Distinguished Engineer, AI Applications

GEICO

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Palo Alto, CANew York, NYSeattle, WA
Salary: $210,000–$350,000 / yr
Employment: Full-time
Posted: 54 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $208k

This role $280k

$133k $373k

below market most similar roles pay here above market

This role pays more than 80% of similar roles. Most pay $162,000–$254,943 — the blue band above. At the midpoint, this role pays about $280k versus about $208k for comparable roles.

Based on 240 similar postings.

Employer

About GEICO

GEICO (Government Employees Insurance Company) is one of the largest auto insurers in the United States, offering affordable auto, home, renters, and other personal insurance products. Industry: Insurance

GEICO currently has 73 open roles on FindRole.

Listed pay typically runs $115,000–$230,000 across 70 roles with salary data.

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View all roles at GEICO

At a glance

TL;DR · Distinguished Engineer, AI Applications

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JOB TITLE: Distinguished Engineer, AI Applications The Distinguished Engineer, AI Applications joins the AI organization to serve as a senior technical authority driving the architecture and long-term strategy for Generative AI and virtual agent platforms. This role involves defining foundational architectures for agentic workflows, knowledge curation, and retrieval systems to support contact center productivity across claims, service, and sales. Key responsibilities include establishing multi-year technical roadmaps, evaluating build versus buy tradeoffs, and mentoring senior engineers. The position requires expertise in LLM orchestration using LangChain and LlamaIndex, RAG architectures, and vector databases like Pinecone or Milvus. Candidates must demonstrate proficiency with Elasticsearch, Snowflake, Kafka, Spark, and Ray, while managing production systems on AWS or Azure using Kubernetes and CI/CD to solve complex scalability and reliability challenges in a production-grade environment.

What does a Engineer earn in California?

Median $199500 from 103 postings across 31 companies.

See salary data

Skills

Generative AI LLM RAG LangChain LlamaIndex AWS Azure Kubernetes CI/CD Kafka Spark Ray Airflow Temporal Prefect Elasticsearch Qdrant Milvus Pinecone Weaviate Snowflake NoSQL OpenTelemetry LangSmith Arize Phoenix Weights & Biases Distributed Systems

What you'll do

Define and evolve the foundational architecture for Generative AI and agentic workflow platforms.
Serve as the final technical authority on complex architectural decisions impacting multiple business domains.
Design high-performance components for knowledge curation, search retrieval, and workflow orchestration.
Establish multi-year technical strategies and roadmaps for AI platform capabilities and GenAI applications.
Evaluate and select core technologies including LLM orchestration frameworks, RAG systems, and observability tools.
Translate complex technical concepts into architectural guidance and decision frameworks for cross-functional teams.
Lead deep technical reviews and architectural assessments for critical AI and GenAI initiatives.
Mentor senior engineers on architectural thinking, engineering quality, and technical decision-making.

What we're looking for

Master’s degree or higher in Computer Science, Engineering, Statistics, or a related field.
10+ years of professional software engineering experience with deep expertise in large-scale distributed systems.
Extensive experience architecting and building multi-component AI/ML platforms using search, data, and streaming technologies.
Proficiency with LLM orchestration frameworks like LangChain or LlamaIndex and RAG architectures.
Experience with agentic frameworks and multi-agent systems for complex task execution.
Strong background in full software development lifecycle ownership, including CI/CD, Kubernetes, and production operations.
Deep experience with major cloud platforms such as AWS and Azure.
Demonstrated hands-on experience building production systems using LLMs and Generative AI technologies.

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