Note: The job is a remote job and is open to candidates in USA. Bolt.new by StackBlitz is a company focused on developing next-gen, AI-powered app builders. As a Staff Engineer on the AI team, you will lead the technical direction of AI agents, shaping how they turn natural language into production-ready applications and influencing the broader AI strategy.
Responsibilities
- Define AI Agent Architecture: Set technical direction for how agents manage context, orchestrate workflows, and scale
- Lead multi-model strategy: Build evals and selection criteria across providers (OpenAI, Anthropic, Google); partner with provider teams to test new capabilities
- Build tool-use & workflow foundations: Design safe, reliable interfaces for tool calling (search, queries, domain actions); evaluate frameworks (e.g., Vercel AI SDK, LangGraph) and set org best practices
- Drive cross-team execution: Align product/design/engineering, resolve tradeoffs, and mentor engineers to raise AI engineering standards
- Establish data & evaluation standards: Own dataset methodology and the eval harness; turn failure modes and conversation insights into measurable improvements
- Drive Research and Innovation: Experiment with prompting, context handling, and post-training; share learnings externally when appropriate
Skills
- Deep LLM experience: Built and scaled production LLM systems; strong grasp of capabilities, limits, and emergent behavior
- Prompt engineering: Sets best practices and mentors across models and use cases
- Software engineering: Strong fundamentals; designs scalable systems and makes pragmatic architectural calls
- Strategic execution: Drives ambiguous, high-scope work end to end; influences across teams
- Systems thinking: Spots process/communication/technical debt and improves team velocity
- Model & agent literacy: Tracks coding-agent/LLM advances; understands model tradeoffs and the agent lifecycle
- Data-driven leadership: Builds data collection + eval harnesses; turns insights into measurable improvements
- Strong verbal and written English communication skills are required, as this role involves frequent collaboration with team members, stakeholders, and customers where English is the primary working language
- Fine-tuning and alignment of: LLMs (SFT, RLHF/RLAIF, DPO/ORPO)
- Machine Learning Background: Understanding of ML fundamentals and experience with model evaluation metrics
- Open Source Contributions: Experience contributing to or maintaining open-source AI/ML projects
- Research Background: Experience reading and implementing techniques from AI/ML research papers
- External Presence: Experience speaking at conferences, publishing technical content, or representing an organization in industry forums
Company Overview