AI Engineer - United States

Pulsora, Inc.•Chicago, IL

7d•$50,000 - $60,000•Hybrid

About The Position

Pulsora, a well-funded Silicon Valley software startup founded in 2021, is seeking a highly skilled and experienced AI/ML Developer to join their team. This role focuses on the rapidly evolving fields of Large Language Models (LLMs) and generative AI, with an emphasis on developing, integrating, and optimizing complex agentic and RAG-based systems. The company's mission is to empower enterprises to manage and improve their environmental, social, and governance (ESG) and overall sustainability footprint through an innovative technology platform.

Requirements

Undergraduate degree in Computer Science or similar Engineering field.
5+ years of professional experience in software development.
Minimum of 2 years focused on AI/ML development, particularly with LLMs.
Strong proficiency in Python and its relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn).
Proven experience integrating and working with major LLM APIs (public and private/local), e.g., Gemini, OpenAI, Anthropic, Llama, Ollama, including hands-on experience using techniques for LLM efficiency.
At least 1 year of deep practical experience with LangChain and LangGraph for building complex LLM applications and agentic workflows using autonomous agents, tools, memory management, parallelization, etc.
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).
Solid understanding and implementation experience with RAG architectures, vector DBs, vector search, embeddings, and reranking mechanisms.
Experience leveraging AI Copilot or similar generative AI coding tools for accelerated development, code generation, refactoring, optimization, and vibe coding to create integrated backend and frontend applications.
Strong collaboration across a small team, including great communication with both onshore and offshore departments and translating vague requirements into actionable systems.
Self-motivated and proactive—you create momentum without needing direction.
A strong problem solver who can navigate ambiguity.
A builder who cares about shipping real, working products.
Comfortable with ownership, accountability, and high expectations.
Thrives outside of traditional work structures.
Owns the quality of the product they build.

Nice To Haves

Advanced degree is a plus.
Experience creating UI using React and integrating the UI with the backend using REST APIs is a big plus.
Hands-on experience with Java, especially integrating Java modules with Python modules is a nice to have, but not necessary.
Ideally have industry and market knowledge of ESG and sustainability.

Responsibilities

Design, develop, and deploy production-grade applications leveraging various LLMs and context optimization techniques.
Architect and implement sophisticated, multi-step and multi-agent workflows using frameworks like LangChain and LangGraph.
Build and optimize RAG pipelines, including implementing and managing embeddings, vector databases, and advanced rerankers.
Utilize code generation applications (e.g., Replit, Cursor, Google AI Studio, GitHub Copilot in Agent mode) to create full applications, generate tests, perform testing, and integrate them into the core product without writing code.
Lead efforts in LLM fine-tuning (e.g., LoRA, QLoRA) for specific domain knowledge and tasks, and implement strategies for efficiency.
Develop and refine advanced prompt engineering techniques to maximize model performance, consistency, and safety.
Own end-to-end implementation from frontend to backend.
Expose AI/LLM functionality written in Python using Java services, leveraging multi-threading capabilities in Java to augment AI/LLM functionality developed in Python.
Utilize AI-powered development tools (e.g., GitHub Copilot) to efficiently generate, refactor, and optimize high-quality code.
Collaborate closely with team leads, managers, QA, product managers, and the team in the US, which will require partial work during US working hours.