Distinguished Machine Learning Engineer

Das ist der Job

Distinguished Engineer GEICO is seeking a Distinguished Engineer (AI Platforms) to join our AI organization.

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Serve as a final technical authority on complex architectural decisions impacting multiple products, teams, and business domains. Drive alignment across teams by translating complex technical and business concepts into clear architectural guidance and decision frameworks.

Annual Salary $210,000.00 - $350,000.00 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.

This individual will serve as one of the most senior technical authorities driving the architecture, evolution, and long‑term technical strategy of GEICO’s Generative AI and virtual agent platforms. This platform directly supports productivity and service quality for 20K+ contact center employees across claims, service, and sales.

In this role, you will operate with enterprise‑wide technical influence, shaping foundational AI platform capabilities that enable large‑scale, production‑grade GenAI and agentic workflows across GEICO.

You will work closely with senior engineers, architects, product leaders, and executives to define and evolve durable, scalable, and extensible AI systems that underpin multiple lines of business.

The ideal candidate brings a proven track record of designing and architecting complex, multi‑system AI/ML platforms at scale, deep hands‑on expertise, and a strong passion for Generative AI technologies in real‑world production environments.

Key Responsibilities Enterprise Architecture & Technical Authority Define, own, and evolve the foundational architecture for GEICO’s Generative AI and agentic workflow platforms.

Design interconnected, high‑performance, and durable platform components that power end‑to‑end GenAI workflows, including: Knowledge curation and management Search and retrieval systems Prompt and context management Workflow orchestration and action execution Semantic and knowledge graph systems Platform & GenAI Applications Strategy, Architecture, and Business Impact Establish and drive multi‑year technical strategy and roadmaps for both AI platform capabilities and Generative AI (GenAI) applications in close partnership with product and business leaders.

Balance speed, scalability, reliability, and extensibility while ensuring platforms and GenAI applications can support future AI use cases, evolving business needs, and organizational growth. Influence investment decisions by evaluating build vs. buy tradeoffs and architectural choices for both the underlying platform and GenAI applications.

Define the reference architecture and best practices for GenAI application development, deployment, and integration, ensuring alignment with overall enterprise architecture. Collaborate with business stakeholders to identify high‑impact GenAI application opportunities and develop strategies to maximize business value and measurable outcomes.

Continuously assess and communicate the business impact of GenAI applications, providing clear metrics and feedback loops to inform ongoing strategy and platform evolution.

System & Technology Evaluation Lead evaluation and selection of core technologies, frameworks, and infrastructure components with an emphasis on building and scaling Generative AI applications, including LLM orchestration (e.g., LangChain, LlamaIndex), agentic workflows, RAG systems, and evaluation/observability tooling, while partnering on underlying AI platform infrastructure and services to support production readiness.

Ensure architectural consistency and technical rigor across open‑source, cloud‑agnostic, and managed service integrations. Cross‑Organization Influence Collaborate across engineering, data science, ML, product, and design organizations to align on platform and GenAI application direction, technical standards, and business objectives.

Partner with senior technical and business leaders across departments to promote enterprise‑wide adoption of GenAI best practices and maximize organizational impact.

Technical Leadership & Problem Solving Tackle the most complex and ambiguous technical and business challenges affecting system‑wide and application‑specific performance, reliability, and scalability. Lead deep technical reviews, architectural assessments, and design discussions for critical AI and GenAI application initiatives.

Guide platform and GenAI application evolution through hands‑on engagement when necessary, especially in high‑impact or high‑risk areas.

Mentorship & Technical Stewardship Mentor senior engineers and technical leads, setting a high bar for architectural thinking, engineering quality, and technical decision‑making for both platform and GenAI application initiatives.

Establish and reinforce best practices for platform and GenAI application design, reliability, observability, and operational excellence. Contribute to internal documentation, architectural standards, and technical knowledge sharing for both the AI platform and GenAI applications.

Minimum Qualifications Master’s degree or higher in Computer Science, Engineering, Statistics, or 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 technologies such as: Search and retrieval systems (e.g., Elasticsearch, Qdrant, Milvus, Pinecone, Weaviate) Data platforms (e.g., Snowflake, relational and NoSQL databases, and feature stores) Streaming and distributed processing (e.g., Kafka, Spark, Ray) Workflow orchestration (e.g., Airflow, Temporal, Prefect) LLM orchestration and application frameworks (e.g., LangChain, LlamaIndex) Observability, evaluation, and tracing for GenAI systems (e.g., LangSmith, ArizePhoenix, Weights & Biases, OpenTelemetry) Vector databases, embedding pipelines, and retrieval‑augmented generation (RAG) architectures Agentic frameworks and multi‑agent systems for complex task execution Strong background in full software development lifecycle ownership, including CI/CD, Kubernetes, monitoring, 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 (e.g., GPT, Llama, Mistral, Claude) to power conversational and agentic workflows.

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.

Equal Employment Opportunity The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law.

GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates.

GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment.

We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants. #J-18808-Ljbffr