Posted 22 days ago
Applied AI Engineer
@ Astek
Montréal, Quebec
Overview
Astek is hiring an Applied AI Engineer on a full-time basis to build Generative AI applications, AI assistants, agents and intelligent automation solutions. The work involves developing prototypes, integrating AI with enterprise systems and APIs, and translating business requirements into working software. The posting requires 3 to 5 years of software engineering experience and 1 to 3 years building GenAI applications.
Responsibilities:
- Build generative AI applications, agents and copilots
- Integrate AI solutions with APIs and enterprise platforms
- Develop proofs of concept and reference implementations
- Test and evaluate AI solution quality, safety and reliability
- Translate business requirements into working software with stakeholders
Requirements summary:
- 3 to 5 years of software engineering experience
- 1 to 3 years of GenAI application development
- Proficiency in Python and API integration
- Experience with LLM frameworks such as LangChain or LangGraph
- Familiarity with GitHub, CI/CD and containers
- Familiarity with Azure or AWS
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-10-20
- First seen by our source
- 2026-11-11
- Source record updated
- 2026-11-11
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office, Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Astek
| Field | Value |
|---|---|
| Open jobs on Jobsy | 39 |
Required Qualifications
- 3 to 5 years of software engineering experience with hands-on application development responsibilities.
- 1 to 3 years of practical experience developing Generative AI applications, AI assistants, AI agents, copilots, or intelligent automation solutions.
- Proficiency in Python and experience building APIs, integrations, and enterprise applications.
- Working knowledge of Large Language Models (LLMs), prompt engineering, embeddings, vector databases, semantic search, Retrieval-Augmented Generation (RAG), and common AI application patterns.
- Hands-on experience with one or more AI development frameworks, such as LangGraph, LangChain, Claude Code SDK, OpenAI SDK, or similar technologies.
- Familiarity with Model Context Protocol (MCP), AI gateways, agent-to-agent communication, or tool-calling frameworks.
- Experience implementing AI agents, orchestration workflows, tool integrations, or agentic applications.
- Experience building proofs of concept, prototypes, or reference implementations.
- Experience integrating applications with enterprise systems, data platforms, and APIs.
- Familiarity with automated testing and evaluation approaches for AI solution quality, safety, reliability, and performance.
- Awareness of Responsible AI principles, AI governance, security controls, and enterprise data protection requirements.
- Experience with GitHub, CI/CD pipelines, containers, and modern software engineering practices.
- Familiarity with Azure or AWS services used to host and operate applications and AI workloads.
- Ability to work with business stakeholders and application development teams to translate requirements into working software.
- Strong communication, collaboration, and problem-solving skills.
Preferred Qualifications
- Experience with Azure AI Foundry, AWS Bedrock, Anthropic Claude, OpenAI GPT models, SpaceX Grok Models, Gemini, or similar enterprise AI platforms.
- Experience building RAG solutions, knowledge assistants, or AI-powered search capabilities.
- Exposure to multi-agent systems and agent orchestration workflows.
- Experience integrating applications with ServiceNow, Jira, Confluence, SharePoint, Microsoft Graph, Databricks, Snowflake, or similar enterprise platforms.
- Familiarity with Kubernetes, containerized application deployment, and cloud-native architectures.
- Experience working in financial services or another regulated industry.
Journal
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