Ai Engineer Jobs

About The Position

Requirements

• A four-year degree or equivalent experience.
• At least 5 years of software development experience, with strong hands-on engineering and programming skills.
• Expertise in software architecture, design, distributed systems, APIs, cloud-native technologies, and modern engineering practices.
• Demonstrated programming proficiency in languages such as Java, Python, or Kotlin.
• Hands-on experience building and productionizing AI applications using LLMs, agentic architectures, model APIs, retrieval/context patterns, tool integration, and evaluation frameworks.
• Ability to lead complex technical initiatives from design through production, guide architectural decisions, and navigate ambiguous engineering challenges across teams or systems.
• Experience with production engineering practices, including CI/CD, testing, observability, reliability, performance, security, and operations.
• Experience developing reusable engineering patterns, technical tooling, reference implementations, APIs, SDKs, or platform capabilities that improve platform adoption and engineering efficiency.
• Ability to provide technical guidance, influence engineering decisions, and improve engineering practices through collaboration, architecture reviews, and knowledge sharing.
• Effective communication and technical judgment, including the ability to evaluate tradeoffs and collaborate across product, engineering, and platform teams.

Responsibilities

• Lead complex technical engagements that accelerate enterprise AI platform adoption, combining solution architecture, hands-on engineering, and technical guidance to help teams move from experimentation to production.
• Design, build, and productionize AI solutions, reference implementations, technical tooling, and platform-support capabilities using LLMs, agentic architectures, enterprise context and retrieval, model APIs, and tool integrations.
• Guide technical design and implementation across engineering efforts; help teams navigate architectural decisions, troubleshoot challenges, and develop scalable, maintainable solutions.
• Apply software engineering and distributed systems expertise to improve the reliability, security, performance, observability, and operational readiness of production AI systems.
• Identify recurring implementation challenges, integration gaps, and platform limitations, and collaborate with platform engineering to develop reusable patterns, APIs, SDKs, frameworks, and shared capabilities.
• Establish and improve engineering practices across engagements, including architecture reviews, code quality, testing, evaluation, deployment, and production operations.
• Collaborate across product, engineering, and platform teams to evaluate technical approaches, share implementation learnings, and improve enterprise AI capability adoption.
• Maintain technical knowledge and stay current with evolving AI and software engineering technologies through formal training and self-directed learning.

Benefits

• Eligible team members and dependents may receive medical, vision, dental, and life insurance, among other health benefits and programs.
• 401(k)
• Employee discount
• Short-term disability
• Long-term disability
• Paid sick leave
• Paid national holidays
• Paid vacation