Principal AI Engineer

The Hartford•Hartford, CT

20h•Hybrid

About The Position

We are seeking a Principal AI Engineer responsible for building our AI platform to accelerate the design, development, and deployment of AI use cases, with a particular emphasis on GenAI capabilities and accelerating use cases. This role involves bringing the transformative power of AI/GenAI capabilities to re-imagine the ‘art of possible’ and serve internal customers and transform businesses. The team is dedicated to building a state-of-the-art AI platform and is looking for an experienced Principal AI Engineer to help build the foundation of our AI capability. This individual will be a thought partner to platform leadership, providing vision and executing the build of platform capabilities that accelerate the development of complex digital assistants, enable rapid experimentation, and support the scaling and productionization of solutions with built-in scalability, security, and self-service features. The ideal candidate is an accomplished professional with significant hands-on experience in data, analytics, and MLOps/LLMOps engineering, equipped to manage and drive broader stakeholder engagements. This role requires versatility and expertise across a wide range of skills, and someone who is biased for action, visionary, and an engineer at heart will fit seamlessly.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or a technical field.
10+ years of experience with cloud (AWS / GCP)
Demonstrate a willingness to challenge the status quo and a bias for action
Extensive programming experience with Python, Typescript.
At least 8 years of experience designing and building data-intensive solutions using distributed computing.
10+ years building and shipping software and/or platform infrastructure solutions for enterprises.
Hands-on experience with cloud platforms and services, such as Google Cloud, AWS, Azure and their offerings for AI / generative AI
Experience with CI/CD pipelines, Automated Testing, Automated Deployments, Agile methodologies, Unit Testing and Integration Testing tools.
Experience with building scalable serverless applications (real-time / batch)
Knowledge of distributed NoSQL database systems.
Excellent problem-solving skills and the ability to work in a collaborative team environment.
Excellent communication skills.
Candidate must be authorized to work in the US without company sponsorship.

Nice To Haves

Experience with data engineering, ETL technology, and conversation UX is a plus.
Experience with HPCs, vector embedding, and Hybrid/Semantic search technologies.
Proficiency in customization techniques across various stages of the RAG pipeline, including model fine-tuning, retrieval re-ranking, Hybrid search and multimodal RAG plus.
Strong proficiency in embeddings, ANN/KNN, vector stores, quantization, database optimization, & performance tuning.
Experience in building Agentic systems using frameworks like LangGraph and crewai is a plus.
Basic understanding of Natural Language Processing, vector space models and Deep Learning.

Responsibilities

Key thought leader, collaborator, and contributor to the build of the AI platform that supports and accelerates GenAI and traditional predictive and ML solutions.
Define and execute the vision and roadmap for the AI platform that aligns with the organization's strategic goals and customer needs.
Drive the future state of the AI platform by staying updated with the latest trends and developments.
Lead the build and execution of POCs and prototypes that serve to qualify and validate emerging AI platform solutions that can be leveraged as solution quick starts and eventually become capabilities within the AI platform for enterprise consumption.
Provide hands-on engineering support to the build of platform capabilities e.g., agentic frameworks, IAC, production-grade capabilities, monitoring systems, developer experience, FinOps capabilities etc.
Partner with shared service teams like Architecture, Cloud, Security, etc. to design and implement platform solutions.
Collaborate with the DS team to develop a self-service internal developer AI platform.
Provide leadership and mentorship to engineers on the team, fostering a culture of innovation, collaboration, and continuous upskilling and learning.