Lead AI Forward Engineer

The Lead AI Forward Engineer designs and guides the delivery of AI-powered solutions that reduce operational toil and accelerate technology teams across the CIO organization.

This role operates as a forward-deployed solution architect and engineer, partnering closely with teams to identify opportunities, design end-to-end architectures, and drive implementations to production.

Solution Architecture and Delivery

• Identify high-impact opportunities to apply AI automation and intelligent agents across CIO technology teams.
• Design end-to-end AI solutions, including workflows, integration patterns, data flows, and operational considerations.
• Guide implementation from prototype to production, ensuring solutions meet reliability, security, and compliance expectations.
• Define reusable architectural patterns and reference designs to enable broader adoption across teams.
• Build scalable pipelines to collect and analyze inference- and workflow-level telemetry, integrating with TR's data backbone.
• Develop dashboards and reports providing clear visibility into performance, reliability, safety, and cost.
• Ensure compliance with TR's AI standards for monitoring, governance, privacy, and auditability.

AI System Design and Technology Strategy

• Evaluate and recommend AI/ML technologies and platforms (LLM orchestration, agentic frameworks, cloud AI services) based on capability, cost, risk, and fit.
• Design flexible architectures that can evolve with model/provider changes and emerging AI capabilities.
• Apply sound judgment on when AI is appropriate vs. when simpler automation or traditional engineering approaches are better.
• Establish and track SLOs/SLIs for critical AI services to meet enterprise reliability and compliance requirements.
• Integrate AI observability tooling into CI/CD so new models, prompts, and workflows are automatically enrolled in monitoring and evaluation.
• Develop automated guardrails and policy enforcement (e.g., limits, anomaly detection, abuse/failure pattern detection) with cloud engineering and security teams.

Cross Functional Partnership and Influence

• Partner with engineering teams, service owners, and stakeholders to translate business needs into technical requirements and solution designs.
• Communicate trade-offs and design decisions clearly to both technical and non-technical audiences, including senior leadership when needed.
• Mentor engineers and share patterns, practices, and lessons learned to raise overall AI solution design maturity.
• Partner with Product, Data Science and AI teams to design and run evaluation frameworks for LLMs/ML models (offline/online tests, benchmarks, canaries, A/B experiments).
• Work with Product, Data Science, AI Inference Engineering, and Enterprise AI teams to onboard new AI use cases into the observability platform from day one.
• Collaborate with Cloud Engineers (AWS, Azure and GCP) and SREs to align AI observability with broader platform observability and capacity management.
• Support scaling and monitoring of AI infrastructure and workloads during major releases and global events.

Required Skills & Qualifications

• Strong solution design/architecture capability: end-to-end system design, integration patterns, API thinking, and operational design.
• Working knowledge of AI/ML and LLM application patterns, including:
• LLM capabilities/limitations, prompt design, orchestration approaches, and agent workflows
• Practical trade-offs (latency, quality, cost, safety, reliability)
• Production AI systems and observability challenges (prompting, context windows, RAG, hallucinations, provider variability).
• Proficiency in Python (strongly preferred) and ability to prototype and validate designs with hands-on technical work.
• Cloud architecture familiarity in AWS, Azure, or GCP, including common service patterns and enterprise constraints.
• Knowledge of distributed systems, microservices, CI/CD, and cloud-native architectures.
• Strong communication skills: ability to document designs, influence decisions, and align diverse stakeholders.

What's in it For You?

• Hybrid Work Model: We've adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
• Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset.
• Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow's challenges and deliver real-world solutions.
• Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
• Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more.