Software Engineering SMTS
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- You have 6+ years experience designing and building large scale, distributed backend systems.
- Posting language
- English
- Posted
Original job description
Description
The Experience The Agentic Setup team builds AI agents, on a skills based architecture, that turn expert only, multi step product configuration, Org troubleshooting and management into natural language, agent assisted workflows. As part of this team, you will work across agent runtime, capability and skill design, evaluation infrastructure, and the systems that let agents find and act on the right data.We are looking for a Lead Software Engineer to help us build agentic experiences for product setup and configuration. You will help design a core agent framework, contribute to a growing skills ecosystem, and build the evaluation infrastructure that keeps agent behavior trustworthy as it scales. This role is based in San Francisco. You'll join a team building intelligent systems that automate the repetitive, elevate the strategic, and power better decisions at scale.What You'll Actually Be Doing
Design and build a core agent framework that hosts many specialized capabilities, orchestrates sub tasks reliably, and integrates seamlessly into human workflows.
Define the contract for reusable agent skills, focusing on API design, versioning, and composability so many teams can build and contribute consistently.
Build evaluation infrastructure that measures agent quality even when outputs are non deterministic, and use that signal to catch regressions over time.
Help agents efficiently find the right records and context using structured queries, catalogs, and semantic search.
Build and ship high quality, production grade software using modern engineering practices, with AI as a core part of your development workflow, pushing the boundaries of AI development tools to deliver secure, optimized, and high quality code.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code, human or AI generated, for correctness, quality, security, and performance.
You're Our Person If...
You have 6+ years experience designing and building large scale, distributed backend systems.
You have experience with API design, versioning, and building systems that many teams build on top of.
You have strong skills in at least one modern programming language and experience shipping production code.
You can reason clearly about ambiguous, large scale systems and communicate tradeoffs to a team.
You have a demonstrated, genuine AI first approach to engineering, using AI tools (such as Claude Code, GitHub Copilot, Codex, or Cursor) to move faster, build fluency across the stack, and contribute well beyond your core specialty.
You have advanced prompt engineering skills and the ability to write precise, structured prompts, cultivating the system context that makes AI outputs reliable, secure, and production ready.
You have a related technical degree.
Even Better If...
You have experience building or working with AI agents, large language model (LLM) based systems, or evaluation infrastructure for non deterministic outputs.
You have experience with retrieval systems such as semantic search or structured data catalogs.
You have experience migrating purpose built automation into general, composable APIs.
The Experience The Agentic Setup team builds AI agents, on a skills based architecture, that turn expert only, multi step product configuration, Org troubleshooting and management into natural language, agent assisted workflows. As part of this team, you will work across agent runtime, capability and skill design, evaluation infrastructure, and the systems that let agents find and act on the right data.We are looking for a Lead Software Engineer to help us build agentic experiences for product setup and configuration. You will help design a core agent framework, contribute to a growing skills ecosystem, and build the evaluation infrastructure that keeps agent behavior trustworthy as it scales. This role is based in San Francisco. You'll join a team building intelligent systems that automate the repetitive, elevate the strategic, and power better decisions at scale.What You'll Actually Be Doing
Design and build a core agent framework that hosts many specialized capabilities, orchestrates sub tasks reliably, and integrates seamlessly into human workflows.
Define the contract for reusable agent skills, focusing on API design, versioning, and composability so many teams can build and contribute consistently.
Build evaluation infrastructure that measures agent quality even when outputs are non deterministic, and use that signal to catch regressions over time.
Help agents efficiently find the right records and context using structured queries, catalogs, and semantic search.
Build and ship high quality, production grade software using modern engineering practices, with AI as a core part of your development workflow, pushing the boundaries of AI development tools to deliver secure, optimized, and high quality code.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code, human or AI generated, for correctness, quality, security, and performance.
You're Our Person If...
You have 6+ years experience designing and building large scale, distributed backend systems.
You have experience with API design, versioning, and building systems that many teams build on top of.
You have strong skills in at least one modern programming language and experience shipping production code.
You can reason clearly about ambiguous, large scale systems and communicate tradeoffs to a team.
You have a demonstrated, genuine AI first approach to engineering, using AI tools (such as Claude Code, GitHub Copilot, Codex, or Cursor) to move faster, build fluency across the stack, and contribute well beyond your core specialty.
You have advanced prompt engineering skills and the ability to write precise, structured prompts, cultivating the system context that makes AI outputs reliable, secure, and production ready.
You have a related technical degree.
Even Better If...
You have experience building or working with AI agents, large language model (LLM) based systems, or evaluation infrastructure for non deterministic outputs.
You have experience with retrieval systems such as semantic search or structured data catalogs.
You have experience migrating purpose built automation into general, composable APIs.
More about this job
Responsibilities
Design and build a scalable agent framework, reusable skills ecosystem, and evaluation infrastructure for reliable AI-assisted product setup and configuration. Improve how agents retrieve relevant data and context, ship secure production-grade software, and maintain shared system context and engineering standards.
Requirements
Requires at least six years of experience building large-scale distributed backend systems, strong skills in a modern programming language, and experience with API design and production software. Candidates should use AI tools effectively, have advanced prompt-engineering skills, communicate system tradeoffs clearly, and hold a related technical degree; experience with agents, LLM systems, evaluation infrastructure, or retrieval systems is an advantage.
Skills
- Distributed Backend Systems
- Agent Framework Design
- API Design
- API Versioning
- Software Engineering
- AI Agents
- Prompt Engineering
- Evaluation Infrastructure
- Semantic Search
- Structured Queries
- System Design
- Security
- Performance Optimization
- Cross-Functional Communication
Visa sponsorship
Not detected in the job text
Categories
- Software
- Technology
- Engineering
Keywords
- Agentic Systems
- AI Agents
- Agent Runtime
- Agent Framework
- Reusable Skills
- API Design
- API Versioning
- Distributed Backend Systems
- Large Language Models
- Evaluation Infrastructure
- Non-Deterministic Outputs
- Semantic Search
- Structured Queries
- Data Catalogs
- Prompt Engineering
- Claude Code
- GitHub Copilot
- Codex
- Cursor
- Production Software
- System Context
- System Design
- Security
- Performance Optimization
- Human Workflows