Top AI Specialist Jobs in NYC, NY

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Design, deploy, and manage AI-enabled legal tools and digital employees; support AI governance, data analytics and reporting for contracts; administer CLM and legal tech platforms; maintain processes, controls, and playbooks; and coordinate with attorneys, business teams, and external counsel to improve contracting, vendor management, and data quality.

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.

Develop data-driven insights, predictive models, and analytical tools for U.S. Rates trading. Build dashboards and applications, leverage AI/agentic tools and ML techniques, partner with product and sales, and identify revenue-generating data products to drive strategy and improve client outcomes.

Join an internal AI enablement team to assess workflows, build prompt-based automations and lightweight apps, coach business teams, test and document tools, track user skill development, research AI platforms, and ensure governance and security compliance.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

Evaluate and implement AI and automation solutions for legal workflows; lead pilots and rollouts; collaborate with attorneys and tech teams; create training and change management materials; identify process improvements to increase efficiency across practice areas.

Develop and optimize prompts, context management, and multimodal prompting workflows for LLM-powered products. Collaborate with Customer Success to iterate on prompts, review conversations and feedback, document and teach prompting best practices, and build small prototypes using Python and low-code tools to test complex prompting and data workflows.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead discovery and build AI-enabled operational workflows across R&D and business functions. Translate requirements into practical solutions, own design-to-launch, optimize adoption, and manage Marketing Operations (campaigns, automation, tech stack). Measure outcomes, document solutions, and ensure alignment with shared AI standards.

The SAP AI Specialist will integrate AI within SAP systems, optimizing capabilities using SAP Joule and BTP AI services, and developing predictive analytics and automation solutions.

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.

Conduct research on machine learning algorithms, implement and validate these algorithms, collaborate in a multidisciplinary team, and publish findings.

Lead identification, prioritization, and delivery of production-grade AI and generative AI solutions for reinsurance operations. Drive AI strategy, cross-functional execution, governance and responsible AI, change management, training, and measurable business value.

Lead identification, design, and delivery of generative AI solutions across reinsurance operations. Drive AI strategy, cross-functional coordination, MLOps productionization, responsible AI governance, change management, and stakeholder adoption to deliver measurable business value.

Lead change management for AI-powered tools and workflows: assess impacts, build adoption plans, create training and communications, coach leaders and enablement teams, recruit change champions, track adoption metrics, and share learnings across the Change Management team.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.

Evaluate and improve LLM financial reasoning by designing real-world finance tasks, creating reference solutions, scoring AI outputs with structured rubrics, refining evaluation frameworks, and collaborating with researchers to raise data quality and model performance. Must provide detailed feedback and identify gaps to enhance AI across finance use cases.

The AI Implementation Specialist analyzes client workflows, identifies automation opportunities, designs and implements AI-driven solutions to enhance business efficiency and productivity.

Design and deliver GenAI solutions: prototype to production LLM services, build RAG pipelines, fine-tune models (LoRA/QLoRA/PEFT), engineer prompts/tools/memory, ensure safety and evaluation, deploy with MLOps (CI/CD, containers, IaC), optimize inference, and ensure security/compliance while collaborating with product, data, and SRE teams.

Work with product, engineering, and data teams to generate, label, and evaluate medication-focused datasets, review AI outputs for clinical accuracy, provide SME guidance for product features, ensure safety/compliance, and improve clinical intelligence processes and tooling.

Design realistic, specialty-specific clinical case scenarios and gold-standard attending-level responses, evaluate and grade AI-generated outputs using structured rubrics, provide detailed written feedback to improve model clinical reasoning, and participate in onboarding, calibration, and review sessions in a fully remote, asynchronous contractor role (~20 hours/week).

PhD-level physicists will design challenging graduate-level physics problems and contribute high-quality datasets to improve AI model reasoning, ensuring scientific rigor and consistency while collaborating remotely and asynchronously.