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27 results for Data Engineer in Rutherford, NJ

Cyber Security Engineer

Maryknoll, NY
onsite
Permanent / Full Time
100000 - 108312 USD / Yearly
We are looking for a Cyber Security Engineer to strengthen and oversee the organization’s security posture in New York. This role is suited to an experienced, detail-oriented individual who can assess risk, guide security practices, and protect systems across a mixed technology environment. The ideal candidate brings strong judgment, technical depth, and the ability to communicate clearly with stakeholders while handling sensitive matters with discretion. Responsibilities: • Lead day-to-day security efforts by identifying vulnerabilities, analyzing threats, and coordinating timely remediation activities across systems and networks. • Evaluate the security of Windows and macOS environments, including patch management practices, endpoint protections, and configuration standards. • Monitor network activity and security controls such as firewalls and related tools to help prevent unauthorized access and reduce operational risk. • Investigate potential incidents, determine the scope of exposure, and drive response actions to contain and resolve security issues effectively. • Review third-party security documentation, including SOC 2 reports, to support vendor risk assessments during contracting and procurement processes. • Help develop, maintain, and reinforce information security policies, standards, and procedures in alignment with regulatory and organizational requirements. • Partner with IT teams, leadership, and internal users to communicate security recommendations, report findings, and support informed decision-making. • Contribute technical and analytical expertise to strengthen monitoring capabilities, improve risk visibility, and support ongoing security program maturity.
2026-06-03T00:00:00Z

AI Engineer

New York, NY
onsite
Temporary to Hire
71 - 80 USD / Hourly
This role sits at the intersection of AI engineering, data scientist, developer enablement, and customer engagement. You will partner with Product, Engineering, Applied Science, and AI Platform teams to support implementation decisions, accelerate AI adoption, and help teams adopt reusable AI engineering patterns and implementation best practices.This is a deeply hands-on role focused on building, prototyping, and iterating on AI-powered experiences. The ideal candidate combines strong software engineering fundamentals with practical experience deploying LLM applications, agent systems, and AI-native workflows in production environments. What you’ll doStart with customers• Spend real time with lawyers, legal operations teams, and our internal subject-matter experts — in their offices, on their calls, watching their workflows. Develop a strong understanding of customer workflows and operational challenges through direct engagement.• Translate ambiguous, half-formed customer pain into crisp problem statements the team can build against.• Collaborate closely with customers and internal stakeholders to prototype, validate, and refine AI-powered workflows and user experiences based on customer feedback and observed user needs.• Bring the customer voice back into our roadmaps, our model choices, and our trade-offs.• Occasional travel to customer sites may be required to better understand workflows and gather product feedback. Build AI-powered applications and workflows<ul><li>Contribute to AI-powered applications and workflows for legal and business use cases, including leveraging existing RAG pipelines, research assistants, and related AI capabilities developed by ML engineering teams.</li><li>Implement and iterate on LLM application capabilities such as prompt engineering, multi-step workflows, tool calling, and lightweight agent patterns in collaboration with machine learning engineering teams.</li><li>Contribute to scalable orchestration layers for prompting, retrieval, and tool integration across AI services.</li><li>Work with frameworks such as LangChain, LangGraph, LlamaIndex, MCP/A2A, OpenAI SDKs, Google ADK, and/or Anthropic/Claude APIs to prototype and productionize AI capabilities.</li><li>Participate in experimentation, testing, and performance optimization activities for LLM-based applications in production environments.</li></ul>Contribute to AI Engineering Enablement<ul><li>Support adoption of AI engineering practices by helping software engineering teams incrementally integrate machine learning and generative AI capabilities into existing products and workflows, in collaboration with AI/ML engineering teams.</li><li>Promote reusable AI/ML engineering standards, tooling, and best practices that reduce friction for teams adopting AI and machine learning technologies, while aligning with recommendations from data science and AI platform teams.</li><li>Help software engineers expand their capabilities in ML-oriented development for applicable use cases without requiring deep data science specialization.</li><li> </li></ul>
2026-06-10T00:00:00Z