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Encore Technical Solutions Inc.

Senior Machine Learning Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Oct 31, 2026
Posting language: English
Posted: Oct 1, 2026

Original job description

Senior AI Engineer, Agentic Systems

Start Date - October 2026

📍 [Toronto / Hybrid] | Full-time

Our client is a global financial services leader making a major strategic investment in AI. They're hiring a Senior AI Engineer to design, build and own the agentic systems that put their models in front of business users, and to make those systems reliable enough to stay there.

What you'll do

Build agentic systems end-to-end, covering agent loops, orchestration, memory and state, and tool integrations
Diagnose and fix real-world failures such as stalled loops, tool misuse and behaviour that drifts between runs
Build evaluation sets and regression checks that reflect real workflows, so quality is measured continuously and not only at demo time
Balance latency, answer quality and token cost for each workflow
Connect agents to systems of record and take them from prototype to production

What you'll bring

Deep expertise in production Python
Hands-on experience with agent frameworks and protocols such as the Claude Agent SDK, LangGraph, MCP or equivalents
Experience building and debugging agentic systems in production
Rigour in evaluation, with measurement designed for business use rather than demos
Strong engineering discipline: version control, tests, reproducibility and maintainable code
A background as either a software engineer who moved into AI, or an AI engineer with strong systems fundamentals

Nice to have

Agent tracing and evaluation tools, such as LangSmith, W&B or custom solutions
Event-driven or distributed systems, such as Kafka
Retrieval and memory design for long-running agents
Full-stack experience integrating agents into user-facing apps

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More about this job

Responsibilities

Design, build, and operate production agentic systems, including agent loops, orchestration, memory, state, and integrations with business systems. Diagnose production failures, create workflow-based evaluations and regression checks, optimize latency, answer quality, and token costs, and move agent prototypes into production.

Requirements

Requires deep production Python expertise and hands-on experience building and debugging agentic systems using frameworks or protocols such as Claude Agent SDK, LangGraph, or MCP. Candidates should bring strong systems fundamentals, rigorous evaluation practices, and disciplined engineering practices including version control, testing, reproducibility, and maintainable code.

Skills

Production Python
Agentic Systems
Agent Frameworks
Claude Agent SDK
LangGraph
Model Context Protocol (MCP)
Agent Orchestration
Agent Evaluation
Debugging
Regression Testing
Tool Integration
Version Control
Reproducible Engineering
Distributed Systems
Retrieval and Memory Design
Full-Stack Development

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Agentic Systems
Production Python
Claude Agent SDK
LangGraph
Model Context Protocol (MCP)
Agent Loops
Orchestration
Memory and State
Tool Integrations
Production Systems
Evaluation Sets
Regression Checks
Latency Optimization
Answer Quality
Token Cost
Systems of Record
Agent Tracing
LangSmith
Weights & Biases
Event-Driven Systems
Distributed Systems
Kafka
Retrieval Design
Full-Stack Development
Version Control
Testing
Reproducibility
Financial Services

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