Software Engineer, AI Native

Collaborate with cross‑functional teams (product, design, operations, infrastructure) to build innovative AI‑native application experiences

Build and integrate LLM / generative AI capabilities into product surfaces (mobile, web), including prompt engineering, structured prompting, and context management

Develop and maintain reusable software components for interfacing with back‑end platforms, model serving/inference layers, and AI tool chains

Implement retrieval‑augmented generation (RAG) patterns (e.g., embeddings + retrieval) and contribute to context‑aware and personalized user experiences

Contribute to agentic workflows and AI agents (including human‑in‑the‑loop / expert‑in‑the‑loop designs) to automate tasks and scale impact

Analyze, debug, and optimize code and systems for quality, efficiency, performance, reliability, and cost

Establish effective quality practices for AI features, including evaluation/QA for AI outputs, monitoring, and iterative improvement via feedback loops

Architect efficient and scalable systems that power complex applications and AI‑enabled features, identify and resolve performance and scalability issues

Drive end‑to‑end execution of medium‑to‑large features with increasing independence, contribute to technical direction within the team

Establish ownership of components, features, or systems with comprehensive end‑to‑end understanding

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

6+ years of programming experience in a relevant language OR a PhD + 3 years programming experience in a relevant language

Experience building maintainable and testable codebases, including API design and unit testing techniques

Experience collaborating cross‑functionally and contributing to technical decisions through influence, communication, and execution

Experience effectively utilizing AI technologies and tools (e.g., large language models, agents, etc.) to enhance workflows

Experience with one or more languages such as C/C++, Java, Python, JavaScript, Hack, and/or shell scripting

Experience with AI/ML techniques and workflows such as fine‑tuning, transfer learning, few‑shot/zero‑shot approaches, and/or model distillation

Experience implementing RAG, embeddings, or knowledge‑backed generation and familiarity with tokenization and transformer‑based systems

Experience in one or more of the following: LLMs, generative AI, machine learning, recommendation systems, pattern recognition, data mining, or related fields

Experience designing AI agents, orchestration, and human‑in‑the‑loop systems and treating AI as a collaborator to accelerate delivery

Experience with architectural patterns of large‑scale software applications and improving efficiency, scalability, and stability of system resources

Experience improving quality through thoughtful code reviews, appropriate testing, rollout, monitoring, and proactive changes

Understanding of Responsible AI practices (AI safety, ethics, alignment, explainability) and building safeguards/quality controls for AI outputs

Experience with ML tooling/frameworks such as PyTorch, Tensor Flow, and Python