Applied AI Engineer - US at Pulsora in Chicago, IL

Summary: Pulsora is a well-funded Silicon Valley software startup focused on empowering enterprises to manage their environmental, social, and governance (ESG) sustainability footprint. They are seeking an Applied AI Engineer to build and scale full-stack products, design and deploy LLM-powered systems, and ensure system quality and reliability. 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 - Design & Operate GenAI Systems - 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 - Leverage AI-First Development Workflows - 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 - Contribute to evolving best practices for AI-first engineering - Ensure Quality, Reliability & Performance - 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 - Take full ownership of system reliability and production stability - Collaborate & Execute in Fast-Moving Environments - 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 - Advance AI & Product Capabilities (Nice to Have Contributions) - Build advanced agent systems (planning, orchestration, parallel execution) - Apply frameworks like LangChain, LangGraph, or similar where appropriate - Explore fine-tuning, evaluation frameworks, and benchmarking techniques - Contribute to intuitive, user-friendly AI-driven experiences and human-in-the-loop workflows Required Qualifications: - 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 Preferred Qualifications: - Ideally have industry and market knowledge of ESG and sustainability - Build advanced agent systems (planning, orchestration, parallel execution) - Apply frameworks like LangChain, LangGraph, or similar where appropriate - Explore fine-tuning, evaluation frameworks, and benchmarking techniques - Contribute to intuitive, user-friendly AI-driven experiences and human-in-the-loop workflows Required Skills: AI-powered application development, LLM-powered application deployment, LLM API integration, Prompt design, Context management, Agent workflows, Backend development, Frontend development, AI-assisted coding tools, Production debugging, Performance optimization, AI output evaluation, CI/CD Benefits: Equity, Benefits, Hybrid-friendly work environment, in office 2-3 times per week (for those in New York, San Francisco Bay Area, and Munich)