AI Solutions Developer

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.

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 operational handoffs. Business Requirements and Solution Design: Translate business needs into detailed technical specifications, assess feasibility, define project scopes and success criteria, and communicate technical risks, dependencies, and trade-offs to stakeholders. Cross-Functional Collaboration: Partner with subject matter experts, IT teams, and AI platform specialists to validate technical solutions, ensure content accuracy, improve usability, and align applications with business objectives. Innovation and Continuous Improvement: Research emerging LLMs, agentic frameworks, and AI technologies; prototype promising solutions; and identify opportunities to consolidate applications, reduce manual work, and improve measurable business outcomes. Requirements Education: Bachelor's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related quantitative discipline. A master's degree is an asset. Professional Experience: Three to five years of relevant experience in AI/ML, data science, software engineering, or a related field, with a demonstrated track record of building and deploying intelligent systems or automation solutions. Python Development: Strong proficiency in Python, including experience with pandas and asynchronous programming. Frontend Development: Working knowledge of JavaScript or TypeScript for building user-facing applications. AI Agents and LLMs: Hands-on experience developing multistep agentic workflows using code-first frameworks such as LangChain, AutoGen, or CrewAI, and integrating LLM APIs from providers such as OpenAI, Google Gemini, and Anthropic. RAG and Vector Databases: Practical experience designing RAG pipelines and working with PostgreSQL and pgvector, vector databases such as Pinecone or Weaviate, or search libraries such as FAISS. Cloud and Application Deployment: Experience deploying applications in Google Cloud, particularly Vertex AI and Cloud Functions, with familiarity with Azure or AWS considered beneficial. Software Engineering Practices: Solid understanding of Git, automated testing, CI/CD, RESTful API development, secure coding, and maintainable software architecture. Data and Knowledge Management: Ability to design reliable content ingestion and synchronization processes that keep connected knowledge sources accurate, current, and appropriately accessible. Security and Governance: Understanding of authentication, access control, data privacy, responsible AI practices, and the risks associated with deploying LLM-powered applications. Problem-Solving Skills: Ability to assess technical feasibility, troubleshoot complex issues, compare implementation options, and balance solution quality with development time and operating costs. Communication and Collaboration: Strong written and verbal communication skills, with the ability to explain technical concepts, limitations, risks, and trade-offs to nontechnical stakeholders. Ownership and Adaptability: A proactive, independent approach to taking solutions from initial concept through production deployment and ongoing maintenance, along with a willingness to learn and adapt to a rapidly evolving AI landscape. Additional Assets: Professional certifications in Google Cloud, Azure, AWS, or AI technologies, as well as experience with speech technologies, interactive avatars, and multilingual AI applications. Candidates who do not meet every listed qualification but have relevant experience and a strong interest in building practical AI solutions are encouraged to apply. Benefits Competitive Compensation: Annual base salary ranging from CAD $85,500 to $105,600 , depending on qualifications, experience, skills, and work location. Flexible Work Arrangements: Remote work opportunities, with workplace expectations and any in-person requirements discussed during the recruitment process. Home Office Support: A home office reimbursement program to support a productive remote working environment. Comprehensive Healthcare: Competitive medical and dental benefits. Retirement Savings: Access to a retirement savings program. Parental Support: Baby bonus and parental leave top-up programs. Professional Development: Online learning opportunities, professional networking, and resources to support continued growth. Sustainable Mobility Incentive: An electric vehicle purchase incentive program. Innovative Technology Environment: Opportunities to work with modern AI technologies, cloud infrastructure, and intelligent automation solutions. Collaborative Culture: A diverse and inclusive workplace that values innovation, teamwork, continuous improvement, and meaningful contributions. Career Growth: The opportunity to expand your technical expertise while developing AI solutions that deliver measurable business impact.