Staff AI Engineer
New
USFull-TimeStaff
Salary$250,000 to $265,000 USD
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSPythonMachine LearningCI/CDGenerative AI
Requirements
- 8+ years of professional experience developing AI and machine learning systems in production environments.
- Proven ability to lead complex technical initiatives spanning multiple teams, systems, or platforms.
- Strong expertise in software engineering principles, including system design, testing, CI/CD, debugging, and scalable architecture.
- Experience building and deploying LLM-powered applications, generative AI solutions, AI agents, RAG systems, and advanced prompt engineering workflows.
- Experience designing AI evaluation frameworks, monitoring systems, and shared tooling for machine learning applications.
- Strong programming skills in Python and familiarity with software engineering best practices.
- Experience working with cloud environments, including AWS services and serverless technologies.
- Knowledge of relational databases and production data systems.
- Ability to mentor senior engineers and influence technical strategy without direct management responsibility.
- Strong communication skills with the ability to collaborate across technical and non-technical teams.
Responsibilities
- Design and develop core AI system architectures that support multiple product areas, ensuring scalability, reliability, and reuse.
- Establish engineering standards, evaluation frameworks, testing strategies, and shared infrastructure for AI and machine learning systems.
- Identify and proactively address technical challenges, improving system performance and preventing future engineering issues.
- Own the development of complex AI solutions, including conversational agents, deep learning models, and personalization systems.
- Build and optimize production-grade AI/ML applications using modern approaches such as generative AI, LLMs, and advanced model evaluation techniques.
- Partner with product, engineering leadership, and research teams to translate complex business goals into effective technical solutions.
- Raise the technical capabilities of the engineering organization through design reviews, code reviews, and knowledge sharing.
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