AI Solutions Lead

AI Solutions Lead

Locations: Manhattan, New York

Type: Full-time – Onsite (2 days a week)

Experience: 12 - 15 years

Job Description

We are seeking a highly experienced AI Solutions Lead to design and deliver advanced AI-driven solutions for enterprise clients. This role combines hands-on AI engineering, data architecture, and consulting, requiring strong technical depth along with the ability to translate complex business challenges into scalable and production-ready solutions.

The role involves working closely with stakeholders across business and technology teams to identify opportunities for AI-led transformation, particularly in areas such as LLM-powered automation, intelligent data discovery, and natural language interfaces. You will take ownership of solution design, development, and validation, ensuring high levels of accuracy, reliability, and business impact.

This position is best suited for professionals who thrive in dynamic consulting environments, can navigate ambiguity, and are equally comfortable in stakeholder conversations and hands-on development.

Roles & Responsibilities:

AI Solution Design & Development

• Design and implement AI-driven solutions, including LLM-based applications, agentic workflows, and automation systems
• Build multi-step data pipelines for document processing, transformation, validation, and error handling
• Develop semantic search and RAG-based solutions using embeddings, vector databases, and retrieval pipelines
• Build natural language query (NLQ) interfaces for business users

Stakeholder Engagement & Consulting

• Engage with business stakeholders to understand complex workflows and identify opportunities for AI adoption
• Translate business requirements into scalable technical architectures and solution designs
• Provide guidance on feasibility, solution approach, and implementation strategy

Data Engineering & Architecture

• Design and maintain data pipelines, APIs, and backend systems
• Develop semantic data models and metadata layers for AI-driven applications
• Ensure integration with enterprise platforms, data sources, and governance systems

AI/LLM Engineering

• Develop and optimize LLM-based applications using structured prompts, tool usage, and validation frameworks
• Implement agentic AI patterns including orchestration, memory, and multi-step reasoning
• Integrate AI capabilities with enterprise systems and data platforms

Validation & Quality Assurance

• Establish ground-truth datasets, evaluation frameworks, and accuracy benchmarks
• Perform systematic error analysis and continuous model/pipeline improvement
• Ensure high standards of data quality, explainability, and reliability

Technical Background:

Core Skills

• Strong proficiency in Python (data pipelines, APIs, backend development)
• Experience building data engineering pipelines and scalable backend systems
• Strong SQL expertise (CTEs, joins, analytical queries)
• Hands-on experience with LLMs / Generative AI applications

AI & Data Engineering

• Experience with:
• RAG (Retrieval Augmented Generation) architectures
• Embeddings and vector databases
• Agentic workflows / orchestration frameworks
• Strong understanding of:
• Prompt engineering
• Structured outputs and validation
• Data modeling and knowledge representation

Tools & Technologies

• Python ecosystem: pandas, pydantic, httpx, BeautifulSoup, openpyxl
• Backend frameworks: FastAPI / Flask
• Exposure to cloud platforms (AWS/Azure) and modern data ecosystems

Nice to Have

• Knowledge graph technologies (e.g., Neo4j)
• Experience with data governance or metadata platforms
• Familiarity with document parsing and extraction workflows
• Domain exposure to financial services or large-scale enterprise data

Base Compensation Range: $140,000 – $160,000

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.