Robust baseline experience writing Python (Pandas, NumPy, requests) and a strong understanding of software engineering fundamentals (OOP, REST APIs). * **AI Familiarity:** Hands-on experience (which can include academic projects, bootcamps, or personal portfolios) using LLM APIs (OpenAI, Gemini) and basic RAG architectures. * **Data Skills:** Proficient with SQL and comfortable querying relational databases. * **Soft Skills & Mobility:** Excellent communication skills with the confidence to converse with factory operators. Highly curious, eager to learn, and willing to travel occasionally to manufacturing facilities. **Preferred Qualifications** * Basic experience with AI frameworks such as LangChain, LlamaIndex, or LangGraph. * Familiarity with cloud platforms (e.g., Google Cloud Platform/Vertex AI, Microsoft Azure). * Familiarity with version control (Git/GitHub) and containerization (Docker). * Academic background or brief exposure to Supply Chain, Manufacturing, or Logistics environments. **Success Measures** * **Technical Growth:** Rapid ramp-up on advanced enterprise AI architectures and frameworks (e.g., LangGraph, Vertex AI). * **Prototype Delivery Velocity:** Successfully completing assigned development tasks within the sprint cycle. * **User-Centric Execution**: Translating frontline operator feedback into functional code modifications. #TBdigital