*****Please do not apply if you are not a US Citizen, or Green Card Holder. Unfortunately, this role does not offer sponsorship*****
Role Overview
We’re seeking an experienced AI engineer who enjoys building real products—not just experiments—and who can take ideas from early sketches to live, customer-facing systems. In this role, you’ll collaborate closely with product and platform partners to design and deliver intelligent features that are secure, scalable, and grounded in sound engineering principles.
You’ll operate with a high degree of autonomy, make thoughtful tradeoff decisions, and move quickly without sacrificing quality. This position is well suited for someone who thrives amid ambiguity, adapts easily as priorities shift, and still delivers reliable solutions used by active end users interacting with agent-driven experiences.
What You’ll Work On
Intelligent Feature Delivery
Collaborate with engineers, data scientists, program leaders, and product partners to ship AI-driven capabilities that meaningfully improve how users work.
Design and implement agent-based systems that handle reasoning, task decomposition, orchestration, and tool usage across internal and external workflows.
Build and scale modern agent frameworks that integrate tools, MCPs, APIs, and emerging interaction patterns while handling failures, exceptions, and human feedback loops.
Apply validation, attribution, and safety mechanisms that ensure consistent and predictable agent behavior by treating prompts and model outputs as untrusted inputs.
Convert fast-changing product concepts into clear technical approaches and working implementations.
Develop advanced retrieval-based pipelines that allow AI systems to search, combine, and reason over structured and unstructured data sources.
Provide technical leadership in defining how agent orchestration evolves across the organization.
Own features end to end—from prototyping and experimentation through deployment, monitoring, and ongoing support.
Move quickly during discovery phases while maintaining production-quality standards in deployed systems.
Product & Team Collaboration
Work hand-in-hand with product managers to refine scope, user experience, and feasibility as ideas evolve.
Partner with AI platform and infrastructure teams to align on shared tools, patterns, and best practices.
Offer technical guidance that helps teams navigate tradeoffs in a rapidly changing environment.
Act as a stabilizing force between shifting product direction and durable technical execution.
Mentor peers and help elevate the overall quality of AI engineering practices.
Engineering Quality & Safety
Design AI solutions with security and privacy as first-class concerns.
Build systems that are maintainable, testable, and resilient to continuous iteration.
Apply strong software engineering fundamentals, including testing strategies, version control, observability, and documentation.
Proactively identify and address risks related to model behavior, reliability, performance, and misuse.
AI Systems & Integration
Build and integrate solutions using large language models, retrieval-augmented generation, agent-based architectures, and API-driven tool use.
Implement prompt strategies, evaluation methods, and feedback loops to steadily improve system quality.
Embed AI capabilities into existing applications, services, and workflows.
Monitor live systems and continuously optimize for response quality, latency, cost efficiency, and user outcomes.
What You Bring
Required Experience
7+ years of professional software engineering experience, including meaningful work on AI-enabled or intelligent systems.
Strong proficiency in Python, with experience integrating AI/ML or LLM-based services; familiarity with JavaScript or TypeScript for UI-driven or interactive experiences.
Proven ability to work independently and make sound technical decisions under time pressure.
Demonstrated success delivering production systems in environments with evolving requirements.
Solid understanding of software architecture, API design, distributed systems, and data access patterns across relational databases and data platforms.
Working knowledge of security, data privacy, and access control in modern AI systems.