1 day ago
Bethesda, MD, USA +2 moreStaff+
Base Salary
$115k - $230k/yr
Responsibilities
- Identify and evaluate opportunities to automate business processes with AI, intelligent workflows, and agent-based systems.
- Architect, build, deploy, and operate applied AI solutions for automation, document intelligence, decision support, and intelligent assistants.
- Design AI agents and agentic workflows that orchestrate tools, APIs, reasoning steps, and business logic.
- Build scalable, resilient, performant, secure, and highly available production systems.
- Use knowledge graphs to improve reasoning, entity relationships, context retrieval, and multi-step workflows.
- Collaborate with product, engineering, operations, analytics, and domain partners to translate business needs into technical designs.
- Mentor engineers and scientists through coaching, pairing, reviews, and architectural guidance.
- Explore models, frameworks, and reasoning techniques and apply them to real-world challenges.
- Provide technical leadership on architecture, experimentation, and deployment across multiple teams.
- Conduct experimentation and evaluation through hypothesis definition, measurement, validation, and production improvement.
- Establish engineering practices for reliability, interpretability, safety, governance, and monitoring of production AI systems.
Requirements
- At least 8 years of professional software engineering or applied machine learning experience, including at least 2 years working with generative AI or LLM-based systems in production.
- Strong hands-on experience with Python and AI frameworks and APIs including LangChain, LangGraph, LangSmith, LlamaIndex, Hugging Face, OpenAI, and Anthropic.
- Experience designing, building, and operating production AI systems, agentic workflows, and intelligent automation features.
- Experience building scalable, resilient, secure, maintainable products and systems that operate reliably in production.
- Strong understanding of agent architectures, workflow orchestration, retrieval-augmented generation, vector databases, and knowledge graph integration.
- Ability to collaborate across teams and co-create solutions with engineers, product managers, and domain experts.
- Experience mentoring engineers and helping others develop AI, LLM, and agent-based system design skills.
- History of delivering measurable business outcomes from AI systems.
- Strong competency in distributed systems, service design, performance optimization, and reliability engineering.
- Preferred experience with domain-tuned LLMs, vector reasoning techniques, or specialized retrieval architectures.
- Preferred experience in insurance, financial services, or other regulated industries.
- Preferred experience deploying AI components in Java ecosystems using Spring AI, LangChain4j, or Embabel.
- Preferred background in document intelligence, fraud or anomaly modeling, or ontology and knowledge graph design.
- Familiarity with AI safety practices, evaluation frameworks, monitoring, and regulatory compliance.
- Ability to communicate complex technical topics to senior leadership and non-technical stakeholders.
Benefits
- Personalized development programs, mentorship, and certification assistance.
- Inclusive and collaborative culture rooted in shared success.
- Benefits and flexibility intended to support employee well-being and future needs.
Categories
About GEICO
GEICO sells auto and other personal lines insurance to U.S. consumers through a primarily direct-to-consumer model via web, mobile, and phone, with some local agents. Its products include car, motorcycle, RV, boat, homeowners, renters, condo, umbrella, and commercial auto coverage, plus roadside assistance. Founded in 1936 and headquartered in Bethesda, Maryland, GEICO is a subsidiary of Berkshire Hathaway and is among the largest auto insurers in the United States.