APPLIED AI SOFTWARE DESIGNER

Join our Team At this time, Ericsson Canada Inc. does not provide immigration assistance/sponsorship now or in the future for this position. About the Opportunity At Ericsson, we are transforming how large-scale software systems are understood, designed, developed, tested, and maintained through Generative AI and agentic software engineering. We are seeking an Applied AI Software Designer with 2–4 years of software engineering experience and hands-on experience applying AI to developer workflows. You will use Large Language Models (LLMs), AI agents, knowledge systems, and software-analysis tools to enable agentic design and development across large, complex existing codebases. You will build practical AI-driven engineering solutions, reusable tools, and knowledge foundations that improve developer productivity, software quality, and engineering efficiency across Ericsson's 5G/6G systems. Working closely with software developers, architects, AI specialists, and domain experts, you will help turn emerging AI capabilities into reliable, secure, and reusable engineering solutions.   What you will do: Agentic Software Engineering & Code Understanding ·    Design and develop agentic workflows covering feature design, code implementation, debugging, test generation, code review, refactoring, documentation, and impact analysis. ·    Build RAG, context engineering, and knowledge engineering solutions that provide agents with relevant source code, architecture, requirements, documentation, and domain knowledge. ·    Combine LLM-based reasoning with deterministic software analysis, including code indexing, dependency analysis, call relationships, static analysis, and code graphs. ·    Integrate coding agents with source control, CI/CD pipelines, testing environments, APIs, and engineering knowledge sources using tool calling, MCP, and specialized agents where appropriate. ·    Develop validation approaches for AI-generated code and engineering outputs, addressing correctness, grounding, traceability, and reliability. ·    Identify high-value engineering use cases, prototype solutions, evaluate their impact on development efficiency and quality, and productionize successful approaches. ·    Measure the usability, adoption, and impact of these solutions on development efficiency and software quality.   AI Developer Tools and Reusable Engineering Foundations ·       Develop reusable AI tools, components, agent workflows, and integration patterns that can be adopted across multiple engineering teams. ·       Integrate AI capabilities into developer environments, coding assistants, repositories, and existing engineering workflows. ·       Contribute to the development of AI-enabled developer platforms, tool registries, knowledge services, and agentic development environments. ·       Identify opportunities to improve software reuse, reduce duplicated engineering effort, and standardize effective AI-assisted development practices. ·       Apply these capabilities to large-scale C/C++ and Python systems, considering complex architectures, interfaces, dependencies, and cross-component interactions. Quality, Security and Responsible AI Engineering ·       Develop repeatable benchmarks and evaluation methods to assess AI agent accuracy, reliability, and effectiveness across representative engineering tasks. ·       Analyze agent failures and knowledge gaps, and improve context, retrieval, tools, and workflows through iterative experimentation. ·       Integrate appropriate security, access-control, data-protection, intellectual-property, and compliance considerations into AI-enabled engineering workflows. .  ·      Apply software quality practices, automated testing, and CI/CD integration to validate AI-generated outputs and maintain reliable engineering solutions. ·       Contribute to reusable standards and guardrails that support safe, consistent, and responsible AI adoption.     Collaboration, Adoption and Continuous Improvement ·       Collaborate with developers, architects, AI specialists, and domain experts to identify high-value use cases and translate engineering needs into practical solutions. ·       Evaluate and measure the impact of AI-driven workflows on development productivity, software quality, engineering effort, and developer experience. ·       Gather feedback from users and continuously improve the usability, reliability, and adoption of AI-enabled tools. ·       Contribute to the design and development of AI-native applications for 5G/6G systems.   The skills you bring: ·    Bachelor's or Master's degree in Computer Science, Software Engineering, Electrical Engineering, AI/ML, or a related technical field. ·    2–5 years of software engineering experience developing embedded software for wireless Layer 2 (L2) protocol stacks in 3GPP-based cellular systems, particularly 5G/6G baseband platforms. ·    Strong programming skills in C/C++ and Python. ·    Practical experience with RAG, context engineering, or knowledge engineering for AI-assisted development. ·    Strong software engineering fundamentals, including architecture, code design, testing, debugging, version control, CI/CD, and code review. ·    Strong analytical, problem-solving, communication, and collaboration skills. ·    Hands-on experience building and integrating agentic workflows for software engineering. ·    Experience deploying and supporting AI-enabled tools in production engineering environments. ·    Experience evaluating coding agents and LLM-generated outputs for correctness, reliability, and task completion. ·    Knowledge of telecommunications, RAN, 5G/6G is an asset. ·    Familiarity with 3GPP specifications relevant to 5G NR and RAN software development. ·    2–5 years of software engineering experience developing embedded software for wireless Layer 2 (L2) protocol stacks in 3GPP-based cellular systems, particularly 5G/6G baseband platforms   What We Offer ·    Opportunity to shape how AI and coding agents are used in large-scale production software engineering. ·    Hands-on work with real engineering challenges that go beyond standalone code generation, including architecture, dependencies, design intent, and domain knowledge. ·    Collaboration with experienced engineers, architects, AI specialists, and global R&D teams. ·    Exposure to telecom software platforms and emerging 5G and 6G systems. ·    Continuous learning and long-term career development in applied AI, agentic engineering, software architecture, and developer tooling.   Why Join Us Help bring agentic software engineering into real-world development at scale. If you are passionate about applying AI to the challenges of understanding and evolving complex software, we encourage you to join our team.   Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.   What happens once you apply? Click Here  to find all you need to know about what our typical hiring process looks like.   Ericsson uses a merit-based hiring approach that values people with different experiences, perspectives and skillsets. We truly believe this approach drives innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team.  Ericsson is proud to be an Equal Opportunity employer,  learn more.   If you need assistance or to request an accommodation due to a disability, please contact Ericsson at hr.direct.americas@ericsson.com.    DISCLAIMER: The above statements are intended to describe the general nature and level of work bei