Director Applied Artificial Intelligence

About TraceLink and OPUS

TraceLink is building an Agentic Supply Chain Operating System. Powered by the OPUS Platform, it continuously unifies the information required to perform operational work across multiple enterprises. It is built from the bottom up, starting with the companies that make up each customer's supply network.

The operating system rests on four foundations:

• Supply Network Digital Twin. A live representation of the partners, products, locations, and business transactions across the supply network, built on the Integrate-Once™ Agentic Business Network.
• Multienterprise Business Processes. Orders, shipments, inventory, quality, and compliance work that forms, adapts, and completes across enterprise boundaries rather than inside one system.
• Agentic Supply Chain Intelligence. Control Towers apply knowledge, analytics, and supply chain meta-reasoning to operational context, so people understand what is happening and what should happen next.
• Governed Agents. OPUS Agents are created as governed users, assigned to human managers, and controlled through OPUS Agent Profiles, roles, permissions, objectives, Tasks, Decisions, and Rules.

At the center of these foundations is the OPUS Brain: the cognitive layer that lets OPUS Agents perceive what is happening across the supply network, reason about it, plan, decide, coordinate with other agents and people, and learn from outcomes. All of this happens within the governance boundaries each agent is assigned. The OPUS Brain is what turns a governed identity into a capable digital teammate. Agents are users. Each has an identity, an assigned role, and scoped permissions, and every action it takes is recorded. The OPUS Brain makes sure every thought that leads to an action can be traced and explained as well.

Role overview

The Director of Applied Artificial Intelligence owns the OPUS Brain. You will lead the team that designs, builds, evaluates, and operates the cognitive functions that drive agentic orchestration for every OPUS Agent. Those functions include context assembly, memory, reasoning, planning, decisioning, multi-agent coordination, escalation, and learning.

This is a hands-on leadership role at the intersection of AI research, cognitive architecture, and supply chain operations. You will decide how large language models, reasoning and planning systems, knowledge graphs, and classical machine learning combine into a single, reusable cognitive architecture. That architecture must serve many agent roles across multienterprise processes. You will also make sure the OPUS Brain enforces governance by design, so that every agent reasons and acts only within its scoped permissions, rules, and objectives, and stays accountable to its human manager.

Reporting to the Vice President of Platform Architecture, you will lead a team of applied AI, ML, and agent-systems engineers. You will partner closely with Product Management, Platform Engineering, Solutions, Security, Compliance, and Legal.

Key responsibilities

OPUS Brain strategy and architecture

• Define and own the architecture and multi-year roadmap for the OPUS Brain as the shared cognitive foundation for all OPUS Agents and Agentic Control Towers.
• Establish a modular set of cognitive functions that agent roles can compose and configure rather than rebuild: perception, memory, reasoning, planning, decisioning, orchestration, and reflection.
• Evolve the OPUS Brain's capabilities so agents can progress from analysis and recommendation to governed autonomous execution.
• Make build-versus-buy and model-selection decisions across foundation models, reasoning models, retrieval systems, and classical ML components.

Governance embedded in cognition

• Ensure the OPUS Brain enforces OPUS Agent Profiles, roles, permissions, objectives, Tasks, Decisions, and Rules at every step of reasoning and action, not only at the point of execution.
• Make agent reasoning traceable: every Decision should be linked to the context, knowledge, and Rules that produced it and captured in the audit log.
• Define human-in-the-loop patterns inside the cognitive architecture, including confidence thresholds, escalation triggers, and approval checkpoints.
• Protect against failure modes such as hallucination, goal drift, permission overreach, and unsafe tool use through guardrails and runtime controls.

Evaluation and AI operations

• Build rigorous evaluation frameworks for each cognitive function and for end-to-end orchestration, covering reasoning quality, plan correctness, decision accuracy, adherence to Rules and permissions, reliability, cost, and latency.
• Create simulation and scenario-testing environments, grounded in the Digital Twin, where agents can be tested against realistic supply chain disruptions before deployment.
• Own observability of agent reasoning, drift detection, incident response, and continuous improvement.

Responsible AI and compliance

• Partner with Security, Compliance, and Legal to meet regulatory requirements in highly regulated industries such as life sciences.
• Define responsible AI standards for transparency, explainability, data privacy, and auditability of agent reasoning and decisions.
• Make the OPUS Brain's governance a product feature customers can inspect and trust, including explanations human managers can understand.

Leadership and collaboration

• Hire, develop, and lead a high-performing team spanning applied AI research, ML engineering, and agent systems; set a culture of shipping, measurement, and accountability.
• Work with Product and Platform Engineering so agent teams can configure OPUS Brain capabilities for new operational roles quickly and safely.
• Work with Customer Success to bring agents into customer operations and turn feedback from human managers into improvements in the cognitive architecture.
• Represent TraceLink's work on agentic cognition with customers, partners, analysts, and industry forums.

Qualifications

Required

• 10+ years of experience, including 4+ years in machine learning, AI, or data science and 3+ years leading applied AI or ML engineering teams.
• A track record of shipping LLM-based or agentic systems into production for enterprise customers.
• Deep hands-on expertise in agent architectures, including LLM reasoning, planning and task decomposition, tool use, agent memory, retrieval-augmented generation, and multi-agent orchestration.
• Experience designing evaluation methods for agent reasoning, planning, and decision quality, not only model outputs.
• Experience building AI systems with identity, role-based access, permissions, guardrails, and full audit trails.
• Strong software engineering foundations, including cloud platforms (AWS, Azure, or GCP), APIs, event-driven architectures, and distributed systems.
• Ability to explain complex AI concepts, including how agents reason and decide, to executives, customers, and non-technical operators.
• Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience required. PhD a plus.

Desired

• Background in cognitive architectures, automated planning, symbolic or neuro-symbolic reasoning, or decision theory.
• Experience with knowledge graphs, digital twins, optimization, or simulation environments for agent testing.
• Domain experience in supply chain, logistics, manufacturing, or life sciences operations.
• Familiarity with multienterprise networks, B2B integration, EDI, or supply chain control towers.
• Experience in regulated environments such as FDA, EU GMP, or DSCSA compliance.
• Published research, patents, or open-source contributions in agentic systems, reasoning, or planning.

Why join TraceLink

You will build the mind behind a new category: an operating system where people and governed AI agents work side by side across entire supply networks. The OPUS Brain decides how digital teammates understand, reason, and act on the partners, products, and transactions that keep critical goods, including medicines, moving safely. You will build agents that are capable because they think well, are trusted and they are accountable by design.

US Pay Range 257900 - 347100 USD