Top AI Engineer Jobs

Design, build, and operate end-to-end data and AI systems: scalable ETL pipelines, model development and deployment, backend services/APIs, cloud infrastructure, MLOps, data governance, and lead technical reviews while mentoring engineers and collaborating with stakeholders.

Design, build, and ship end-to-end AI features: implement multi-step agentic flows with LangChain/LangGraph, integrate LLMs, connect to live data sources, deploy and monitor AI services on cloud, and instrument observability. Optionally build React/TypeScript front-end components for streaming AI outputs and co-pilot experiences.

Design, build, test, and deploy AI agents, agentic workflows, and automation solutions. Partner with stakeholders to prototype and productionize full-stack AI applications across cloud, VPS, and local GPU environments while ensuring scalability, security, and performance.

The Internal Systems Engineer builds AI-powered tools and maintains a shared agent platform while integrating AI into customer operations at impact.com.

Develop, test, and improve AI-powered voice and chat agent workflows: write scripts, configure conversational flows, analyze user data, perform QA, troubleshoot agent behavior, and collaborate with engineers and designers to optimize performance.

Build and ship end-to-end product features, debug and resolve production issues, partner with Product on UX and direction, use AI heavily for development and prototyping, and iterate quickly across the stack to improve quality and speed.

Lead technical delivery of AI-enabled web apps, dashboards, and automation. Build full-stack systems (frontend, backend, infra), integrate LLMs, RAG, vector DBs and third-party services, prototype then productionize solutions, work client-facing for scoping and translation, and provide technical leadership across architecture, standards, and documentation.

Design and build the intelligence layer: retrieval and memory systems, RAG pipelines, feedback and evaluation loops, RL and fine-tuning experiments, LLM integration, observability for AI performance, and collaborate to productize AI features.

Lead production agentic development and build R&D tooling that accelerates team workflows. Ship weekly in the main codebase, create and improve custom agents, MCP integrations, evals, and codegen pipelines, train engineers on new workflows, and raise team standards for prompts, tooling, and autonomous throughput.

As an AI Prompt Engineer, you'll develop prompt templates, conduct A/B tests, collaborate with trainers, and maintain prompt libraries for generative AI applications.

The Staff AI/ML Engineer will design, build, and improve AI systems for document retrieval and data extraction, work with clients, and mentor team members to establish best practices.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.