Top AI Automation Jobs in NYC, NY

Senior AI leader responsible for defining enterprise AI strategy, prioritizing high‑value use cases across underwriting, pricing, claims and operations, building an AI organization, partnering with technology/data/risk teams, ensuring regulatory compliance, and driving adoption and measurable business outcomes.

Enable and mentor partners to sell and deliver NiCE AI/CCaaS solutions. Lead technical discovery, demos, PoVs, and architecture reviews; build partner enablement content; manage technical partner relationships, integrations, release impacts, and service scoping.

The Principal Consultant leads AI and digital transformation engagements, guides clients in identifying AI opportunities, builds strategies and roadmaps, implements solutions, and develops teams to achieve measurable business outcomes.

Build and ship AI-native systems for a fintech app: AI agents, RAG/retrieval systems, tool-calling and automation for onboarding, KYC, support, risk, CRM and operations. Work with product and engineering to design reliable, low-hallucination, cost- and latency-aware solutions and turn manual processes into scalable AI-enabled systems.

Design, build, and maintain LLM-powered workflows, automations, and internal tools. Integrate AI solutions with GTM systems (Salesforce, HubSpot, Outreach, Gong), build orchestrations with n8n/Zapier/Clay/Apps Script, and establish AI architecture (RAG, vector DBs, MCPs). Partner with business leaders to prioritize, deliver, and iterate durable automation and internal applications that improve operational efficiency and member experiences.

Designs and deploys AI assistants, copilots, custom agents, and end-to-end workflow automations across business functions. Builds integrations between AI platforms and enterprise systems using APIs, middleware, and serverless architectures. Develops prompt, RAG, and agentic solutions while measuring ROI and adoption. Partners with IT Operations and Security on governance, privacy, compliance, and secure deployment. Documents solutions, trains teams, and continuously improves automations based on usage and feedback.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Build and productionize AI-powered internal automation tools, including RAG workflows, intelligent agents, integrations, and reusable automation components. Partner with Sales, Marketing, and Finance AI Champions to identify workflow bottlenecks and enable safe self-service. Improve TDD, CI/CD, infrastructure-as-code, monitoring, logging, and observability practices while maintaining reliable internal APIs and workflows. Establish a scalable component library and operational model for enterprise automation.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

Lead enterprise adoption of Microsoft Copilot, Copilot Studio, and Power Platform by analyzing business processes, designing AI agents, building ROI-backed automation roadmaps, delivering training and prompt engineering best practices, and measuring utilization and productivity improvements across functions.

Design and execute test strategies and automation for cloud-native and GenAI/AI-ML systems. Perform functional, integration, performance, security, and API testing; validate model accuracy, fairness, robustness, and data quality; integrate automation into CI/CD; track defects; mentor junior QA engineers.

The AI Automation Engineer will automate internal processes, mentor non-technical staff on building tools, and ensure solutions deliver measurable business impact using AI technologies.

Partner with Commercial teams to discover root causes, design and deploy end-to-end AI automation solutions, drive adoption and enablement, run hackathons, and maintain a prioritized roadmap while collaborating closely with Engineering.

Embed with Commercial teams to run discovery and root-cause analysis, design and build end-to-end AI automation solutions, deploy and drive adoption, enable AI fluency across teams through best practices and an AI Hub, run hackathons, collaborate with GTM Systems engineering, and maintain a prioritized Commercial AI roadmap.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.

Design and build automation frameworks and evaluation pipelines for agentic AI products. Develop non-deterministic tests, golden datasets, tool-use validation, prompt regression tests, latency/token monitoring, hallucination detection, and collaborate with AI engineers to convert requirements into measurable automated test cases.

Lead QA Automation for agentic AI products by designing eval pipelines, golden datasets, and automated tests for tool-use, hallucination detection, latency/token monitoring, and regression across models and prompts. Integrate performance testing into CI/CD and collaborate with AI engineers to convert requirements into measurable automated evaluations.

The AI Engineer will develop scalable AI systems, automate workflows, and collaborate with business teams to enhance operational efficiency across OpenSesame.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

The AI Automation Engineer will apply AI in finance operations to automate processes like AP, AR, and reconciliation, ensuring compliance and performance measurement.

Build scalable QC systems and validation pipelines for RL training data: define quality standards, design metrics and experiments, audit supplier datasets, partner with vendors to diagnose failures, and integrate learnings into infrastructure and vendor tooling.

The Director of AI Automation leads AI-driven automation systems, translating strategic goals into practical solutions, managing teams, and enhancing operational efficiency.

Join a talent pool to teach, author, or advise on AI-powered automation. Deliver live workshops, create course materials, design exercises, shape curriculum, review technical content, and support program updates. Part-time (10–15 hrs/week), remote with collaboration in European time zones. Roles span junior to senior levels and emphasize hands-on experience with automation platforms and real-world operational workflows.

The AI Automation Engineer develops AI-driven systems to automate sales and marketing workflows, partnering with various teams to enhance revenue generation and process efficiency.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.