Staff Software Engineer
Greybridge Search & Selection
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.
#J-18808-Ljbffr
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.
#J-18808-Ljbffr
Reference: WJ-3875_12643232