Software Engineer, AI

Why you'll love Softchoice

At Softchoice, a World Wide Technology (WWT) company, we work together to make a new world happen. As an IT solutions provider serving U.S. commercial and SMB organizations, as well as the entire Canadian market, we help organizations turn ambition into realworld outcomes. We do this through the delivery of secure cloud, AI, software and digital workplace solutions that enable agility, innovation and growth.

With a highly engaged, high-performing team, we are certified as a Great Place to Work in both Canada and the United States, and have been recognized as a Best Workplace in Canada for more than 20 years. We stand proudly for our people and their success through career development and advancement, and continuously strive to do what's good for our people and communities.

As part of WWT, we connect customers to the global scale, advanced innovation, world-class partnerships, and deep expertise of a leader in AI and digital transformation. This includes access to WWT's Advanced Technology Center (ATC), a collaborative ecosystem featuring state-of-the-art hardware and software that enables customers and partners to conceptualize, test, and validate innovative solutions before deploying them at scale.

The impact you will have

Softchoice is on a mission to help our clients unleash the power of AI and cloud-native software. We are hiring a Software Engineer, AI to play a key role in designing and delivering AI-driven solutions that empower businesses with intelligent automation, data-driven insights, and next-generation software applications.

In this intermediate-level role, you will independently deliver complex components and defined technical workstreams from design through deployment and operational support, while working within an overall solution architecture established with senior engineers and architects. You will translate business requirements into secure, scalable, and supportable software and help move AI concepts and proofs of concept into production.

What you'll do

• Design, build, test, deploy, and support production-ready AI applications and defined technical workstreams, with architectural guidance on broader solution decisions.
• Translate customer and business requirements into component designs, implementation plans, estimates, acceptance criteria, and technical trade-offs.
• Develop AI solutions using LLMs, RAG, semantic search, document/data processing, and agentic workflows.
• Build secure backend services, APIs, integrations, and cloud-native components that connect AI applications with enterprise systems and data sources.
• Design and optimize ingestion, chunking, embeddings, retrieval, prompting, grounding, tool use, memory, and workflow orchestration.
• Evaluate models, platforms, and solution approaches based on quality, latency, cost, scalability, security, privacy, and operational requirements.
• Productionize AI solutions through automated testing, resiliency, observability, performance optimization, evaluation, monitoring, and responsible AI controls.
• Contribute to CI/CD, infrastructure-as-code, containerized/serverless deployments, and MLOps/LLMOps practices.
• Participate in architecture, design, and code reviews; create reusable components; improve engineering standards; and produce technical documentation and runbooks.
• Collaborate with customers, architects, engineers, data teams, and business stakeholders through discovery, technical design, demonstrations, estimates, and knowledge transfer.

What you'll bring to the table

• Typically 4-6 years of software engineering experience, including at least 2 years developing AI, machine learning, or generative AI solutions.
• Proven experience delivering production-grade applications or AI capabilities beyond proof-of-concept.
• Strong Python development skills and experience with at least one additional language such as TypeScript/JavaScript, Java, C#, or Go.
• Experience building backend services, APIs, integrations, databases, authentication/authorization, and asynchronous or event-driven applications.
• Hands‑on experience with Azure, AWS, or Google Cloud and modern AI platforms such as Azure AI Foundry, Amazon Bedrock, Vertex AI, OpenAI, Anthropic, or open-source models.
• Practical experience with LLM applications, RAG, embeddings, vector search, prompt engineering, AI agents/tool integration, evaluation, and structured or unstructured data pipelines.
• Experience developing modern web applications using frameworks such as React or Next.js.
• Solid understanding of software architecture, secure development, responsible AI, and component-level technical design.
• Experience using AI-assisted engineering tools such as GitHub Copilot, Cursor, or Claude Code to accelera