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System Soft Technologies

Senior Software Developer, AI Solutions

Quebec, QC, Canada

Job type: Full-time
Apply by: Oct 29, 2026
Experience: CS/CE degree, 7+ years’ experience, 5+ in Python.
Posting language: English
Posted: Sep 29, 2026

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Original job description

Job Summary

client is looking for a senior software engineer - a builder first - for our AI Solutions team. This is a hands-on development role, not machine-learning research: you’ll build production agentic solutions for our customers and for client from the building blocks of agentic systems - context, memory, guardrails, orchestration. You’re past the debate about using AI coding tools - you use them daily to ship more - and you bring the architecture instinct to design systems, guide agents, and validate what they build.

Note: this is a software development role, not ML research or modeling.

Responsibilities:

Build agentic AI solutions for customers and client from the core building blocks: context, memory, guardrails, tool calling / MCP, skills, and orchestration.
Design the harness, context, and loops that let agents do real development - including agents that build software.
Use agentic coding tools daily to maximize output, then attack the next bottleneck in the SDLC.
Steer agents with software-architecture direction and validate their output - hallucinated APIs, risky dependencies, security regressions.
Evaluate and adopt emerging AI tooling into Syntax’s practices.
Own delivery end to end and communicate clearly on specs, decisions, and roadblocks.

Qualifications:

Strong software-engineering foundation with production software you’ve built, shipped, and owned.
CS/CE degree, 7+ years’ experience, 5+ in Python.
Solid architecture and system design - decompose an ambiguous problem, design the solution, guide humans or agents to build it.
Daily, fluent use of agentic coding tools (Claude Code, Codex, Copilot).
Fluency with the building blocks of agentic AI: context, memory, guardrails, tool calling / MCP, and skills.
Judgment to validate AI output - hallucinated APIs, risky dependencies, security regressions.
Clear communication, precise specification writing, and Git proficiency.

Plus:

Shipped production agentic systems or AI-powered applications end to end.
Contributed to MCP servers/tools, eval frameworks, or agent-orchestration frameworks.
GenAI frameworks (LangChain, LlamaIndex, CrewAI) and model evaluation; GitLab and GitLab CI.
Cloud services and deployments (AWS, Azure, GCP).

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More about this job

Responsibilities

Build and deliver production agentic AI solutions, including the context, memory, guardrails, tool calling, and orchestration that enable agents to perform real development work. Use AI coding tools, guide and validate agent output, evaluate emerging tools, and own delivery while communicating specifications, decisions, and roadblocks.

Requirements

Requires a strong production software engineering background, a CS/CE degree, at least seven years of experience, and at least five years with Python. Candidates should have strong architecture and system-design skills, daily experience with agentic coding tools, fluency in agentic AI building blocks, sound judgment validating AI output, clear communication, and Git proficiency.

Skills

Python
Software Architecture
System Design
Agentic AI
Context Engineering
Memory Systems
Guardrails
Tool Calling
Model Context Protocol (MCP)
Agent Orchestration
Agentic Coding Tools
AI Output Validation
Git
GenAI Frameworks
Model Evaluation
Cloud Deployment

Visa sponsorship

Not detected in the job text

Keywords

Python
Agentic AI
Production Software
Software Architecture
System Design
Context
Memory
Guardrails
Tool Calling
Model Context Protocol (MCP)
Skills
Orchestration
Agentic Coding Tools
Claude Code
Codex
GitHub Copilot
AI Output Validation
Security Regressions
Git
LangChain
LlamaIndex
CrewAI
Model Evaluation
GitLab
GitLab CI
AWS
Azure
Google Cloud Platform
Agent-Orchestration Frameworks
Eval Frameworks

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