Lead AI Forward Engineer

Thomson Reuters

. Identify high-impact opportunities to apply AI automation and intelligent agents across CIO technology teams .

Posted 9/29/2026full-timeUnited StatesSenior💰 $127,400 - $236,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI solutions, including end-to-end architecture, integration patterns, and operational workflows. Proficient in collaborating with cross-functional teams to ensure compliance, reliability, and performance of AI systems in complex enterprise environments.

Highest-signal resume keywords

AI Solution DesignEnd-to-End ArchitecturePython ProficiencyCloud Architecture (AWS, Azure, GCP)AI Observability

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Applicant Tracking System Keywords

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Hard Skills

Solution ArchitectureIntegration PatternsAPIsData FlowsDistributed SystemsAI/ML Application PatternsTelemetry PipelinesDevOps PrinciplesMicroservicesPolicy Enforcement

Soft Skills

Strong Communication SkillsTechnical LeadershipMentoring

Tools & Technologies

LangChainLlamaIndexServiceNowCI/CD ToolsObservability Tooling

Industry Keywords

AI StandardsOperational ExcellenceEnterprise GovernanceComplianceAuditability

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformITSMMicroservicesPythonServiceNow

About the role

Key responsibilities & impact

Identify high-impact opportunities to apply AI automation and intelligent agents across CIO technology teams
Partner with engineering teams, service owners, and stakeholders to translate business needs into technical requirements, solution designs, and delivery plans
Design end-to-end AI solutions, including workflows, integration patterns, data flows, APIs, and operational considerations
Guide implementations from prototype through production, ensuring reliability, security, compliance, and maintainability
Define reusable architectural patterns and reference designs for broader AI adoption
Build scalable pipelines for inference-level and workflow-level telemetry, integrating data with Thomson Reuters' data backbone
Develop dashboards and reporting for AI performance, reliability, safety, usage, and cost
Ensure compliance with Thomson Reuters AI standards for monitoring, governance, privacy, auditability, and operational controls
Evaluate and recommend AI/ML technologies and platforms
Design flexible architectures adaptable to changing models, providers, requirements, and AI capabilities
Establish and track SLIs and SLOs for critical AI services
Integrate AI observability tooling into CI/CD processes
Develop automated guardrails and policy-enforcement mechanisms
Partner with Product, Data Science, AI Inference Engineering, and Enterprise AI teams on LLM and ML evaluation frameworks
Onboard AI use cases into the observability platform
Collaborate with Cloud Engineers across AWS, Azure, and GCP, plus SRE and platform teams, on observability, capacity planning, and operational management
Support scaling, monitoring, and operational readiness of AI infrastructure during major releases and global events
Communicate technical trade-offs, architecture decisions, risks, and recommendations to technical and non-technical stakeholders, including senior leadership
Mentor engineers and share patterns, practices, and lessons learned

Requirements

What you’ll need

6+ years of progressive experience in solution architecture, technical strategy, senior engineering, platform engineering, or related technical roles
Experience building software prototypes and delivering solutions to production in ambiguous, low-precedent environments
Strong end-to-end solution design and architecture capability, including integration patterns, APIs, data flows, distributed systems, and operational design
Working knowledge of AI/ML and LLM application patterns, including LLM capabilities and limitations, prompt design, orchestration approaches, agent workflows, RAG, vector search, and enterprise integration considerations
Practical understanding of production AI system trade-offs, including latency, quality, cost, safety, reliability, context-window constraints, hallucinations, and provider variability
Experience designing, building, operating, or observing production AI systems and associated telemetry, monitoring, evaluation, and operational workflows
Proficiency in Python
Cloud architecture familiarity in AWS, Azure, or GCP, including common service patterns, enterprise constraints, and security considerations
Knowledge of microservices, distributed systems, CI/CD, cloud-native architectures, and API-driven integration approaches
Experience with DevOps, Platform Engineering, or SRE principles and designing systems for operational excellence
Strong communication skills, with the ability to document designs, influence decisions, and align diverse technical and business stakeholders
Demonstrated technical leadership through mentoring, architectural governance, cross-team enablement, or shared standards
Familiarity with LLM frameworks and patterns, such as LangChain, LlamaIndex, or comparable technologies
Experience with AI observability, including telemetry pipelines, dashboards, alerting, service-level indicators, service-level objectives, and evaluation frameworks
Experience designing AI guardrails, policy enforcement, anomaly detection, or AI safety and reliability controls
Exposure to enterprise service management platforms, such as ServiceNow or comparable ITSM tools
Exposure to security architecture, privacy, compliance-oriented environments, enterprise governance, and auditability requirements
Experience collaborating with Product, Data Science, AI Inference Engineering, Enterprise AI, Cloud Engineering, SRE, or Platform Engineering teams
Experience supporting the scaling and monitoring of AI infrastructure and workloads in large, complex enterprise environments

Benefits

Comp & perks

Flexible hybrid working environment
Work from anywhere for up to 8 weeks per year
Flexible vacation
Two company-wide Mental Health Days off
Headspace app access
Retirement savings
Competitive 401k plan with company match
Tuition reimbursement
Employee incentive programs
Resources for mental, physical, and financial wellbeing
Two paid volunteer days off annually
Pro-bono consulting project opportunities
Environmental, Social, and Governance (ESG) initiative opportunities
Health, dental, vision, disability, and life insurance programs
Competitive vacation, sick and safe paid time off
Paid holidays, including two company mental health days off
Parental leave
Sabbatical leave
Optional hospital, accident and sickness insurance
Optional life and AD&D insurance
Flexible Spending and Health Savings Accounts
Fitness reimbursement
Employee Assistance Program
Group Legal Identity Theft Protection benefit
529 Plan access
Commuter benefits
Adoption & Surrogacy Assistance
Employee Stock Purchase Plan
Annual Bonus based on enterprise and individual performance