Closed listing
Staff Software Engineer, AI
- Toronto, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Experience
- 8+ years software engineering experience
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
We're seeking a Staff Software Engineer, AI to help lead the design, development, and scaling of enterprise AI solutions at Thomson Reuters.
This is a senior technical leadership role focused on building production-grade AI systems, RAG architectures, agent-based workflows, and LLM-powered applications that support legal, tax, risk, and compliance professionals.
The ideal candidate combines deep software engineering expertise with hands-on experience delivering AI products at scale.
Required Experience
- 8+ years software engineering experience
- 4+ years in AI/ML-focused engineering roles
- Expert-level Python
- Generative AI, LLMs, and RAG architectures
- AI agent frameworks and orchestration
- Distributed systems and large-scale system design
- Cloud platforms (AWS, Azure, or GCP)
- Kubernetes, Docker, Terraform
- MLOps / LLMOps
- Production AI deployments
Preferred Experience
- OpenAI, Anthropic, Claude, Gemini, or similar LLM platforms
- Vector databases, embeddings, and semantic search
- Enterprise AI governance and model risk management
- AI product launches and production scaling
- Experience in legal, tax, accounting, compliance, or other regulated industries
- Speaking, publishing, or thought leadership within the AI space
Target Titles
- Staff AI Engineer
- Principal AI Engineer
- Staff Software Engineer
- Lead AI Engineer
- AI Platform Engineer
- Staff Machine Learning Engineer
- Applied AI Engineer
- AI Systems Engineer
Ideal Candidate
Looking for engineers who have built and scaled production AI systems, can drive technical strategy, mentor engineers, influence architecture decisions, and translate emerging AI capabilities into enterprise-ready products.
Red Flags
- Prompt engineering only
- Academic AI backgrounds with limited software engineering depth
- No production AI deployment experience
- No large-scale architecture experience
- Frontend-heavy backgrounds
LinkedIn Skills I Would Add
Required
- Python
- Artificial Intelligence (AI)
- Generative AI
- Machine Learning
Nice to Have
- AWS
- Kubernetes
- Large Language Models (LLM)
- Retrieval-Augmented Generation (RAG)
More about this job
Responsibilities
Lead the design, development, and scaling of enterprise AI solutions, including production-grade AI systems, RAG architectures, agent-based workflows, and LLM-powered applications. Drive technical strategy and architecture decisions, mentor engineers, and turn emerging AI capabilities into enterprise-ready products for legal, tax, risk, and compliance professionals.
Requirements
Requires 8+ years of software engineering experience, including 4+ years in AI/ML-focused engineering roles, expert-level Python, and hands-on experience delivering AI products at scale. Candidates should have expertise in generative AI, LLMs, RAG, agent orchestration, distributed systems, cloud platforms, containers, infrastructure as code, and production AI operations.
Skills
- Python
- Artificial Intelligence
- Generative AI
- Machine Learning
- Large Language Models
- Retrieval-Augmented Generation
- AI Agent Frameworks
- Distributed Systems
- System Design
- AWS
- Azure
- Google Cloud Platform
- Kubernetes
- Docker
- Terraform
- MLOps
Visa sponsorship
Not detected in the job text
Categories
- Software
- Technology
- Engineering
- Management & Leadership
- Data & Analytics
Keywords
- Python
- Artificial Intelligence
- Generative AI
- Machine Learning
- Large Language Models
- Retrieval-Augmented Generation
- AI Agents
- Agent Orchestration
- Distributed Systems
- Large-Scale System Design
- AWS
- Azure
- Google Cloud Platform
- Kubernetes
- Docker
- Terraform
- MLOps
- LLMOps
- OpenAI
- Anthropic
- Claude
- Gemini
- Vector Databases
- Embeddings
- Semantic Search
- Enterprise AI Governance
- Model Risk Management
- Production AI Deployment
- Legal Technology
- Regulated Industries