AI Architect

Join our Team

As the Company at the forefront of the creation of the Mobile world, and with more than 60,000 patents to our name, we’ve made it our business to make a mark. Being part of Ericsson empowers you to learn, lead, and perform at your best, shaping future technology. Ericsson is an inclusive employer where you are recognized for the skills, talent, and perspective you bring to the team.

Within the Solution Area Cognitive Networks Solutions Software R&D (SA CNS SW R&D), we offer the opportunity to collaborate with highly qualified Global teams and to enable success stories for our customers. You will be exposed to groundbreaking technology (5G, ML/AI, Automation, and Cloud computing) and support the delivery of multiple Data-Intensive projects from our customer base and internal requirements. You must have the ability to perform hands-on Cloud and Data engineering tasks independently, coupled with the appropriate testing. Are you ready to write the future with us?
Come, and be where it begins.

About this opportunity:

Within Cognitive Software Engineering, we offer the opportunity to collaborate with highly qualified teams across the globe and contribute to success stories for our customers. As a SaaS System Architect, you will design and develop scalable and high-performing distributed cloud-based applications.
Your deep understanding of software architecture will be essential in supporting multiple applications and customer scenarios, ensuring a seamless transition from development to production and maintenance. You will work closely with cross-functional teams, including product owners, domain experts, and technical leaders, to ensure reliability, scalability, and architectural excellence across our solutions.

What you will do:

• Translate stakeholders’ visions into comprehensive AI/ML/Generative AI architectural strategies and implementation roadmaps, aligning with business objectives and digital transformation goals.
• Partner with enterprise architects, application architects, data scientists, MLOps engineers, DevOps teams, and business stakeholders to deliver AI-centric SaaS use cases and refine architectural designs.
• Evaluate and select optimal technologies from open-source and commercial options, considering deployment models, cost efficiency, and integration with existing infrastructure.
• Drive the successful execution and continuous improvement of AI-centric applications using agile methodologies.
• Collaborate with security and risk management teams to identify potential risks, promote ethical AI practices, and ensure compliance with relevant regulations.
• Guide project teams through technical reviews, design approvals, and governance processes, maintaining standards for data privacy, security, and regulatory compliance in AI solutions.
• Build and maintain relationships with key stakeholders, contributing to business development efforts such as proposal development.
• Lead and mentor diverse teams in an inclusive environment, recognizing individual contributions and fostering growth.
• Support the development of team members through hands-on guidance and structured training programs.

The skills you bring:

• Bachelor’s degree in computer science, engineering, or a related field.
• 10+ years of experience in software development.
• 3+ years of experience as an AI Architect.
• Track record of working in architecture roles, presenting designs to stakeholders, technical authorities, or review boards.
• Experience building enterprise-integrated solutions that deliver complete end-to-end value.
• Proven expertise in architecture disciplines, including designing scalable and performant AI/ML systems.
• Solid background in data science with deep knowledge of AI/ML concepts.
• Working knowledge of using the current state-of-the-art machine learning frameworks such as Tensorflow, Keras, scikit-learn, Pytorch, etc.
• Hands-on experience deploying cloud-based AI/ML workloads on major platforms (e.g., AWS Bedrock and SageMaker, Google Vertex AI and PaLM, Azure OpenAI and Azure ML) or third-party solutions (e.g., Databricks, Snowflake Snowpark/Cortex, Dataiku, DataRobot).
• Proficiency in architecting cost-optimized, scalable solutions using serverless technologies, Containerization, and Cloud Infrastructure.
• Working knowledge of generative AI, including deployment and hosting of large foundational models.
• Proven expertise in LLM architectures (e.g., Transformers, GANs, VAEs), fine-tuning, Retrieval Augmented Generation (RAG), Context embedding, vector databases, and semantic search tools.
• Strong coding skills in Python for robust AI development and packaging.
• Experience with LangChain and LangGraph frameworks.
• Demonstrated ability to implement MLOps practices for end-to-end model lifecycles (training, testing, monitoring, and iteration).
• Experience with Cloud MLOps platforms (Vertex AI, SageMaker, etc.) and other MLOps platforms: MLFlow, Kubeflow, KServe, Seldon, DVC, CometML, etc.
• Deep understanding and hands-on experience in building Microservices based applications following the API First approach for serving ML models.
• Proficiency with loading data from different data repositories: SQL Databases, Data Warehouses, and Data Lakes.
• Proficiency in classic DevOps, CI/CD practices, and Test Automation.
• Professional certifications in AI/ML technologies on cloud platforms (e.g., AWS, GCP, or Azure).
• AWS certifications like AWS Certified Solutions Architect – Professional, AWS Certified Solutions Architect – Associate, or other relevant certifications would be a strong asset.
• Excellent stakeholder management, cross-functional collaboration, and leadership skills (including coaching, facilitation, and program delivery).
• Strong communication skills to work effectively with multidisciplinary teams.
• Experience contributing to go-to-market activities, such as RFI/RFP responses and proposal development.
• Knowledge of Agile Software Development Methodologies.