Staff Applied AI Engineer
Remote • Remote
Posted 1mo ago
Job Location
Remote
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Engineer
About the job
As a Staff Engineer on the AI team, you will lead the technical direction of AI agents that transform natural language into production-ready applications. This involves defining how LLMs are used to tackle complex challenges such as maintaining context across large codebases, orchestrating intuitive multi-step workflows, and managing everything from minor UI adjustments to significant architectural decisions. This role goes beyond simple API integration; you will establish the patterns and systems that guide AI reasoning and generation of full-stack applications, influencing the AI strategy across multiple teams and impacting the daily experience of millions of users building products with Bolt.
Responsibilities
- Define AI agent architecture, including context management, workflow orchestration, and scaling strategies.
- Lead multi-model strategy, developing evaluation criteria and testing new capabilities with AI providers.
- Build foundations for tool-use and workflows, designing safe interfaces for tool calling and setting best practices for frameworks.
- Drive cross-team execution by aligning product, design, and engineering efforts, resolving tradeoffs, and mentoring engineers.
- Establish data and evaluation standards, owning dataset methodology and eval harnesses to drive measurable improvements.
- Drive research and innovation in prompting, context handling, and post-training, sharing learnings externally.
Requirements
- Deep experience building and scaling production LLM systems, with a strong understanding of their capabilities, limitations, and emergent behaviors.
- Proficiency in prompt engineering, setting best practices and mentoring across various models and use cases.
- Strong software engineering fundamentals, with experience designing scalable systems and making pragmatic architectural decisions.
- Proven ability to drive ambiguous, high-scope work end-to-end and influence across teams.
- Systems thinking skills to identify and improve process, communication, and technical debt.
- Literacy in models and agents, tracking advancements in coding agents and LLMs, and understanding model tradeoffs and agent lifecycles.
- Data-driven leadership, including building data collection and evaluation harnesses and translating insights into improvements.
- Strong verbal and written English communication skills for collaboration with team members, stakeholders, and customers.
Benefits
- Fully remote, globally distributed team
- Opportunity to shape the future of software development with AI