Senior Software Engineer, Ai
$145k - $183k per yearToast
Job DescriptionToast is recruiting on behalf of this company for a Senior Software Engineer, AI to join their Engineering team in Toronto. They are looking for an experienced backend engineer who is excited to build and optimize LLM-powered systems that help users uncover meaningful business insights.
Responsibilities
Design, build, and maintain backend systems that power LLM-driven and agentic workflows
Develop retrieval pipelines, orchestration layers, and multi‑step agent architectures that support scalable AI‑powered search experiences
Lead the evaluation of agentic systems using automated, offline, and human‑in‑the‑loop frameworks to measure relevance, quality, latency, and task success
Improve retrieval and ranking systems across hybrid retrieval, re‑ranking, query rewriting, and post‑retrieval synthesis
Optimize LLM‑powered workflows for speed, accuracy, reliability, and production readiness
Own technical projects from concept through launch, including experimentation strategy, architecture decisions, and operational excellence
Collaborate closely with product, infrastructure, and data teams to align technical solutions with user needs and business goals
Stay current with advances in LLMs, retrieval systems, and agentic reasoning, and apply relevant developments to product and engineering work
Contribute to engineering best practices that support maintainability, observability, testing, and continuous delivery
Requirements
5+ years of experience building and operating backend systems in production
Strong experience in at least one of the following areas: search and retrieval, data pipelines, distributed systems, or API‑driven service architectures
2+ years of hands‑on experience working with search, retrieval, or ranking systems
Experience building or evaluating LLM‑powered or agentic systems, including retrieval‑augmented generation or multi‑step workflows
Strong software engineering fundamentals with the ability to write clean, maintainable, and well‑tested code
Proficiency in Python and experience with backend frameworks, APIs, and production infrastructure
Familiarity with vector databases and search platforms such as FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, or OpenSearch
Experience with cloud platforms such as AWS, GCP, or Azure in environments with scale, low‑latency requirements, and high availability
Experience using AI coding tools to improve development workflows
A customer‑focused mindset with the ability to connect technical decisions to user outcomes
Demonstrated ability to lead projects, make sound architectural decisions, and support the growth of others on the team
Benefits
Competitive compensation with a salary range of CA$145,000–CA$183,000, plus equity
Extended health and dental coverage starting from day one
Employee Stock Option Plan for full‑time employees
Flexible vacation policy designed to support rest and balance
Career development support through coaching, feedback, and performance reviews
Access to high‑quality equipment and tooling
Hybrid work model with in‑office collaboration in Toronto on designated days
Opportunities to work closely with leadership and contribute to meaningful technical direction
A workplace that values belonging, authenticity, accessibility, and professional growth
An inclusive hiring approach that considers potential, transferable experience, and equivalent backgrounds
#J-18808-Ljbffr
Responsibilities
Design, build, and maintain backend systems that power LLM-driven and agentic workflows
Develop retrieval pipelines, orchestration layers, and multi‑step agent architectures that support scalable AI‑powered search experiences
Lead the evaluation of agentic systems using automated, offline, and human‑in‑the‑loop frameworks to measure relevance, quality, latency, and task success
Improve retrieval and ranking systems across hybrid retrieval, re‑ranking, query rewriting, and post‑retrieval synthesis
Optimize LLM‑powered workflows for speed, accuracy, reliability, and production readiness
Own technical projects from concept through launch, including experimentation strategy, architecture decisions, and operational excellence
Collaborate closely with product, infrastructure, and data teams to align technical solutions with user needs and business goals
Stay current with advances in LLMs, retrieval systems, and agentic reasoning, and apply relevant developments to product and engineering work
Contribute to engineering best practices that support maintainability, observability, testing, and continuous delivery
Requirements
5+ years of experience building and operating backend systems in production
Strong experience in at least one of the following areas: search and retrieval, data pipelines, distributed systems, or API‑driven service architectures
2+ years of hands‑on experience working with search, retrieval, or ranking systems
Experience building or evaluating LLM‑powered or agentic systems, including retrieval‑augmented generation or multi‑step workflows
Strong software engineering fundamentals with the ability to write clean, maintainable, and well‑tested code
Proficiency in Python and experience with backend frameworks, APIs, and production infrastructure
Familiarity with vector databases and search platforms such as FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, or OpenSearch
Experience with cloud platforms such as AWS, GCP, or Azure in environments with scale, low‑latency requirements, and high availability
Experience using AI coding tools to improve development workflows
A customer‑focused mindset with the ability to connect technical decisions to user outcomes
Demonstrated ability to lead projects, make sound architectural decisions, and support the growth of others on the team
Benefits
Competitive compensation with a salary range of CA$145,000–CA$183,000, plus equity
Extended health and dental coverage starting from day one
Employee Stock Option Plan for full‑time employees
Flexible vacation policy designed to support rest and balance
Career development support through coaching, feedback, and performance reviews
Access to high‑quality equipment and tooling
Hybrid work model with in‑office collaboration in Toronto on designated days
Opportunities to work closely with leadership and contribute to meaningful technical direction
A workplace that values belonging, authenticity, accessibility, and professional growth
An inclusive hiring approach that considers potential, transferable experience, and equivalent backgrounds
#J-18808-Ljbffr
Vacancy posted 43 minutes ago
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