Principal AI Engineer 3

Principal AI Engineer

Ready to turn bold ideas into real-world impact?
At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory, our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment.

Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises.
Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook.

Job Description

Supply Chain & Manufacturing Forward Deployed Senior AI Engineer

Role Overview

We are seeking a high-caliber Supply Chain & Manufacturing Forward Deployed AI Engineer to 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, combining agile 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 using Python and 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 Assistants integrated 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 Solutions utilizing agentic workflows to parse contracts and market data.
• Predictive Decision Support Systems for complex Supply Chain Planning and Logistics network optimization.
• Multi-Agent Digital Workers automating 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: professional experience delivering software, advanced analytics, or digital transformation initiatives with hands-on experience building GenAI solutions.
• Domain Expertise: Experience working inside Supply Chain, Manufacturing, Operations, Logistics, or Industrial environments

.

• Core Software & AI Stack:
  • Production-grade Python and clean coding practices
  • Hands-on experience with modern AI/ML tooling: LLM APIs (GPT-4, Gemini, Claude), vector databases, and frameworks like LangChain, LangGraph, or LlamaIndex
  • Experience with cloud platforms (e.g., Azure OpenAI, Google Cloud/Vertex AI)
• Core Data Skills: Strong SQL skills with 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 enterprise ERP systems (SAP) and industrial systems (Poka, Weaver, MES)
• Experience with AI 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 &