AI Platform Engineer

Acestack

Halifax

On-site

CAD 120,000 - 180,000

Full time

14 days+

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Job summary

Acestack is seeking an AI Platform Engineer in Halifax to design and scale an agentic AI platform that powers enterprise SDLC workflows. You will build agent harnesses, skills, and MCP servers, enabling teams to deploy AI-driven development at scale.

The role sits in DevOps and Platform Engineering, requiring hands-on software engineering, knowledge of LangChain/LangGraph, MCP servers, and Claude Code. Onsite with a 4-day work model.

Qualifications

  • Strong software development with Python and/or TypeScript/JavaScript.
  • Build, deploy, and operate production-grade services.
  • Hands-on experience with agent-based AI solutions using LangChain, LangGraph, or comparable frameworks.
  • Practical experience with MCP servers and developing custom skills, tools, integrations.
  • Experience using Claude Code for real-world engineering tasks.
  • Knowledge of AI agent architecture, tool calling, orchestration, and workflow automation.
  • Experience integrating AI capabilities into DevOps and software delivery processes.

Responsibilities

  • Design and build AI agents across the full software delivery lifecycle (SDLC).
  • Build agents using coding harnesses, custom skills, tools, and MCP servers.
  • Develop agents on platforms like Devin using LangChain/LangGraph.
  • Choose platforms/frameworks based on enterprise use cases.
  • Implement spec-driven development workflows (Specify Clarify Plan Tasks Analyze Implement).
  • Create technical controls for gates (Spec Ready, PR Ready).
  • Evaluate frontier AI models and coding harnesses (e.g., Claude Code).
  • Develop reusable AI capabilities across multiple teams.
  • Collaborate with DevOps, security, and platform teams to deploy agents safely.
  • Maintain and contribute to enterprise skill/tool catalogs.

Skills

Python/TypeScript
Agent-based AI
LangChain/LangGraph
MCP servers
Claude Code
AI architecture
DevOps integration
Production-grade services

Job description

AI Platform Engineer

Location: Halifax, NS
Work Model: Onsite / 4 Days
Job Type: Full Time

Primary Skills

Agentic AI, Python/TypeScript, LangChain/LangGraph & MCP

Job Description

We are seeking a hands-on AI Platform Engineer to help build and scale an agentic AI platform that enables development teams to execute AI-driven Software Development Lifecycle (SDLC) workflows at enterprise scale.

This role sits within DevOps and Platform Engineering and focuses on building the harnesses, skills, tools, and AI agents that power development workflows across the organization. The ideal candidate will have strong software engineering experience along with practical expertise in agentic AI, coding assistants, MCP servers, and AI agent frameworks.

Key Responsibilities
  • Design and build AI agents across the full software delivery lifecycle, including:
    • Specification creation
    • Technical specification generation
    • Build and test
    • Deployment and release
    • Post-Implementation Verification (PIV)
    • Post-deployment operations
  • Build agents using coding harnesses, custom skills, tools, and MCP (Model Context Protocol) servers.
  • Develop agents on managed platforms such as Devin and using frameworks such as LangChain and LangGraph.
  • Select the appropriate platform, framework, or technology based on individual use cases and enterprise requirements.
  • Implement and extend spec-driven development workflows, such as Specify Clarify Plan Tasks Analyze Implement, using approaches similar to GitHub Spec Kit.
  • Build technical controls that enforce AI-driven development lifecycle gates, such as Spec Ready and PR Ready, as machine-checked controls.
  • Continuously evaluate and expand the capabilities of frontier AI models and coding harnesses such as Claude Code.
  • Develop reusable AI capabilities that can improve engineering productivity across multiple development teams.
  • Partner with DevOps, security, and platform teams to safely deploy new agents, skills, and tools into production.
  • Maintain and contribute to shared enterprise skill and tool catalogs.
  • Evaluate emerging agentic AI platforms, frameworks, and architectural patterns and provide build-vs-adopt recommendations.
  • Demonstrate newly developed agents and platform capabilities to development teams and explain their underlying technical implementation.
  • Support teams adopting AI-driven development practices by providing hands-on technical guidance and troubleshooting.
  • Help establish scalable, secure, and reliable patterns for enterprise AI agent adoption.
Required Skills & Experience
  • Strong software development background using Python and/or TypeScript/JavaScript.
  • Ability to build, deploy, and operate production-grade services, not just prototypes.
  • Hands‑on experience building agent-based AI solutions using LangChain, LangGraph, or comparable agent frameworks.
  • Practical experience with MCP servers and developing custom skills, tools, and integrations for AI coding environments.
  • Demonstrated experience using frontier coding assistants such as Claude Code for real‑world engineering work.
  • Experience developing reusable tools and automation for software development workflows.
  • Strong understanding of AI agent architecture, tool calling, orchestration, and workflow automation.
  • Experience integrating AI capabilities into DevOps and software delivery processes.
  • Strong problem‑solving and engineering skills with the ability to work across platform, security, and development teams.
Preferred Skills
  • Experience with spec-driven development methodologies and AI‑assisted SDLC.
  • Experience with managed agent platforms such as Devin.
  • Knowledge of enterprise DevOps, CI/CD, cloud platforms, and platform engineering.
  • Experience implementing governance, security, and automated quality gates for AI‑driven workflows.
  • Experience evaluating emerging AI technologies and making technical build‑vs‑buy decisions.
  • Strong communication skills with the ability to demonstrate and explain complex AI engineering solutions to technical teams.
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