Sr Staff Engineer - Applied AI

GEICO • Palo Alto, CA

4d • $130,000 - $260,000

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. Senior Staff Engineer, Applied AI About GEICO 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. Role Overview GEICO is seeking a Senior Staff Engineer, Applied AI to provide technical architecture and leadership for medium to large, complex, cross-functional AI initiatives that have visibility at the tech VP level. This is a self-directed, senior individual contributor role for someone with deep technical expertise, proven ability to influence across organizational boundaries, and a track record of delivering scalable, resilient, production-ready AI systems that drive measurable business outcomes. You will provide technical direction and architecture for capabilities spanning multiple teams, working closely with Staff Engineers, engineering leaders, product management, and business stakeholders to design and scale AI-powered solutions. You will actively mentor and sponsor mid-level engineers, set technical standards for AI/ML engineering excellence, and drive adoption of best practices across the organization.

Requirements

• 8 or more years of professional software engineering or applied machine learning experience, including 2 or more years working with Generative AI or LLM-based systems in production
• Proven track record of architecting and delivering complex AI/ML capabilities that span multiple teams and have measurable business impact
• Deep hands-on expertise with Python and modern AI frameworks including LangChain, LangGraph, LangSmith, LlamaIndex, Hugging Face, OpenAI/Anthropic APIs, and emerging agentic frameworks
• Demonstrated experience building and deploying production RAG (Retrieval-Augmented Generation) systems including document ingestion, chunking strategies, vector search, and context retrieval
• Demonstrated experience designing and operating production AI systems including multi-agent architectures, intelligent automation, and workflow orchestration
• Strong understanding of agent architectures, workflow orchestration, retrieval-augmented generation (RAG), vector databases, knowledge graphs, and semantic reasoning
• Familiarity with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) for building interoperable AI systems
• Experience ensuring platform scalability, cross-domain coherence, and alignment with AI platform capabilities and strategy
• Strong expertise in distributed systems, microservices architecture, service design, performance optimization, and reliability engineering
• Proven ability to influence technical direction across multiple teams and build consensus among engineers and engineering leaders
• Track record of mentoring engineers at various levels and helping them develop AI and technical leadership capabilities
• Demonstrated ability to translate business needs into scalable technical solutions and communicate effectively with both technical and non-technical stakeholders
• History of delivering measurable business outcomes from AI systems in production environments

Nice To Haves

• Experience building advanced Generative AI capabilities including domain-tuned LLMs, specialized retrieval architectures, or prompt optimization frameworks
• Experience in knowledge graph design, ontology development, and graph-based reasoning for business domains
• Experience with insurance, financial services, or other highly regulated industries including compliance and risk management
• Experience deploying AI components in Java ecosystems including Spring AI, LangChain4j, or Embabel for enterprise integration
• Background in document intelligence, fraud detection, anomaly modeling, or decision support systems
• Experience with AI safety practices, evaluation frameworks, monitoring, observability, and regulatory compliance
• Experience with MLOps platforms including model training, deployment, and monitoring
• Contributions to open-source projects, technical blogging, or community participation
• Ability to map technical concepts to GEICO's business context and insurance industry specifics

Responsibilities

• Specify architectures and system decompositions for AI/ML capabilities that involve significant integrations and cross-team collaboration across multiple product areas
• Provide technical architecture and leadership for medium to large, complex, cross-functional AI initiatives with visibility at the tech VP level
• Architect and lead implementation of advanced Generative AI solutions including agent-based systems, intelligent automation, document intelligence, and decision support systems that span multiple business domains
• Design and implement sophisticated agentic workflows that orchestrate multiple AI agents, tools, APIs, reasoning steps, and business logic to automate complex enterprise processes at scale
• Question status quo with an eye for simpler designs and more secure approaches, influencing tech VPs to set direction for multiple teams
• Build systems and platforms that meet the highest standards for scalability, resilience, performance, availability, security, and compliance
• Identify and scope opportunities for automating business processes using AI across multiple product areas and business domains
• Advance the state-of-the-art in applied AI by integrating knowledge graphs, vector reasoning, retrieval architectures, and multi-agent systems to solve complex business problems
• Drive innovation by exploring new models, frameworks, reasoning techniques, and AI architectures and applying them strategically to high-impact business challenges
• Run rigorous experimentation programs including hypothesis definition, A/B testing, measurement frameworks, and iterative improvement across production AI systems
• Translate ambiguous business problems into clear technical solutions, working with product and engineering leadership to define roadmaps and priorities
• Serve as principal contributor and approver for design patterns, architectural standards, and best practices for AI/ML systems across multiple teams
• Establish and drive adoption of engineering best practices for reliability, interpretability, safety, governance, monitoring, and responsible AI deployment
• Ensure AI system implementations meet functional and non-functional requirements including security, compliance, data handling, and regulatory standards
• Lead rigorous code reviews, architecture reviews, and design discussions, setting the bar for engineering excellence
• Proactively identify and resolve technical debt, architectural inconsistencies, and scalability issues across AI platform capabilities
• Partner deeply with Staff Engineers, engineering managers, product leaders, and business stakeholders to co-create scalable AI solutions across organizational boundaries
• Influence technical direction across multiple teams by articulating clear vision, building consensus, and demonstrating thought leadership
• Work with tech VPs and senior leadership to align technical strategy with business objectives and communicate complex technical topics in business terms
• Collaborate with engineering leaders to define team structure, hiring needs, and capability development for AI/ML engineering
• Actively mentor and sponsor mid-level engineers (Engineer II through Staff level) who want to develop advanced AI, LLM, and agentic workflow capabilities
• Provide technical guidance and coaching through pairing sessions, architecture reviews, and one-on-one mentorship
• Contribute to community-led organizations including open-source projects and communities of practice within GEICO and the broader industry
• Help other engineers gain technical and non-technical leadership skills needed to progress in their careers
• Foster a culture of continuous learning, curiosity, and innovation across the engineering organization

Benefits

• Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
• Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
• Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
• Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed