> Markdown version of [/jobs/ext/618766-sr-ai-engineer](https://www.wearedevelopers.com/jobs/ext/618766-sr-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SR. AI ENGINEER - **Company:** Revi Inc - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $220,000.0 - $270,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Microsoft Azure, Batch Processing, Big Data, Cloud Computing, Cloud Engineering, Continuous Integration, Information Engineering, Distributed Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Reliability Engineering, Software Deployment, Systems Integration, Speech Recognition, Core Voice Platform, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Containerization, Kubernetes, Information Technology, Apache Flink, Apache Kafka, Machine Learning Operations, Speech Synthesis, GPT, Data Pipelines, Docker, Databricks, Web Api - **Published:** June 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d693521d2d7d7fe9 ## About the Role Do you have experience in Systems integration?, Do you have a Bachelor's degree?, * 6+ years of professional work experience building and shipping ML/AI systems in production. Personal projects, hackathons, and class work do not substitute for this requirement - we need engineers who have operated AI in real production environments at meaningful scale * Deep, hands-on experience with agentic AI - you have personally architected and shipped single-agent or multi-agent systems in a production setting. You can speak fluently about tool use, planning loops, evaluation, failure modes, and the tradeoffs between orchestration patterns * Strong deterministic ML modeling background - production experience training and serving classification, ranking, retrieval, or recommendation models. Familiarity with the full ML lifecycle: data, features, training, evaluation, serving, monitoring * Production experience with LLM providers (Anthropic Claude, OpenAI GPT, or equivalent) - not just API calls, but production integration including prompt engineering at scale, tool use, structured outputs, evaluation, cost control, and reliability engineering * Production deployment experience is critical and non-negotiable - you have personally owned services running in production, including CI/CD, containerization (Docker/Kubernetes), cloud infrastructure (AWS/GCP/Azure), monitoring/observability, and on-call. Candidates without demonstrable production deployment ownership will not be considered * Hands-on production experience with large-scale data processing tools - including distributed batch processing (Spark, Databricks, or equivalent) and streaming/event pipelines (Kafka, Kinesis, Pub/Sub, Flink, or equivalent). You have built and operated real data pipelines feeding ML/AI systems at scale, not just consumed pre-processed datasets * Excellent Python, strong fundamentals in distributed systems, data engineering, and modern cloud infrastructure * BS, MS, or PhD in Computer Science, Machine Learning, or a related quantitative field - or equivalent professional track record, * Prior Staff or Tech Lead experience at a high-growth startup or a top-tier tech company * Experience with voice AI, real-time conversational systems, or speech-to-text/text-to-speech pipelines * Deep experience with vector databases, retrieval systems, and large-scale RAG architectures * LLM observability and evaluation tooling expertise (LangSmith, Langfuse, custom eval frameworks) * Experience in restaurant tech, commerce platforms, or B2B SaaS at scale * Experience fine-tuning, distilling, or post-training open-weight models for production ## Description We're hiring a Senior AI Engineer to architect, build, and own production-grade agentic AI systems at Revi. You'll lead the design of single-agent and multi-agent systems that take real actions for restaurants and their customers, own the deterministic ML stack that powers personalization and decisioning across the product, and set the bar for how we deploy, monitor, and evolve AI in production. This is an IC role for a builder who has shipped - repeatedly - and knows what production reliability for AI systems actually requires., * Architect and ship agentic AI systems end-to-end - designing single-agent and multi-agent topologies, tool interfaces, memory and state management, evaluation harnesses, and the production infrastructure that holds it all together * Own the deterministic ML modeling stack - feature pipelines, training, ranking/retrieval, evaluation, and online serving for high-traffic use cases * Drive integration with LLM providers (Claude, GPT, and others) at production scale - handling latency, cost, reliability, prompt iteration, structured outputs, function/tool calling, and provider failover * Own production deployment and operations: CI/CD, containerization, observability, on-call quality, cost monitoring, and graceful degradation strategies for AI systems * Set technical direction and review architectural decisions across the AI Engineering team; mentor junior engineers and raise the engineering bar * Partner with product and leadership to translate Revi's growth strategy into concrete AI roadmaps ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Web APIs you might not know about](https://www.wearedevelopers.com/videos/281-web-apis-you-might-not-know-about) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)