Supply Chain and Manufacturing AI Senior Product Engineer

Mars; Warszawa; Hybrid; PLN 180,000 - 300,000; Full time

Job summary

Mars, Incorporated and its Affiliates is seeking a high-caliber Supply Chain & Manufacturing Forward Deployed AI Engineer to lead rapid prototyping and PoC delivery across global functions. You will embed with frontline operations to understand bottlenecks, write robust Python code, and design scalable AI architectures that integrate with SAP ERP and shop-floor systems.

The role blends agile software delivery, hands-on AI product engineering, and cross-functional collaboration, requiring strong

Qualifications

• Bachelor's degree in CS/engineering or quantitative field.
• 5+ years delivering software/analytics with 2+ years GenAI experience.
• Experience in Supply Chain, Manufacturing, Logistics, or Industrial environments.
• Proficiency in Python and clean coding practices.
• Experience with ML tooling and cloud platforms.
• Strong SQL skills.
• Excellent communication and facilitation abilities.

Responsibilities

• On-site discovery with frontline teams to map bottlenecks.
• Translate problems into user stories and data models.
• Act as Scrum Master for prototyping work and backlog management.
• Design, write, and deploy working prototypes using Python and cloud tech.
• Construct Retrieval-Augmented Generation pipelines and AI architectures.
• Integrate AI systems with SAP and shop-floor platforms.
• Ingest and structure real-world data from diverse sources.
• Ensure secure, scalable, and well-documented solutions.

Skills

Python

LLM APIs

Vector databases

LangChain/LangGraph

Cloud platforms

SQL

Communication

Education

Bachelor's degree in Computer Science/Engineering/Information Systems or quantitative field

Tools

SAP

Poka

Weaver

MES

Git

Docker

CI/CD

Job description

Job Description:

We are seeking a high-caliberSupply Chain & Manufacturing Forward Deployed AI Engineerto lead rapid prototyping, discovery, and proof-of-concept (PoC) delivery.In this role, the incumbent will actively de-risk the design, development, integration, testing, and delivery of production-ready, AI-powered solutions across our global Supply Chain and Manufacturing functions.

This is a unique, highly impactful hybrid role, combiningagile software delivery, frontline business engagement, hands‑on AI product engineering, and modern AI/ML systems architecture. The ideal candidate will embed directly with frontline operations at the point of solution consumption to intimately understand operational bottlenecks, translate them into structured technical requirements, and write the critical lines of code that drive tangible business value.

The ideal candidate is equally comfortable facilitating workshops on the manufacturing floor, managing rapid agile delivery cycles, designing technical architecture, and writing robust, clean Python code.

Key Responsibilities

Frontline Engagement & Discovery

• On-Site Discovery:Partner directly with frontline Supply Chain, Manufacturing, Logistics, Procurement, and Planning teams to intimately map out operational bottlenecks

• Translate Ambiguity:Facilitate discovery workshops and process reviews to translate messy business problems into clean user stories, functional specs, and technical data models

• Own the Agile Lifecycle:Act as the Scrum Master for your prototyping work, managing backlog prioritization, rapid feedback iterations, risks, dependencies, and assumptions.

Rapid AI Prototyping & Development

• Code & Deploy:Design, write, and deploy robust working prototypes usingPythonand modern cloud technologies

• Build Advanced AI Architectures:Construct enterprise-grade Retrieval-Augmented Generation (RAG) pipelines, semantic search engines, and multi-agent system workflows

• Design for Scale:Focus on engineering prototypes that are "designed for scale" to ensure seamless code transition and handoff to core engineering teams

• Reusable Tooling:Build reusable AI components, libraries, and accelerators to streamline future supply chain use cases

Systems Integration & Data Engineering

• Platform Connections:Design and build API integrations connecting AI applications directly to shop-floor platforms (e.g.,Poka, Weaver, MES)

• Enterprise Infrastructure:Integrate AI systems with core enterprise platforms (SAP ERP), document repositories, and knowledge bases

• Data Pipelines:Ingest, clean, structure, and connect messy, real-world data from databases, telemetry streams, and unstructured files

• Cross-Functional Security:Partner with Security, Data, and Architecture teams to ensure robust, compliant, and secure integration patterns.

Typical Use Cases

• Intelligent Manufacturing Knowledge Assistantsintegrated with platforms like Poka and Weaver to assist line operators.

• AI-Powered Shopfloor Voice Assistants& hands-free Standard Operating Procedure (SOP) guidance.

• Supplier & Procurement Intelligence Solutionsutilizing agentic workflows to parse contracts and market data.

• Predictive Decision Support Systemsfor complex Supply Chain Planning and Logistics network optimization.

• Multi-Agent Digital Workersautomating complex document analysis, compliance checks, and operational reporting.

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, Engineering, Information Systems, Supply Chain, Manufacturing, or a highly quantitative field.

• Experience:5+ yearsof professional experience delivering software, advanced analytics, or digital transformation initiativeswith at least2+ yearsof hands-on experience building GenAI solutions.

• Domain Expertise:Experience working insideSupply Chain, Manufacturing, Operations, Logistics, or Industrial environments

• Core Software & AI Stack:

  • Production-gradePythonand clean coding practices

  • Hands-on experience with modern AI/ML tooling: LLM APIs (GPT-4, Gemini, Claude), vector databases, and frameworks likeLangChain, LangGraph, or LlamaIndex

  • Experience with cloud platforms (e.g.,Azure OpenAI, Google Cloud/Vertex AI)

• Core Data Skills:StrongSQL skillswith the ability to query, manipulate, and validate complex enterprise datasets

• Delivery & Soft Skills:Superb communication and facilitation skills.Comfortable walking a manufacturing floor, gaining trust from operators, and presenting technical architectures to executive leadership

Preferred Qualifications

• Hands-on experience with enterpriseERP systems (SAP)and industrial systems (Poka, Weaver, MES)

• Experience withAI Evaluation and Guardrail frameworks(e.g., Ragas, TruLens, Phoenix) to systematically evaluate model outputs

• Strong engineering discipline: familiarity with version control (Git/GitHub), containerization (Docker), and basic CI/CD workflows

• Experience with data pipelines/analytics platforms (e.g.,Snowflake, Databricks, Apache Spark, Airflow)

Success Measures

• Velocity & Outcome Ownership:Swiftly converting ambiguous user pain points into functional, de-risked AI prototypes

• High Adoption & Smooth Handoff:High transition rate of validated prototype code to core engineering teams for full-scale production

• Measurable Business Value:Delivering clear, quantifiable improvements to operational metrics (e.g., reduction in line downtime, faster SOP lookups, improved logistics query speed).