Staff Engineer, Interactive Voice Response - AI/ML

Geico Insurance•Chevy Chase, MD

55d•$115,000 - $230,000

About The Position

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers. Our Service Engineering team at GEICO is revolutionizing customer service using AI and multi-agent systems. If you're passionate about creating large-scale, distributed AI applications with significant business impact, this opportunity is perfect for you. Our focus is on enhancing self-service rates across all communication channels, from voice (IVR) to chat. Our Staff Engineer is a lead member of the engineering staff working across the organization to provide a friction-less experience to our customers and maintain the highest standards of protection and availability. Our team thrives and succeeds in delivering high-quality technology products and services in a hyper-growth environment where priorities shift quickly. The ideal candidate has broad and deep technical knowledge, typically ranging from front-end UIs through back-end systems and all points in between.

Requirements

Hands-on proficiency with modern AI/ML frameworks and tools (e.g., TensorFlow, PyTorch) and programming languages such as Python, Java, or C++.
Proven experience designing, developing, and deploying AI or machine learning models(LLMs) in production environments, with a focus on scalability and performance.
Strong software engineering background with expertise in building large-scale distributed systems, preferably in cloud environment (Azure or AWS).
Demonstrated ability to apply AI/ML solutions to real-world business problems, delivering measurable impact in areas such as natural language processing, speech recognition, recommendation systems, or intelligent automation.
Experience in building products using micro-services oriented architecture and extensible REST APIs
Experience building the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems
Experience with continuous delivery and infrastructure as code
Experience in leveraging PowerShell scripting
Experience in existing Operational Portals such as Azure Portal
Experience with application monitoring tools and performance assessments.
Ability to excel in a fast-paced, startup-like environment
Knowledge of developer tooling across the software development life cycle (task management, source code, building, deployment, operations, real-time communication)
6+ years of professional software development experience within a Python or Java framework (J2EE, web containers and Java)
4+ years of experience in open-source frameworks
3+ years of experience with architecture and design
3+ years of experience with AWS, GCP, Azure, or another cloud service
Bachelor's degree in Computer Science, Information Systems, or equivalent education or work experience

Responsibilities

Design, develop, and deploy large-scale distributed AI applications that power customer self-service across multiple communication channels (voice, IVR, chat).
Build and optimize multi-agent systems that enable intelligent, collaborative decision-making to improve automation and customer experience.
Collaborate with cross-functional teams (engineering, product, data science) to translate business requirements into scalable AI/ML solutions.
Ensure system reliability, scalability, and performance through best practices in architecture, testing, and monitoring.
Stay at the forefront of AI and distributed systems research, brining innovative approaches and tools into production environment.
Utilize programming languages like Python, SQL, and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of Azure tools and services
Consistently share best practices and improve processes within and across teams

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