Solving enterprises' most complex software engineering challenges.
Senior AI Solution Architect
Location
United States
Posted
60 days ago
Salary
0
Seniority
Senior
Job Description
Senior AI Solution Architect
Janea Systems
• Design scalable architectures for machine learning platforms, AI services, and data processing pipelines. • Define system-level architectures that integrate machine learning models into distributed production systems. • Ensure high availability, scalability, and performance of ML-powered applications. • Architect end-to-end ML pipelines including data ingestion, feature engineering, training workflows, model serving, and monitoring. • Design ML infrastructure capable of supporting experimentation, training, and large-scale inference. • Guide teams in implementing modern MLOps practices across projects. • Provide architectural leadership to engineering teams implementing ML-enabled systems. • Establish best practices for system design, model integration, observability, and reliability. • Conduct architecture reviews and mentor engineers on building scalable ML-driven software systems. • Work closely with ML engineers, backend engineers, data engineers, and DevOps teams to design cohesive AI solutions. • Partner with client stakeholders to translate complex business requirements into scalable technical architectures. • Help guide technical decisions during project planning and delivery. • Stay current with advancements in machine learning infrastructure, distributed systems, and AI engineering. • Identify opportunities to improve the scalability and efficiency of ML systems across projects. • Contribute to internal knowledge sharing and architectural standards across Janea’s engineering teams.
Job Requirements
- 10+ years of experience in software engineering, distributed systems, or backend architecture.
- 5+ years of experience designing systems that incorporate machine learning or data-driven components.
- Strong experience architecting large-scale, production-grade software systems.
- Deep understanding of machine learning system architecture, model deployment patterns, and ML lifecycle management.
- Strong programming experience in Python, Java, C#, or similar languages.
- Experience designing systems in cloud environments (AWS, Azure, or GCP).
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Strong understanding of data pipelines, distributed systems, and microservices architectures.
- Excellent system design, problem-solving, and technical leadership skills.
- Strong written and spoken English communication skills.
- Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Benefits
- Competitive compensation with benefits, paid vacation, and sick leave.
- The opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges.
- Ultra-flexible working conditions – we provide a generous office equipment allowance so you can work from home, we can also provide you with a desk at an office/coworking facility near you, or use both. No business travel necessary.
- An enjoyable, start-up work environment, with excellent opportunities for professional growth and development.
- Flexible working hours – as a remote-first company, our focus has always been on getting the job done well, not when or where it gets done.
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