AI Software Engineer - Cloud-Native Apps & Production AI

Softchoice; Calgary; On-site; CAD 91,000 - 114,000; Full time

Benefits offered by this job

Health benefits

RRSP matching

Paid time off

Job summary

Softchoice, a World Wide Technology company, is seeking an experienced Software Engineer, AI to design and deliver AI‑driven solutions for enterprise clients in Canada. You will independently deliver complex components within an overall solution architecture and translate business requirements into scalable software.

You will build secure backend services, APIs, and data pipelines, evaluate models and platforms, and contribute to MLOps, CI/CD, and observability to productionize AI solutions.

Qualifications

• 4–6 years of software engineering experience, with 2+ years in AI/ML or generative AI.
• Production‑grade applications or AI capabilities experience beyond PoC.
• Proficient Python and at least one other language (TypeScript/JavaScript, Java, C#, or Go).
• Experience building backend services, APIs, databases, and cloud integrations.
• Hands‑on with Azure, AWS, or Google Cloud and modern AI platforms.

Responsibilities

• Design, build, test, deploy, and support production‑ready AI applications and workstreams.
• Translate requirements into designs, plans, estimates, and criteria.
• Develop AI solutions using LLMs, RAG, embeddings, and agent workflows.
• Build secure backend services, APIs, and cloud‑native components connecting AI apps to data sources.
• Contribute to CI/CD, IaC, containers/serverless, and MLOps/LLMOps.

Skills

Python

TypeScript/JavaScript

Cloud platforms

LLMs

GItHub Copilot

Tools

Docker

Kubernetes

GitHub Copilot

Job description

Softchoice, a World Wide Technology company, is seeking an experienced Software Engineer, AI to design and deliver AI‑driven solutions for enterprise clients in Canada. You will independently deliver complex components within an overall solution architecture and translate business requirements into scalable software.

You will build secure backend services, APIs, and data pipelines, evaluate models and platforms, and contribute to MLOps, CI/CD, and observability to productionize AI solutions.