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Within Thomson Reuters' AI Reimagine program, the Lead AI Forward Engineer designs and guides the delivery of AI-powered solutions that reduce operational toil and accelerate technology teams across Platform Engineering, Product Engineering, and Service Management.
This role operates as a forward-deployed solution architect—partnering closely with teams to identify opportunities, design end-to-end architectures, and drive implementations to production.
You will own solution design from concept through deployment, ensuring solutions are scalable, maintainable, and extensible.
You will evaluate emerging AI technologies (LLM orchestration, agent frameworks, cloud AI services), define repeatable patterns, and help build organizational capability through mentorship and shared standards.
**About the Role**
**Solution Architecture and Delivery**
- 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.
- 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 general events.
- Strong solution design/architecture capability: end-to-end system design, integration patterns, API thinking, and operational design.
- 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.
**About you**:
- **6+ years**of experience with progression in solution architecture, technical strategy, or senior engineering roles.
- Experience building software prototypes and taking solutions to production in ambiguous, low-precedent environments.
- Familiarity with LLM frameworks and patterns (e.g., LangChain, LlamaIndex), RAG/vector search concepts, and enterprise integration considerations.
- Experience with DevOps/Platform Engineering/SRE principles and designing for operational excellence.
- Exposure to enterprise service management (e.g., ServiceNow/ITSM), security architecture, and compliance-oriented environments.
- Demonstrated technical leadership through mentoring, architectural governance, or cross-team enablement.
LI-AC1
**What's in it For You?
**
- **Hybrid Work Model**:We

Postúlate en Kit Empleo: kitempleo.com.mx/empleo/560hi0

📌 Lead Ai Forward Engineer (Xico)
🏢 Thomson Reuters
📍 Xico