Top AI Engineer Jobs

Develop real-time Voice AI systems, mentor juniors, and collaborate with customers to optimize call intelligence and reduce latency.

Design and build applications using Python, manage component design, optimize performance, and collaborate with clients on innovative products.

The Senior Associate will build and extend the data platform and AI applications, focusing on data engineering, cloud infrastructure, and AI development.

Design, prototype, and deliver enterprise AI solutions (RAG, LLMs, agents). Architect data flows and integrations, evaluate third-party models, build production features, establish telemetry and evaluation, partner with stakeholders, maintain AI roadmap, and evangelize AI adoption across business units.

Lead a small team to research, develop, train, optimize, and deploy computer vision and multimodal fusion AI/ML models for remote sensing (EO/SAR). Analyze large datasets, translate research into operational systems, present technical findings to customers, and produce supporting documentation and user guides.

The role involves developing AI/ML algorithms in various disciplines, analyzing datasets, and mentoring team members within a research environment.

Develop and manage the research infrastructure for AI at Databricks, focusing on large-scale training, orchestration, and improving developer productivity.

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.

Design, implement, and optimize embedded firmware and NPU/DSP runtimes for on-device ML. Build realtime sensor-to-inference pipelines, optimize latency, memory, and power, debug hardware/firmware interactions, and collaborate with ML, electrical, and product teams to deliver production-grade edge intelligence.

Design, build, and scale an enterprise AI/ML platform and edge inference systems. Develop FastAPI Python services, CI/CD pipelines, ML orchestration (LangGraph, MLflow), data and knowledge pipelines (RAG, knowledge graphs), deploy models to edge GPUs (NVIDIA Jetson) via Azure IoT Edge, and own reliability, observability, and cost optimization. Hybrid role in Atlanta.

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.

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.

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.