Agentic AI Engineer

About the role

We are looking for an early-career Agentic AI Engineer to help build and evolve AI-powered systems that automate and improve supply chain workflows. In this role, you'll work alongside experienced engineers and data scientists to develop agentic AI / GenAI features , integrate knowledge-based retrieval (RAG) patterns, and contribute to testing and validation approaches for AI systems that can behave in non-deterministic ways. This is a strong opportunity for someone who is eager to grow in both software engineering and applied GenAI , and wants to work on real-world enterprise problems in supply chain and (optionally) life sciences.

Responsibilities

• Support the design and implementation of agentic AI / GenAI systems that assist in automating supply chain workflows.
• Build and maintain backend services and integrations using Python and/or Java .
• Contribute to multi-agent workflows , such as tool execution, routing, agent collaboration patterns, and task orchestration.
• Assist in creating testing and validation strategies for AI systems, including evaluation datasets, regression testing, and behavior monitoring.
• Help implement and improve knowledge base systems , including RAG pipelines , grounding strategies, and retrieval quality improvements.
• Contribute to experimentation with:
• lightweight fine-tuning approaches for small language models (SLMs)
• reinforcement-learning-inspired improvement loops for NLP/GenAI tasks (where applicable)
• Partner with product and domain teams to understand supply chain needs and translate them into working software.
• Participate in code reviews, documentation, and operational support to ensure high-quality production systems.
• Required Qualifications
• Master's/Bachelors degree in Data Science, Artificial Intelligence, Machine Learning, Computer Science, or a closely related discipline.
• 0-2 years of professional experience in software engineering, AI engineering, or ML engineering (internships and co-ops count) OR equivalent experience
• Strong programming skills in Python and/or Java , including writing production-quality code.
• Familiarity with cloud platforms such as AWS, GCP, or Azure (academic, personal, or internship experience is acceptable).
• Interest or exposure to Generative AI concepts, such as LLMs, agent workflows, tool calling, or multi-step reasoning.
• Understanding of core engineering fundamentals:
• APIs and services
• basic distributed systems concepts
• debugging and performance basics
• data structures & algorithms
• Ability to learn quickly, take feedback well, and collaborate effectively in a team environment.

Requirements

• Coursework, projects, or hands-on experience with agentic or multi-step AI systems , including non-deterministic behavior patterns.
• Exposure to designing knowledge base solutions , such as:
• Retrieval-Augmented Generation (RAG)
• embedding-based search
• hybrid search approaches
• reranking or relevance evaluation
• Experience or academic background in one of the following:
• fine-tuning small language models (SLMs)
• training or adapting NLP models
• Reinforcement learning concepts applied to language systems
• Exposure to event-driven or reactive systems
• Interest in supply chain domains (logistics, manufacturing, procurement, etc.).
• Knowledge of the life sciences supply chain is a plus, but not required.
• What Success Looks Like
• You can take a defined task (e.g., building a new RAG retriever, improving evaluation coverage, or implementing a new agent tool) and deliver a working solution with support from senior engineers.
• You write clean, testable code and steadily improve your ability to debug real-world production issues.
• You contribute to AI system reliability through experiments, evaluation improvements, and thoughtful engineering.
• Curious, motivated, and excited to build AI-driven products that ship to real users.
• Comfortable working with a mix of predictable engineering tasks and emerging AI workflows.
• Strong team player with a growth mindset and a willingness to learn.
• Please see the

Benefits

Additional Information

Company overview: TraceLink is the world's largest Agentic Business Network, enabling life sciences and healthcare companies to build and manage a scalable digital workforce of governed, no-code AI agents that execute and coordinate mission-critical supply chain operations alongside human teams. Powered by the Integrate-Once™ OPUS platform, TraceLink links more than 300,000 network participants, enabling multi-enterprise processes at global scale. Founded in 2009 with the simple mission of protecting patients, today Tracelink has 5 global offices, over 800 employees and more than 1700 customers in over 60 countries around the world. Our expanding product suite continues to protect patients and now also enhances multi-enterprise collaboration through innovative new applications such as MINT. Tracelink is recognized as an industry leader by Gartner and IDC, and for having a great company culture by Comparably.

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