Lead AI Engineer

Toshiba Global Commerce Solutions is seeking an AI Architect who is an expert in designing and delivering complex systems, acting as a go-to technical authority in the Agentic AI organization. The AI Architect will typically lead multiple projects or an entire critical domain of the platform. For example, they might own the “AI Code Execution and Validation” domain end-to-end, which includes everything from sandboxing, static analysis, runtime monitoring, to deployment integration for AI-generated code.

In this role, an engineer has broad autonomy to define technical approaches and is trusted to make decisions that affect the architecture of the overall system. They coordinate closely with the engineering manager and principal engineers to ensure the platform meets strategic goals. This level is analogous to advanced staff engineers at leading companies – those who have designed large-scale AI or distributed systems and are recognized for solving hard technical problems, such as multi-agent orchestration and cloud scalability.

Key Outputs & Outcomes:

• Strategic Technical Plans: Clearly defined architecture roadmaps and design documents for major parts of the platform, ensuring the team is moving in a coherent direction that aligns with business needs and technological evolution. Outcomes include approved architecture proposals and funded projects based on your plans.
• Successful Delivery of Complex Projects: Completion of large-scale projects under your technical leadership, on time and within performance/scope goals. For example, a new AI-driven code verification service is delivered and reduces human code review effort by, say, 50% – a direct measurable improvement tied to your initiative.
• Technical Innovation: Introduction of new technologies or approaches that significantly improve the platform’s capabilities or efficiency. This could be measured by performance metrics (e.g., system throughput improved by a factor due to your prototyped optimization) or capabilities (e.g., the platform can now support an additional programming language or framework for code generation, expanding Toshiba’s product offerings). Possibly also patents or internal IP generated from innovative solutions.
• Organizational Learning & Standards: The broader org benefits from best practices you establish. For instance, coding standards or security practices you champion become standard operating procedure, reducing bugs and incidents. Other engineers step up with improved design thinking and autonomy, influenced by your mentorship (e.g., you see mid-level engineers confidently leading sub-projects using approaches you advocated).

Responsibilities:

• Technical Roadmapping & Design:
  • Work with Principal Engineer and leadership to define the technical roadmap for your domain (e.g., “AI Code Execution and Validation”). Break down the long-term vision into concrete projects and architecture updates. For instance, plan a series of enhancements over the next year to enable the AI agent to handle larger codebases or multi-module systems autonomously. Author high-level architecture proposals and lead technical planning meetings.
• Project Technical Leadership:
  • Lead the execution of major engineering initiatives. This includes driving project timelines, making critical design decisions, and ensuring cohesion across components. For example, if rolling out a new autonomous code analysis service, decide on the tech stack (perhaps adopting an open-source static code analysis tool and extending it), outline the API contracts between services, and ensure that engineers on the project implement according to specifications. Perform risk management by identifying potential technical pitfalls early (scalability, security) and mitigating them.
• Innovation & Prototyping:
  • Investigate emerging technologies or methods to keep improving the agentic AI platform. Prototype solutions to particularly challenging problems. E.g., evaluate a new LLM with better code understanding, or prototype a new approach for the AI to self-debug runtime errors using reinforcement learning. Based on results, make recommendations (or decisions) on whether to integrate these innovations. This may involve reading research papers or collaborating with research teams, and turning insights into proof-of-concept code..
• Cross-Functional Collaboration:
  • Interface with other groups (Product, QA, Security, Operations) at a senior level. For instance, work with Product Management to understand requirements for new agent capabilities (like supporting a new programming language or framework), and translate that into technical requirements. Coordinate with Ops/IT to ensure the infrastructure supports new features (perhaps needing new server instances or services). Guide QA on designing tests for complex AI-driven features. Essentially, be the technical liaison ensuring that all stakeholders are aligned on what is being built and how it will operate.
• Mentoring and Technical Influence:
  • Influence and uplift the broader engineering team’s skills. Mentor not only direct team members but also engineers in adjacent teams on areas of your expertise (e.g., secure coding practices, or effective use of a new tool you introduced). Review critical design docs from other engineers, providing seasoned insight. Lead by example in fostering a culture of engineering excellence and “autonomous first” thinking – encouraging the team to build solutions that maximize what AI agents can safely do on their own.

Required Skills & Experience:

• 10 years of software engineering experience, including substantial time as a senior/staff engineer driving large projects. Demonstrated ability to lead without direct authority, influencing peers and juniors to achieve engineering goals.
• Exceptional system design and analytical skills – able to conceptualize complex systems, reason about interactions between components (including failure modes and edge cases), and ensure correctness and robustness in design. Experience designing mission-critical systems (high uptime, high security, etc.) is expected.
• Deep knowledge of distributed systems and cloud architecture. Comfortable designing solutions that involve multiple services, databases, queues, and know how to ensure they work together (e.g., eventual consistency issues, transaction management, messaging patterns).
• Proficient in agentic AI toolchains: understanding not just how to use LLMs, but how to build frameworks around them (tool invoking, chaining results, long-horizon planning for agents, etc.). Likely has worked with AI agents or extensive ML-driven systems and knows their pitfalls.
• Mastery of development tools and programming paradigms. For example, able to navigate and improve a large codebase in Python, while also harnessing low-level languages or performance techniques when needed (embedding C/C for performance critical sections, etc.).
• Broad knowledge of software engineering domains: from front-end considerations (if building any UI for monitoring the AI agents) to back-end, databases, networking, and even a bit of ML theory – you can converse with specialists in any of these areas and integrate their work.
• Strong sense of ownership and accountability. Consistently delivers on commitments and takes responsibility for the technical success of the platform.
• Excellent communication and leadership skills: can clearly communicate complex technical vision to engineers and also articulate value and risk to non-technical stakeholders/executives.

Preferred Skills & Tools:

• Multi-Language and Legacy Systems: Experience ensuring AI-generated code works across different tech stacks (Java, C , Python, etc.) – useful if Toshiba’s solutions involve multiple languages. Understanding how to interface with legacy systems through APIs or adapt AI outputs to legacy constraints is a plus.
• LLM Fine-tuning/Customization: While not a data science role, experience in fine-tuning models or customizing LLMs for specific tasks could be valuable, as it allows better alignment of the model’s output with the platform’s needs.
• Advanced Security Knowledge: Familiarity with advanced topics like formal methods for software verification, or static/dynamic analysis tools (Coverity, SonarQube, etc.), which can be used to automatically vet AI-generated code. Also knowledge of compliance standards (ISO, SOC2, etc.) if the platform must adhere to them.
• Global Scale & Distributed Teams: Experience working on systems that operate globally (multiple regions, dealing with network partitions, replication) and coordinating development across distributed teams. Toshiba is a global company; an Engineer V might occasionally coordinate with teams in different geographies for this platform.
• Community Engagement: Recognized in professional communities (conferences, open-source) for expertise in relevant domains (AI engineering, DevOps, etc.). This can help Toshiba’s Agentic AI org stay connected with industry advances.

Toshiba Global Commerce Solutions is a dynamic billion-dollar global company based in Research Triangle Park, NC, providing retail store solutions to your favorite brands. Have you ever been in a hurry and made use of the self-checkout at Lowe's Foods, earned fuel rewards at Kroger, or just paid for purchases at retailers such as Walmart, Michaels, Carrefour, The Gap, Calvin Klein, Boots, Cencosud, BJ's, or Costco? These are just a few examples of our in-store solutions and impressive customer base that made us the world's installed market share leader.

The nature of retail is changing quickly, so if you share our 'Together Commerce' vision of a seamless two-way, participatory shopping experience, let's get together to drive the new economy.

Toshiba Global Commerce Solutions, Inc. offers a competitive salary and generous benefits package including the following:

• Group health coverage (medical, dental, & vision)
• Employee Assistance Programs
• Pre-tax spending accounts
• 401(k) plan (with company match)
• Company provided life insurance
• Pet Insurance
• Employee discounts
• Generous paid holiday schedule, paid vacation & sick/personal days

EEO:

Toshiba Global Commerce Solutions is an equal opportunity/affirmative action employer that evaluates qualified applicants without regard to age, ancestry, color, religious creed, disability, marital status, medical condition, genetic information, military or veteran status, national origin, race, sex, gender, gender identity, gender expression and sexual orientation or any other protected factor. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

Individuals who need a reasonable accommodation because of a disability for any part of the employment process should email benefits@toshibagcs.com to request an accommodation

DIVERSITY, EQUITY & INCLUSION:

We at Toshiba Global Commerce Solutions firmly believe that our people are an integral part to the success of our customers. Furthermore, we're committed to Diversity, Equity, and Inclusion for all our people as highlighted by our 5 Core Principles (Create Outreach, Foster Belonging, Unleash Opportunity, Diverse Cultural Engagement and Culture of Transparency). We're passionate about our customers the retail industry and becoming a more responsible company as we help create a brighter future.