Senior Specialty Software Engineer – AI Engineering

Role Overview

• Design, enhance, and maintain the Tachyon Predictive Ops (TPOps) self-service MLOps framework, enabling rapid experimentation, training, deployment, and monitoring of AI models.
• Build cloud-native MDLC (Model Development Lifecycle) capabilities including model registry, versioning, lineage, and reproducibility.
• Develop unified libraries, SDKs, and extensible components that accelerate both predictive and generative AI workflows.
• Implement reusable automation patterns for model training, validation, deployment, and governance.
• Contribute to the Unified & Managed Predictive AI Platform, spanning on-premise infrastructure, GCP, and upcoming Azure ML integration.
• Implement real-time and batch inferencing capabilities supporting instant prediction use cases and scheduled batch pipelines.
• Support hybrid AI delivery patterns —predictive ML, GenAI workflows, agentic systems, and multi-agent orchestration.
• Build strategic observability features including drift detection, performance optimization, and open-standards monitoring integrations.
• Collaborate with MLOps, platform engineering, and architecture to ensure compliance with enterprise governance and operational excellence requirements.
• Design and develop scalable APIs and microservices to expose AI capabilities to enterprise applications.
• Implement automation and CI/CD patterns enabling consistent deployments across hybrid compute environments.
• Develop prompt engineering standards and reusable blueprints for LLM-powered developer tools such as Copilot, Devin.AI, and agentic systems.
• Work with data scientists, engineers, and platform teams to integrate AI pipelines and frameworks across the enterprise.
• Provide hands-on guidance to junior engineers on modern AI engineering and platform development patterns.

Requirements

• 4+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years hands-on experience with AI/ML development and modern ML frameworks.
• 2+ years strong programming skills in Python and/or Java.
• 2+ years in building APIs, frameworks, automation pipelines, or distributed systems.
• 2+ years experience with cloud platforms (GCP, Azure, AWS) or on-prem platforms such as Kubernetes or OpenShift.

Tech Stack

• AWS
• Azure
• Cloud
• Distributed Systems
• Google Cloud Platform
• Java
• Kubernetes
• Microservices
• OpenShift
• Python

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement