Lead AI Engineer

Lead AI Engineer

📍 Location: New York, New York, United States

🏢 Industry: Financial services

💼 Work Setting: Hybrid

Are you passionate about building enterprise-scale AI systems, advancing Generative AI capabilities, and transforming cutting-edge research into real business impact?

We are seeking an experienced Lead AI Engineer to drive the design, development, deployment, and scaling of advanced AI solutions across the enterprise. This role combines AI architecture, machine learning engineering, applied research, software engineering, and technical leadership to deliver innovative solutions powered by Large Language Models (LLMs), Agentic AI, machine learning, and probabilistic modeling.

The ideal candidate is a hands-on technical leader who can architect production-grade AI systems, influence enterprise AI strategy, mentor engineers and data scientists, and translate complex AI innovations into measurable business outcomes.

Key Responsibilities

AI Architecture & Solution Delivery

• Lead the end-to-end design, development, deployment, and operation of enterprise AI solutions.
• Architect scalable AI applications utilizing:
• Generative AI
• Large Language Models (LLMs)
• Agentic AI Systems
• Machine Learning Models
• Probabilistic Modeling Techniques
• Define technical architecture, integration patterns, and deployment strategies.
• Ensure solutions meet requirements for:
• Reliability
• Scalability
• Security
• Maintainability
• Performance

Generative AI & Agentic AI Engineering

• Design and implement advanced AI systems powered by foundation models and agent frameworks.
• Build intelligent workflows that leverage:
• Multi-Agent Architectures
• Autonomous Reasoning
• Tool Invocation Frameworks
• Retrieval-Augmented Generation (RAG)
• Workflow Automation
• Develop standards for prompt engineering, evaluation, orchestration, and model governance.
• Establish best practices for responsible and secure AI deployments.

AI Experimentation & Evaluation

• Design rigorous evaluation frameworks for AI and machine learning systems.
• Perform:
• Benchmarking
• Model Comparisons
• A/B Testing
• Quantitative Performance Analysis
• LLM Evaluation
• Assess model quality, accuracy, safety, and business impact.
• Drive data-driven technical decisions through scientific experimentation.

Applied Research & Innovation

• Monitor emerging developments in:
• Generative AI
• Foundation Models
• Agentic Systems
• Machine Learning
• Natural Language Processing
• Evaluate new technologies and determine applicability to business challenges.
• Translate research breakthroughs into practical enterprise solutions.
• Establish innovation practices and AI engineering standards across the team.

Rapid Prototyping & Productization

• Create proof-of-concepts and prototypes to validate AI opportunities.
• Quickly evaluate feasibility, business value, and technical viability.
• Transition successful experiments into production-ready applications.
• Deliver AI-powered products such as:
• Intelligent Assistants
• Chatbots
• Knowledge Platforms
• Decision-Support Systems
• Automated Workflows
• Analytics Applications

AI Engineering & Platform Integration

• Partner with engineering teams to operationalize AI solutions.
• Build APIs, services, pipelines, and integration frameworks.
• Ensure AI systems integrate seamlessly with enterprise applications and platforms.
• Support model deployment, monitoring, versioning, and lifecycle management.
• Promote software engineering best practices throughout AI development.

Leadership & Strategic Influence

• Serve as a trusted advisor to senior leadership on AI strategy and opportunities.
• Align AI initiatives with organizational priorities and business objectives.
• Present complex technical concepts to executive audiences in an actionable manner.
• Influence architecture decisions and enterprise technology roadmaps.
• Advocate for responsible AI development and governance.

Mentorship & Team Development

• Coach and mentor AI engineers, data scientists, and technical team members.
• Foster a culture of:
• Technical Excellence
• Scientific Rigor
• Innovation
• Knowledge Sharing
• Continuous Learning
• Participate in hiring and talent development efforts.
• Raise engineering standards across the AI organization.

Qualifications

Required Experience

• 7+ years of experience in:
• Artificial Intelligence
• Machine Learning
• Data Science
• AI Engineering
• Proven record de…