Staff Software Engineer

Greybridge Search & Selection; Toronto; On-site; CAD 140,000 - 175,000; Full time

Job summary

Greybridge Search & Selection is seeking a Staff Software Engineer in Toronto to design and scale production-grade AI systems. You will bridge AI research and engineering, building agentic AI capabilities and multi-step workflows with a focus on reliability and governance.

You will work across AI ingestion, data pipelines, retrieval, and cloud infrastructure, mentoring engineers and making architecture decisions that balance performance, cost and accuracy in production.

Qualifications

• Strong experience building and deploying AI-powered applications.
• Experience designing agentic AI systems or AI workflows.
• Experience taking AI solutions into production cloud environments.
• Hands-on with LangGraph, LangFuse, Kubernetes and Docker.
• Experience with AI evaluation, monitoring and observability.
• Solid understanding of distributed systems and software engineering fundamentals.
• Experience with RAG, semantic search, embeddings or information retrieval.
• Familiarity with PyTorch is beneficial.
• Experience working with cloud platforms — AWS preferred, but cloud-agnostic experience is relevant.
• Strong understanding of data structures, algorithms and core CS principles.
• Ability to make sound technical decisions and explain trade-offs.
• Experience operating at Senior, Lead or Staff level, with significant technical ownership.

Responsibilities

• Architect and develop scalable, production-grade AI systems and platforms.
• Build and integrate agentic AI solutions capable of executing complex, multi-step workflows.
• Develop AI-powered applications using LLMs, RAG and retrieval technologies.
• Build cloud-native infrastructure and distributed systems supporting AI workloads.
• Design ingestion, storage, search and data-processing pipelines at scale.
• Develop and implement AI evaluation frameworks, metrics and quality processes.
• Establish monitoring, observability and operational practices for AI systems.
• Work closely with product, engineering and subject-matter experts to translate complex requirements into technical solutions.
• Evaluate emerging AI technologies and determine where they can deliver genuine value.
• Make architectural decisions across scalability, reliability, cost, performance and accuracy.
• Provide technical leadership and mentorship to other engineers.

Skills

AI-powered applications

Agentic AI systems

Production cloud environments

RAG/semantic search

Distributed systems

Data structures & algorithms

Cloud platforms (AWS)

PyTorch

Tools

Kubernetes

Docker

LangGraph

LangFuse

AWS

Job description

Staff Software Engineer - Agentic AI - Toronto $140,000 - $175,000 + 15% bonus (3 x days per week)

We’re working with a global technology organisation that is investing heavily in AI, agentic systems and intelligent products. The team is building next-generation AI capabilities that support professionals working in highly complex, information-rich and regulated environments.

This is a hands-on Staff-level engineering role sitting at the intersection of AI engineering, platform engineering and applied AI. You’ll be working on systems where accuracy, reliability, evaluation and governance genuinely matter — rather than simply building another chatbot.

You’ll help design, build and scale production-grade AI systems, with opportunities to contribute across areas including:

• Agentic AI and multi-step workflows
• AI-powered ingestion and data pipelines
• Search, retrieval and RAG systems
• AI platform and infrastructure
• Distributed systems and storage
• Evaluation, monitoring and observability
• Cloud-native AI applications
• AI governance, reliability and lifecycle management

You’ll have the opportunity to work across different layers of the platform depending on your experience — from the underlying infrastructure and ingestion pipelines through to search and the agentic layer.

A key part of the role is bridging the gap between AI research and practical engineering: understanding what modern AI can do, but knowing how to build, deploy, monitor and continuously improve those capabilities in production.

What You’ll Be Doing

• Architect and develop scalable, production-grade AI systems and platforms.
• Build and integrate agentic AI solutions capable of executing complex, multi-step workflows.
• Develop AI-powered applications using LLMs, RAG and retrieval technologies.
• Build cloud-native infrastructure and distributed systems supporting AI workloads.
• Design ingestion, storage, search and data-processing pipelines at scale.
• Develop and implement AI evaluation frameworks, metrics and quality processes.
• Establish monitoring, observability and operational practices for AI systems.
• Work closely with product, engineering and subject-matter experts to translate complex requirements into technical solutions.
• Evaluate emerging AI technologies and determine where they can deliver genuine value.
• Make architectural decisions across scalability, reliability, cost, performance and accuracy.
• Provide technical leadership and mentorship to other engineers.

You’ll ideally bring:

• Strong professional experience building and deploying AI-powered applications.
• Experience designing and building agentic AI systems or AI workflows.
• Experience taking AI solutions into production cloud environments.
• Hands-on experience with technologies such as LangGraph, LangFuse, Kubernetes and Docker.
• Experience with AI evaluation, monitoring and observability.
• Solid understanding of distributed systems and software engineering fundamentals.
• Experience with RAG, semantic search, embeddings or information retrieval.
• Familiarity with modern AI/ML frameworks such as PyTorch is beneficial.
• Experience working with cloud platforms — AWS preferred, but cloud-agnostic experience is absolutely relevant.
• Strong understanding of data structures, algorithms and core computer science principles.
• The ability to make sound technical decisions and explain the trade-offs behind them.
• Experience operating at Senior, Lead or Staff level, with significant technical ownership.