Lead AI Engineer

About the role

Lead AI Engineer

📍 Location: Springfield, MA, US

🏢 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 designing and deploying enterprise-scale AI solutions.

Experience leading AI initiatives from concept through production deployment.

Strong background delivering measurable business outcomes through AI.

Required Technical Expertise

Artificial Intelligence & Machine Learning

Generative AI

Large Language Models (LLMs)

Agentic AI

Machine Learning

Natural Language Processing (NLP)

Probabilistic Modeling

Statistical Analysis

Model Evaluation & Benchmarking

Software Engineering

Python

Production Software Development

API Development

Distributed Systems

System Design

Test Automation

Version Control

Infrastructure & Deployment

Docker

Kubernetes

Model Serving Platforms

AI Deployment Frameworks

Observability & Monitoring

Cloud-Native Architectures

Education

Master's Degree or Ph.D. in:

Computer Science

Statistics

Applied Mathematics

Electrical Engineering

Physics

Artificial Intelligence

Related Quantitative Discipline

Preferred Qualifications

Agentic AI & Emerging Technologies

Experience with:

AWS Bedrock AgentCore

AWS Strands

Azure AI Ecosystem

MCP Protocol

Agent-to-Agent (A2A) Frameworks

Enterprise AI & Governance

Experience deploying AI solutions within regulated industries.

Understanding of:

Compliance Requirements

Privacy Regulations

Responsible AI Frameworks

Model Governance

Advanced Analytics

Causal Inference

Bayesian Statistics

Optimization Methods

Advanced Machine Learning

Decision Sciences

Data Platforms & Search Technologies

SQL

Database Design

Vector Databases

Semantic Search

RAG Architectures

Cloud Data Platforms

Research & Technical Leadership

Published Research

Open Source Contributions

Industry Thought Leadership

Scientific Innovation

Core Competencies

AI Engineering Leadership

Large Language Models (LLMs)

Generative AI

Agentic AI

Applied Machine Learning

Natural Language Processing

AI Architecture

Production AI Systems

Retrieval-Augmented Generation (RAG)

AI Evaluation & Benchmarking

Cloud AI Platforms

Software Engineering

Experiment Design

Technical Leadership

Executive Communication

AI Governance

Team Mentorship