AI) - Hybrid

GEICO•Bethesda, MD

3d•Hybrid

About The Position

Our Senior Engineer works with our engineering team to innovate and build new systems, improve and enhance existing systems, and identify new opportunities to apply your knowledge to solve critical problems. You will lead the strategy and execution of a technical roadmap that will increase the velocity of delivering products and unlock new engineering capabilities, including shaping how applied AI and intelligent automation are incorporated into enterprise solutions where they materially improve business outcomes. The ideal candidate is a self-starter with deep technical expertise in their domain and a strong sense of which AI technologies are appropriate for various use cases, while ensuring solutions meet enterprise standards for reliability, security, and operability.

Requirements

Exemplary ability to design, perform experiments—including AI/LLM evaluation, measurement, and iterative improvement in production—and influence engineering direction and product roadmap
Extensive experience shipping LLM, generative AI, or intelligent automation solutions in production environments
Strong grasp of when to use agents, retrieval-augmented generation, classical ML, rules-based workflows, or hybrid approaches for a given business problem
Experience integrating AI into enterprise services via APIs, events, authentication, and observability patterns
Understanding of agent architectures, workflow orchestration, vector retrieval, and knowledge/context design
Extensive experience in leading and building full-stack application and service development, with a strong focus on SaaS products / platforms
Proven expertise in designing and developing microservices using GraphQL, gRPC , Java, Python, Kafka, with a deep understanding of both API and event-driven architectures, including integration of AI inference, retrieval, and async/agent workflows
Proven experience designing and delivering highly-resilient event-driven and messaging-based solutions at scale with minimal latency, including long-running, failure-tolerant workflows for multi-step AI processes
Fluency and specialization with at least two modern OOP languages such as Java, C#, C++, or Python including object-oriented design
Great understanding of open-source databases like MySQL, PostgreSQL, etc., and a strong foundation with NoSQL databases like Cosmos, Cassandra, Apache Trino, etc.
Knowledge of developer tooling across the software development life cycle (task management, source code, building, deployment, operations, real-time communication)
Fluency in test engineering and automated testing concepts, including evaluation and regression testing for non-deterministic AI components
6+ years full-stack development experience (Java/C#/Python/Go), with expertise in client-side and server-side frameworks
4+ years of experience with architecture and design
2+ years of applied AI, generative AI, or intelligent automation experience in production, or demonstrable ownership of AI-enabled platform capabilities
2+ 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

Provide technical leadership to multiple areas and provide technical and thought leadership to the enterprise, including applied AI architecture, technology selection, and integration patterns across teams
Collaborate across team members and across the tech organization to solve our toughest problems, working with product, domain experts, and analytics partners to translate business needs into technical designs that may include AI components
Deliver high-quality services and software for a variety of domains, including AI-augmented workflows and intelligent services where appropriate , with accountability for the quality, usability, and performance of the solutions
Identify and evaluate opportunities to apply AI, intelligent automation, and agentic workflows to enterprise processes, distinguishing high-value use cases from hype-driven experiments
Utilize programming languages like Java, C#, or other object-oriented languages, SQL, and NoSQL databases, container orchestration services including Docker and Kubernetes, cloud tools and services across Azure/AWS/GCP, and integrate AI services, model APIs, and orchestration tooling into the platform stack
Work on end-to-end solutions that may span front-end implementations (Flutter, Angular, React) through API tiers and back-end domain services
Be a role model and mentor, helping to coach and strengthen the technical expertise and know-how of our engineering and product community, including applied AI patterns, production evaluation, and responsible deployment practices.
Influence and educate executives
Design durable, observable AI workflows using orchestration and agent patterns (e.g., Temporal for long-running workflows; Fable and comparable agent frameworks), combining tools, APIs, business rules, and human-in-the-loop steps
Select and rationalize AI technologies for each use case—models, retrieval, vector stores, knowledge graphs, workflow engines—with clear tradeoffs on cost, latency, accuracy, security, and operability
Establish engineering patterns for evaluating, monitoring, and governing components in production, including testing, quality metrics, safety, fallback behavior, and incident response