AI Solutions Developer

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Solutions Developer based in Canada.** Join an innovative technology environment where artificial intelligence, automation, and connected transportation converge to solve real-world business challenges. As an AI Solutions Developer, you will design, build, deploy, and maintain intelligent applications, AI agents, and automated workflows that improve business operations and team productivity. You will develop production-ready solutions using Python, large language models (LLMs), retrieval-augmented generation (RAG), and modern cloud technologies. Your work will support sales enablement, employee learning, customer education, and operational efficiency through secure, scalable, and user-friendly AI tools. Working closely with technical teams and business specialists, you will transform complex requirements into practical applications with measurable business value. You will also help establish engineering standards, implement responsible AI safeguards, and optimize the performance, reliability, and cost of deployed solutions. This remote opportunity is ideal for a hands-on developer who enjoys experimentation, continuous learning, and delivering impactful AI solutions in a fast-evolving industry. ### Accountabilities - AI Application Development: Design, develop, and deploy custom AI agents, intelligent applications, and automated workflows using Python and frameworks such as LangChain, AutoGen, or CrewAI. - Backend Engineering: Build and maintain backend services, microservices, and supporting logic to ensure AI applications are scalable, reliable, and highly available. - RAG Systems and Knowledge Integration: Develop retrieval-augmented generation pipelines connecting LLMs to proprietary information using PostgreSQL with pgvector and vector databases such as Pinecone, Weaviate, and FAISS. - Full-Stack Development: Create end-to-end AI applications with intuitive user interfaces, robust backend functionality, and secure integrations for internal and external users. - Workflow Automation: Build self-service tools and intelligent workflows that automate repetitive tasks, streamline content creation, support localization, and improve training and sales enablement processes. - API Development and Integration: Design secure RESTful APIs and integrate AI solutions with business applications, learning platforms, sales enablement systems, knowledge repositories, and third-party services. - Conversational AI Capabilities: Implement conversation management, context retention, structured outputs, and tool calling to support interactive guidance and multistep workflows. Evaluate emerging capabilities in speech recognition, speech generation, interactive avatars, and multilingual applications. - Cloud Infrastructure and Deployment: Deploy and operate AI solutions using cloud services such as Google Cloud Vertex AI, Cloud Functions, Microsoft Azure, and AWS, aligning with established infrastructure and technology standards. - Security and Responsible AI: Implement authentication, authorization, role-based access controls, data privacy safeguards, and protections against prompt injection, unauthorized access, and unintended actions. Maintain appropriate separation of internal, partner, and customer information. - Engineering Excellence: Establish and maintain CI/CD pipelines, automated testing, version control, code reviews, reusable libraries, API wrappers, and standardized development practices. - AI Evaluation and Performance Optimization: Develop evaluation frameworks to measure answer accuracy, retrieval quality, relevance, and appropriate handling of unsupported requests. Monitor latency, token consumption, error rates, and operating costs to improve reliability and efficiency. - Maintenance and Documentation: Monitor deployed applications, troubleshoot issues, deliver updates, and document deployment procedures, support requirements, and