AI Engineering Jobs in United States
There are 3,909 open AI Engineering jobs in United States on freehire right now. 1,111 of them were posted recently. The skills employers ask for most often are ai, llm and python.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| USD | year | $173,950 | $210,000 | $244,875 | 567 |
| USD | hour | $25 | $38 | $55 | 25 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- ai 96%
- llm 70%
- python 65%
- machine-learning 58%
- agentic-ai 56%
- cloud 51%
- api 48%
- rag 38%
How the work is done
- Remote 723 · 18%
- Hybrid 603 · 15%
- Onsite 562 · 14%
Visa sponsorship offered in 53% of the 469 postings that state a position on it.
Seniority
- Senior 850
- Lead 328
- Staff 234
- Principal 200
- Intern 139
- C-level 114
Who is hiring
- 1000+ employees 348
- 501-1000 employees 148
- 11-50 employees 71
- 51-200 employees 42
- 1-10 employees 12
- 201-500 employees 12
Principal AI Engineer
Senior technical leader who designs and scales enterprise AI/ML systems for Manhattan Associates' supply chain commerce software: leading development and production deployment of ML, deep learning, and generative AI models, mentoring engineers, and driving AI strategy. Core stack is Python (TensorFlow, PyTorch, Hugging Face), Airflow/Spark data pipelines, AWS/GCP/Azure with Docker/Kubernetes, and
Sr. AI Engineer
Senior AI Engineer at Uniphore building the enterprise GenAI stack: evaluating, fine-tuning, and productionizing LLMs and multimodal (NLP/vision/ASR) foundation models, analyzing model performance, and managing large datasets. Core stack: Python, PyTorch/TensorFlow, Hugging Face/Transformers, deployed via Docker/AWS/Kubernetes.
Director, Applied AI & Strategy
Hands-on director role at A+E Global Media prototyping and shipping production-grade agentic AI to automate internal media workflows — building LLM agents with RAG, guardrails, evaluations, and MCP/API integrations, while advising leadership on AI strategy (Buy/Build/Ignore). Requires 8+ years technical and 2+ years building LLM agents.
AI Research Engineer: Vision AI / VLM / Physical AI-1
Research engineer at an AI data foundry translating cutting-edge vision research — VLMs, 2D/3D perception, embodied/physical AI — from paper to production. Daily work spans model training in PyTorch, rigorous ablations, and deployment via FastAPI, Ray, Docker, and Kubernetes, with optional robotics simulation in NVIDIA Isaac/Omniverse.
Senior AI Engineer
Engineer on Centific's Physical AI team, building, fine-tuning, and deploying production AI systems spanning vision, video, multimodal, and agentic/robotics use cases. Core stack: Python, PyTorch/TensorFlow/JAX, NVIDIA NeMo/Riva/RAPIDS/Triton, AWS Bedrock, and GCP Vertex AI.
Staff AI Engineer
Staff AI Engineer at Relativity, whose AI-powered cloud platform RelativityOne serves legal eDiscovery. The role defines the multi-year MLOps roadmap, architects scalable training, inference, and monitoring systems on AWS/Azure/GCP (Python/Java/Scala, Docker/Kubernetes, Terraform, Airflow/Prefect), and mentors engineers across teams.
Staff AI Engineer
Staff AI Engineer at Relativity, a legal data intelligence company: you own how AI-powered eDiscovery products (document review, case strategy, fact/memo generation, translate, redact) are built, evaluated, and operated — spanning LLM/RAG inference paths, evaluation suites, token economics, and retrieval over petabyte-scale legal data.
Applied AI Engineer
Builds LLM- and ML-powered features and agentic automation pipelines for an AI-first wealth management platform, taking AI capabilities from experiment to production while improving model reasoning quality. Core tech: LLMs, ML, and statistical/data analysis in a small startup team.
AI Product Engineer
Build and refine AI-driven software at Tavrn, a legal AI startup automating medical chronologies, demand letters, and record retrieval for plaintiff law firms. Day to day: full product development in Python/JavaScript on cloud platforms, customer onboarding support, testing, and documentation.
Sr. Principal Software and AI Engineer
Senior technical lead architecting and shipping production-grade AI and agentic applications for drug development at a pharmaceutical company, focused on protocol generation and clinical trial execution. Hands-on work spans Python/.NET backends, multi-agent orchestration, LLMOps, knowledge graphs, and GxP-compliant delivery.
Applied AI Scientist
Customer-facing Applied AI Scientist at a ~20-person Series B startup that builds custom AI models for supply chain forecasting: run technical and value demos, work directly with enterprise customer data in Python and SQL, and shepherd evaluations, pilots, and deployments to production. On-site in San Francisco 5 days/week.
AI Engineer
Remote (LATAM) full-time contract building end-to-end AI prototypes solo — RAG pipelines, AI agents, and document-processing tools — for early-stage U.S. clients. Focused on shipping scrappy MVPs fast using LLMs plus AI-assisted dev tools (Claude Code, Cursor, Codex); Python/LangChain/FastAPI stack preferred but flexible.
Generative AI Application Engineer
Mid-level, hands-on engineer for a SaaS data analytics company serving banks, building production generative AI features (LLM-API applications, agents, evaluation/monitoring harnesses) in Python and SQL, deployed on Azure. Remote US role on Eastern hours; candidates must have verifiable shipped GenAI apps and reachable references.
AI Software Engineer, CA
Builds the technical backbone of autonomous AI tools: designing and deploying an AI agentic workflow framework with multi-agent orchestration, LLM integrations (OpenAI, Claude, LangChain), and RAG retrieval/evaluation pipelines. Core stack is Java/Kotlin microservices on GCP/AWS with containerization and async event processing.
Senior AI Engineer
Hands-on technical lead and primary builder on Amalgamated Bank's Data Governance team, designing, building, and operating governed, auditable LLM agents and agentic solutions on Databricks in a regulated banking environment. Core stack: Python, SQL, Databricks (Unity Catalog, AI Gateway), MCP tooling, and LLM observability.
AI Engineer
AI Engineer at Amalgamated Bank developing, testing, and supporting enterprise AI solutions — LLM applications, RAG pipelines, and multi-agent systems — using Python, Databricks, and approved AI platforms in a regulated banking environment, with responsibilities spanning data engineering, model evaluation/monitoring, and AI governance.