AI Technologist Engineer

Lowenstein Sandler•Roseland, NJ

4d•$155,000 - $165,000•Hybrid

About The Position

The AI Technologist / Engineer will design, build, and operationalize AI-powered solutions that improve the efficiency, accuracy, and intelligence of legal and business workflows across the firm. Working closely with attorneys, business professionals, and technology colleagues, this individual will identify opportunities, deliver measurable outcomes, and serve as the firm's subject matter expert on the latest AI platforms and developer tooling. This is a hands-on engineering role for someone who is equally comfortable prototyping a new AI workflow, evaluating emerging platforms, and translating complex capabilities into practical firm value.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Management, or related field.
3+ years of software engineering or AI/ML engineering experience.
Strong programming skills in Python, JavaScript/TypeScript, React and Node.js.
Experience with REST APIs, JSON, and modern integration patterns.
Experience with C# and the .NET framework.
Proficiency in T-SQL, including writing and optimizing queries, stored procedures, and views against relational databases (SQL Server preferred).
Proficiency with Visual Studio Code (VS Code) as a primary development environment.
Demonstrated experience with context engineering principles, including context window structuring, dynamic context assembly, and grounding strategies to maximize LLM accuracy and reliability.
Demonstrated experience using AI coding tools (e.g., Claude Code, GitHub Copilot, Codex, or Cursor/Windsurf) to modify, extend, or upgrade existing applications.
Hands-on proficiency with the Anthropic Claude platform and Claude API (including system prompts, tool use, and multi-turn conversation design).
Proficiency with Claude Code for AI-assisted and agentic software development workflows.
Demonstrated experience with OpenAI ChatGPT and the OpenAI API.
Working knowledge of Google Gemini and NotebookLM for enterprise and research workflows.
Familiarity with Microsoft Copilot and its integration into Microsoft 365 and Azure environments.
Working knowledge of AI data security principles, including secure prompt design, output filtering, data minimization, and least-privilege data access patterns for LLM-based systems that handle confidential or sensitive information.
Solid written and verbal communication skills; ability to present technical concepts to non-technical stakeholders.

Nice To Haves

Experience with MCP (Model Context Protocol) server development and agentic AI frameworks.
Experience with RAG (retrieval-augmented generation) architectures and vector databases.
Experience with Azure OpenAI Service.
Experience with Azure AI Foundry for deploying, managing, and evaluating AI models and agent workflows in enterprise Azure environments.
Familiarity with Microsoft Fabric, including data lakehouse architecture, OneLake, Data Pipelines, and semantic model development.
Experience with Harvey AI or similar legal-specific AI platforms.
Familiarity with legal technology platforms such as Aderant, Intapp, iManage, Vuture, or InterAction.
Understanding of data governance, data security, privacy, and responsible AI practices in enterprise settings, including familiarity with AI security risk assessment, prompt injection defenses, and audit logging for agentic systems.

Responsibilities

Serve as the firm's internal expert on generative AI platforms including Anthropic Claude, OpenAI ChatGPT, Google Gemini and NotebookLM, and Microsoft Copilot and various legal point solutions, evaluating new capabilities and advising on appropriate use cases.
Use Claude Code for AI-assisted software development, leveraging agentic coding workflows to accelerate delivery across the team.
Design and implement secure agentic AI frameworks, including orchestration of multi-step autonomous workflows, tool integration, and guardrails to ensure safe, auditable, and policy-compliant AI operations.
Design, develop, and deploy AI-assisted tools and workflows using leading AI platforms and APIs.
Build and maintain integrations with the firm's core systems (e.g., document management, practice management, intake/conflicts, and data platforms) leveraging AI capabilities.
Develop and maintain context engineering and prompt engineering standards, including system prompt design, context window management, and retrieval augmentation strategies, alongside evaluation frameworks and responsible AI governance practices appropriate for the legal industry.
Apply security-by-design principles to AI implementations, including data classification, access controls, encryption standards, and model input/output validation to prevent data leakage, prompt injection, and unauthorized access to sensitive information.
Evaluate vendor AI solutions and produce clear build-vs-buy recommendations for leadership.
Document architectures, integration patterns, and user guides to ensure firm-wide knowledge transfer and supportability.
Stay current with the AI landscape, bringing forward actionable insights on how emerging capabilities can benefit the firm.