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About the role
As an Associate Principal AI Engineer at Illumina, you will play a crucial role in translating enterprise strategy into scalable, AI-enabled technology solutions by collaborating with Principal Architects, business stakeholders, and engineering teams. Your responsibilities will include: - Define reference architectures, design patterns, and platform standards for AI-enabled enterprise applications spanning web, mobile, and backend services. - Partner with the Principal Architect to develop multi-year technology roadmaps aligning cloud, data, AI, and application strategy with business objectives. - Evaluate emerging technologies and translate them into actionable adoption plans. - Lead architectural reviews to ensure system designs meet scalability, security, performance, observability, and total cost of ownership requirements. In the field of AI and Generative AI Engineering, you will: - Architect Generative AI solutions such as RAG systems, multi-agent workflows, conversational interfaces, and domain-specific fine-tuned models. - Design responsible AI frameworks covering prompt engineering standards, evaluation pipelines, model governance, and content safety controls. - Establish MLOps and LLMOps practices for model deployment, monitoring, drift detection, and continuous improvement. For Cloud and Platform Engineering, your responsibilities will include: - Designing cloud-native solutions on Azure or AWS, leveraging managed AI services. - Architecting CI/CD pipelines, infrastructure-as-code, and platform automation to accelerate engineering velocity. - Defining and enforcing standards for containerization, microservices, API design, and event-driven architectures. As a leader, you will provide technical guidance to engineering teams, mentor senior engineers, and collaborate with product, design, and business stakeholders to deliver measurable business outcomes. Additionally, your qualifications should include: - 15+ years of progressive experience in software engineering, with at least 5 years in architecture or senior technical leadership roles. - Deep hands-on expertise across full-stack development, including Python and Java ecosystems. - Proven experience in architecting and deploying Generative AI solutions in production. - Strong command of at least one major cloud platform (Azure or AWS). - Experience leading distributed engineering teams across multiple time zones. - Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline. Preferred qualifications include experience with agentic AI frameworks, Voice AI platforms, commerce platforms, and data platforms. Industry certifications and active engagement with the technology community are also valued. At Illumina, we prioritize inclusivity, collaboration, and innovation. We are committed to providing equal employment opportunities and promoting a diverse and empowering work environment. If you require accommodation during the application process, please contact accommodations@illumina.com. As an Associate Principal AI Engineer at Illumina, you will play a crucial role in translating enterprise strategy into scalable, AI-enabled technology solutions by collaborating with Principal Architects, business stakeholders, and engineering teams. Your responsibilities will include: - Define reference architectures, design patterns, and platform standards for AI-enabled enterprise applications spanning web, mobile, and backend services. - Partner with the Principal Architect to develop multi-year technology roadmaps aligning cloud, data, AI, and application strategy with business objectives. - Evaluate emerging technologies and translate them into actionable adoption plans. - Lead architectural reviews to ensure system designs meet scalability, security, performance, observability, and total cost of ownership requirements. In the field of AI and Generative AI Engineering, you will: - Architect Generative AI solutions such as RAG systems, multi-agent workflows, conversational interfaces, and domain-specific fine-tuned models. - Design responsible AI frameworks covering prompt engineering standards, evaluation pipelines, model governance, and content safety controls. - Establish MLOps and LLMOps practices for model deployment, monitoring, drift detection, and continuous improvement. For Cloud and Platform Engineering, your responsibilities will include: - Designing cloud-native solutions on Azure or AWS, leveraging managed AI services. - Architecting CI/CD pipelines, infrastructure-as-code, and platform automation to accelerate engineering velocity. - Defining and enforcing standards for containerization, microservices, API design, and event-driven architectures. As a leader, you will provide technical guidance to engineering teams, mentor senior engineers, and collaborate with product, design, and business stakeholders to deliver measurable business outcomes. Additionally, your qualifications should include: - 15+ years of pro