Technical lead building safe, evaluable LLM agents and AI infrastructure for OpenLoop’s telehealth platform. Setting architecture, observability, retrieval, and model operations direction.
About the role
- Applied AI Engineer developing scalable AI-powered applications for Pulsora's sustainability platform. Building and deploying sophisticated AI-driven products using leading LLM APIs.
Responsibilities
- Build & Ship AI-Powered Products
- Design, develop, and deploy LLM-powered applications and agent-based systems in production
- Own the full product lifecycle from concept → production → iteration across backend and frontend
- Build scalable, maintainable systems that solve real customer problems
- Develop prompt strategies, context management (RAG, memory), and agent workflows
- Integrate and optimize across leading LLM APIs (OpenAI, Anthropic, Gemini, open-source)
- Continuously improve system quality, reliability, and performance
- Use AI-assisted coding tools (e.g., Cursor, Copilot, Claude Code) to accelerate development
- Validate, test, and safely integrate AI-generated code into production systems
- Own testing strategy including unit, integration, and end-to-end testing
- Define and implement evaluation frameworks for AI outputs (quality, consistency, failure modes)
- Debug production issues and optimize for latency, cost, and scalability
- Translate ambiguous requirements into working solutions
- Partner with product, design, and customer-facing teams to deliver impactful features
- Collaborate effectively with distributed and offshore engineering teams
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related field preferred (or equivalent hands on experience)
- 1-2 years of experience building AI-powered applications (AI agents or AI-assisted coding) and building and deploying LLM-powered applications or agents in production
- Experience integrating major LLM APIs (e.g., OpenAI, Anthropic, Gemini, open-source)
- Working knowledge of prompt design, context management (RAG, memory, tool use), and multi-step/agentic workflows
- Ability to take products from concept to production and iteration across backend and frontend systems, including working across the full engineering lifecycle
- Practical experience using tools like Claude Code, Cursor, OpenAI, Microsoft Copilot, including the ability to safely integrate AI-generated code into production (validation, CI/CD)
- Experience debugging production issues, optimizing performance (latency, cost), and building maintainable systems
- Ability to define evaluation strategies for AI outputs (quality, consistency, failure modes) and experience with AI-driven testing and reliability practices.
Benefits
- Offers Equity
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