Applied AI Engineer

Job not on LinkedIn

🕒 July 16

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

pulsESG

WebsiteLinkedInAll Job Openings

11 - 50 employees

☁️ SaaS

🌍 Social Impact

💰 Venture Round on 2022-11

SaaS • Social Impact

pulsESG is a public benefit corporation founded in 2021 that focuses on empowering purpose-driven enterprises to manage and improve their ESG (Environmental, Social, and Governance) footprint. The company offers a comprehensive SaaS platform designed for compliance tracking and gaining insights, allowing businesses to effectively meet their sustainability goals.

📋 Description

• 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

🎯 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

• The company will pay with salary, equity, and benefits • You’ll get to work on problems that are hard and important • You get to work on a solution that helps the planet and helps us all • You’ll be joining an extraordinary team at the beginning of an extraordinary journey • Hybrid-friendly work environment, in office 2-3 times per week (for those in New York, San Francisco Bay Area, and Munich)