Senior Engineer
Tech / AI / Software
SeniorEngineer-AI&ML
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Engineer - AI & ML at Senior Engineer. Skills: AI, Machine Learning, AI platform architecture, Cloud infrastructure, AI driven engineering innovation, MLOps. Lead the architecture and engineering of the enterprise AI and ML platform supporting model development, training, deployment, and monitoring. Define scalable infrastructure patterns for AI workloads including batch and real time inference environments”
Industry & Context.
systems architecture and problem-solving skills
What They're Looking For.
Must Have
12 or more years of experience in software engineering, platform engineering, or cloud architecture, expertise in AI and machine learning systems and production ML platforms, Experience designing and operating AI or ML platforms at scale, Deep experience with cloud infrastructure such as AWS and distributed systems, Experience with container orchestration platforms such as Kubernetes, understanding of MLOps practices and ML lifecycle management, Programming experience in languages such as Python, Java, or similar, Experience in AWS cloud, Experience working closely with data science teams to operationalize machine learning models
Nice to Have
Experience with large scale data processing platforms and AI training environments, Experience deploying real time and batch AI inference systems, Familiarity with generative AI, LLM based systems, or modern AI platforms, Experience in Building solution using AI Native Development Lifecycle, Experience building internal AI platforms or developer platforms supporting ML workflows
What You'll Do.
Lead the architecture and engineering of the enterprise AI and ML platform supporting model development
Define scalable infrastructure patterns for AI workloads including batch and real time inference environments
Establish best practices for ML lifecycle management including model versioning
Build and evolve infrastructure supporting large scale data processing and AI model experimentation
Promote the adoption of AI driven engineering practices across development and platform teams
Enable integration of generative AI
machine learning models
and intelligent automation into platform capabilities
Evaluate emerging AI technologies and identify opportunities to incorporate them into the enterprise platform
Design and implement scalable cloud infrastructure to support AI and data intensive workloads
Design and standardize MLOps frameworks for training
and monitoring machine learning models
Establish monitoring and observability for AI models
and platform services
Ensure AI platform infrastructure Security
How You'll Work.
Team & Collaboration
working closely with data science teams; technical influence across engineering teams; Mentor engineers and data scientists on best practices for building scalable AI systems; Drive architectural consistency and engineering standards across teams
Process & Methodology
Lead complex technical initiatives involving AI platforms, cloud infrastructure, and data systems
Full Job Description
We are looking for a highly experienced **Senior Engineer with deep expertise in AI and Machine Learning platforms** to lead the architecture and engineering of our enterprise AI infrastructure. This role will drive the design and scalability of cloud based AI platforms, ML lifecycle systems, and AI driven engineering capabilities across the organization. The Principal Engineer will play a critical role in enabling production grade AI and ML solutions by building the underlying platform, infrastructure, and automation required to support model development, deployment, monitoring, and governance at scale. This is a senior individual contributor role focused on **AI platform architecture, Cloud infrastructure, and AI driven engineering innovation**. **Required Qualifications** * 12 or more years of experience in software engineering, platform engineering, or cloud architecture. * Strong expertise in **AI and machine learning systems and production ML platforms**. * Experience designing and operating **AI or ML platforms at scale**. * Deep experience with cloud infrastructure such as AWS and distributed systems. * Experience with container orchestration platforms such as Kubernetes. * Strong understanding of **MLOps practices and ML lifecycle management**. * Programming experience in languages such as Python, Java, or similar. * Experience in AWS cloud. * Experience working closely with data science teams to operationalize machine learning models. **Preferred Qualifications** * Experience with large scale data processing platforms and AI training environments. Experience deploying real time and batch AI inference systems. Familiarity with generative AI, LLM based systems, or modern AI platforms. * Experience in Building solution using AI Native Development Lifecycle * Experience building internal AI platforms or developer platforms supporting ML workflows. **Key Attributes** * Deep passion for AI and emerging technologies * Strong systems architecture and problem-solvi
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