Senior AI Engineer (Engineering Productivity)

We're looking for a Senior AI Engineer to join our Engineering Productivity team, focused on leveraging AI/LLM technologies to fundamentally improve how our engineers build, test, deploy, and operate software. You'll design and implement AI-powered tools and systems that measurably accelerate development velocity across the organization.What You'll Do:Design and build AI-powered developer tools (code generation, automated review, intelligent testing) that improve engineering efficiency across the companyDevelop and deploy LLM-based applications (RAG, AI Agents, code understanding) to streamline internal workflows — from coding to deployment to incident responseBuild and optimize AI-assisted CI/CD pipelines, including intelligent test selection, build failure prediction, and deployment risk assessmentCreate internal knowledge retrieval systems (RAG-based) enabling engineers to quickly search and understand codebases, documentation, and architectural decisionsEvaluate, fine-tune, and integrate state-of-the-art LLMs (open-source and commercial) for engineering use casesDefine metrics and conduct A/B tests to measure the impact of AI tools on developer productivityCollaborate closely with engineering teams across the organization to identify high-impact automation opportunitiesWhat We're Looking For: 5+ years of software engineering experience, with at least 2 years focused on AI/ML engineeringStrong hands-on experience with LLMs — including prompt engineering, RAG, fine-tuning (SFT/RLHF), and AI Agent frameworks (LangChain, LangGraph, CrewAI, or similar)Solid programming skills in Python; experience with Go, Java, or TypeScript is a plusExperience building production-grade AI applications — not just prototypesFamiliarity with code analysis tools and techniques (AST parsing, static analysis, LSP) is highly preferredUnderstanding of modern CI/CD systems and DevOps practicesStrong system design skills — ability to architect scalable, reliable servicesExcellent problem-solving skills with a pragmatic, results-oriented mindsetNice to Have: Experience building AI coding assistants or developer productivity toolsExperience with code embedding models and code search systemsContributions to open-source AI/ML projectsPublications in relevant areas (NLP, code intelligence, SE + AI)Experience in the Web3/crypto industryOriginally posted on Himalayas

We're looking for a Senior AI Engineer to join our Engineering Productivity team, focused on leveraging AI/LLM technologies to fundamentally improve how our engineers build, test, deploy, and operate software. You'll design and implement AI-powered tools and systems that measurably accelerate development velocity across the organization.What You'll Do:Design and build AI-powered developer tools (code generation, automated review, intelligent testing) that improve engineering efficiency across the companyDevelop and deploy LLM-based applications (RAG, AI Agents, code understanding) to streamline internal workflows — from coding to deployment to incident responseBuild and optimize AI-assisted CI/CD pipelines, including intelligent test selection, build failure prediction, and deployment risk assessmentCreate internal knowledge retrieval systems (RAG-based) enabling engineers to quickly search and understand codebases, documentation, and architectural decisionsEvaluate, fine-tune, and integrate state-of-the-art LLMs (open-source and commercial) for engineering use casesDefine metrics and conduct A/B tests to measure the impact of AI tools on developer productivityCollaborate closely with engineering teams across the organization to identify high-impact automation opportunitiesWhat We're Looking For: 5+ years of software engineering experience, with at least 2 years focused on AI/ML engineeringStrong hands-on experience with LLMs — including prompt engineering, RAG, fine-tuning (SFT/RLHF), and AI Agent frameworks (LangChain, LangGraph, CrewAI, or similar)Solid programming skills in Python; experience with Go, Java, or TypeScript is a plusExperience building production-grade AI applications — not just prototypesFamiliarity with code analysis tools and techniques (AST parsing, static analysis, LSP) is highly preferredUnderstanding of modern CI/CD systems and DevOps practicesStrong system design skills — ability to architect scalable, reliable servicesExcellent problem-solving skills with a pragmatic, results-oriented mindsetNice to Have: Experience building AI coding assistants or developer productivity toolsExperience with code embedding models and code search systemsContributions to open-source AI/ML projectsPublications in relevant areas (NLP, code intelligence, SE + AI)Experience in the Web3/crypto industryOriginally posted on Himalayas