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Remote role with broad senior AI and distributed-systems requirements increases applicant pool moderately.
Highly technical and enterprise-product focused skills are transferable, but principal-level product domain experience matters.
Very senior mandatory years and specific LLM, distributed-systems, and cloud expertise make filters strict.
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Engineer AI-enabled features and solutions addressing complex customer issues in core ECM products.
Collaborate with customers, services, and cloud teams to unblock implementation, deployment, and upgrade challenges.
Architect and optimize petabyte-scale distributed systems across multi-cloud platforms with strong focus on security, performance, and AI-driven code quality.
20+ years software engineering experience with 10+ years in architect or principal engineer roles.
Expertise in Java, C#, C++ with systems programming and performance optimization.
3+ years hands-on experience with LLMs and AI integration including prompt engineering and fine-tuning.
Experience designing distributed systems with Spark, Kafka, Kubernetes on AWS, Azure, and GCP environments.
Senior engineer with deep expertise in enterprise AI application and distributed data systems.
Proven track record working with flagship ECM or similarly complex enterprise software products.
Experienced operating at principal or architect level driving AI adoption, security-first architecture, and cloud-native microservices deployment.