AI Technology Lead

Role Summary

We are seeking a AI Tech Lead to lead the delivery of GenAI-powered applications and data science solutions from concept through production. This role sits at the intersection of engineering, data science, and business, requiring strong project management discipline combined with hands-on technical expertise.

The ideal candidate can manage complex technical programs, guide a team of developers and data scientists, actively contribute to solution design and development of GenAI solutions.

Key Responsibilities:

AI Technology Lead

Location: NYC / NJ

Program & Delivery Management

·         Own end-to-end delivery of GenAI and data science projects, from requirements through deployment and post-production support

·         Translate business problems into clear technical scope, milestones, and delivery plans

·         Manage project timelines, dependencies, risks, and issue resolution across multiple workstreams

·         Drive Agile execution (Scrum / Kanban), including sprint planning, standups reviews, and retrospectives

·         Ensure delivery meets quality, security, compliance, and performance standards

·         Technical Leadership (Hands-on)

·         Act as a technical lead/partner to developers and data scientists

Contribute directly to:

·         Solution architecture and design

·         Code reviews and technical decision-making

·         Proofs of concept and rapid prototyping

Guide implementation of GenAI applications, including:

·         LLM integration (e.g., OpenAI, Gemini, Claude, open-source models)

·         Prompt engineering, RAG pipelines, embeddings, vector databases

·         Model evaluation, guardrails, and responsible AI practices

Full-Stack & Data Understanding

·         Understand and guide full-stack development across:

·         Frontend (React, Angular, or similar)

·         Backend APIs and services (Python, Java, Node.js, etc.)

·         Data pipelines and feature engineering

Partner with data scientists on:

·         Model development and experimentation

·         MLOps / LLMOps workflows

·         Deployment, monitoring, and retraining strategies

Team & Stakeholder Management

·         Manage and mentor a cross-functional team of engineers, data scientists, and analysts

·         Coordinate across product, architecture, security, and business stakeholders

·         Communicate technical progress, risks, and trade-offs clearly to both technical and non-technical audiences

·         Foster a culture of engineering excellence, ownership, and continuous improvement

Required Qualifications

Experience:

·         10+ years of experience delivering technical projects in software engineering,

·         data, or AI domains

·         3+ years leading projects involving AI/ML or GenAI technologies

·         Proven experience managing engineering and data science teams

·         Hands-on experience delivering production-grade applications, not just prototypes

Technical Skills

·         Strong experience designing and delivering solutions on Microsoft Azure

·         Understanding of core Azure services, including: Azure OpenAI Service and GenAI integrations, Azure Data Factory, Azure Functions, App Services, AKS (Azure Kubernetes Service), Azure Blob Storage

Ø  Strong understanding of:

·         Full-stack application development

·         Cloud platforms ( Azure)

·         APIs, microservices, and scalable architectures

Ø  Solid knowledge of GenAI concepts, including:

·         LLMs, embeddings, vector search, RAG architectures

·         Model limitations, hallucinations, evaluation techniques

·         Experience with data science workflows, MLOps, or LLMOps is highly desirable

·         Comfortable reviewing code and contributing when needed

Project Management Skills

·         Strong Agile delivery expertise

·         Experience managing complex, ambiguous problem spaces

·         Excellent risk management and dependency tracking

·         Ability to balance speed, quality, and technical debt

Preferred Qualifications

Experience in finance or asset and wealth management