Senior AI Machine Learning Engineer

The Hartford; Charlotte (NC); Hybrid; USD 117,000 - 176,000; Full time

Job summary

The Hartford is seeking a Senior Data Engineer to lead enterprise-scale AI/ML solutions within Employee Benefits Applied AI and Analytics. You will own model portfolios, build pipelines, and deploy production-grade AI services across pricing, underwriting, and sales workflows.

You will mentor engineers, collaborate with Data Scientists and stakeholders, and help expand into generative AI capabilities. This role supports a hybrid work schedule with office presence three days a week in the US.

Qualifications

• Bachelor’s degree or 6+ years in related technical roles.
• Strong Python, SQL, SDLC and production-grade code delivery.
• Experience deploying AI/ML workloads in AWS and GCP.

Responsibilities

• Lead day-to-day engineering for the EB predictive model portfolio.
• Build, deploy, and maintain AI/ML components and data pipelines.
• Implement designs and translate patterns into production code.
• Support generative AI/agentic AI initiatives and governance.
• Develop batch and near-real-time data/AI pipelines for training and inference.
• Deploy AI services in AWS/GCP with CI/CD, observability, and security.
• Mentor junior engineers and collaborate with stakeholders.

Skills

Python

SQL

SDLC

Git

Automated testing

Cloud (AWS/GCP)

ML/AI workflows

Education

Bachelor’s degree

Master’s degree preferred

Tools

Airflow

Cloud Composer

Step Functions

Vertex AI Pipelines

Job description

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future. The Hartford is seeking a Senior AI Machine Learning Engineer within Employee Benefits Applied AI and Analytics (EB AIA) to help build, deploy, and sustain enterprise-scale predictive and applied AI solutions across pricing, underwriting, sales related EB business workflows. As a Senior AI/ML engineer you will manage and modernize the existing predictive model portfolio while helping the team expand into generative AI, agentic AI and other applied AI capabilities. The role is intended for a hands-on technical lead who can execute approved solution designs, deploy production-ready AI and ML components, operate reliable model pipelines, and guide junior engineers. The person should be able to translate architecture and design direction into working, governed, and production assets with minimal supervision.

Primary Responsibilities

• Lead day-to-day engineering execution for the EB predictive model portfolio, including pricing and underwriting models, scoring pipelines, model refreshes, monitoring, data validations, and production support.
• Build, deploy, and maintain AI/ML components and data pipelines that support applied AI use cases across pricing, underwriting, sales, service, renewal, and policy lifecycle workflows.
• Implement approved solution designs from senior Applied AI Engineers, Architects, and Data Scientists; translate design patterns into tested, reliable production code and workflows.
• Support the initial build-out of generative AI and agentic AI solutions, including prompt orchestration, retrieval-augmented generation patterns, evaluation workflows, guardrails, and integration with existing EB data and application ecosystems.
• Develop and operate batch and near-real-time data/AI pipelines for model training, feature generation, inference, post-processing, business rules integration, and downstream consumption.
• Deploy and sustain production AI services, jobs, APIs, and workflows in AWS and GCP environments using approved CI/CD, testing, observability, security, and operational practices.
• Own implementation quality for assigned components, including code reviews, unit/integration testing, documentation, runbooks, production readiness checks, and incident response support.
• Guide and mentor junior engineers by breaking down technical work, reviewing code, explaining model/data pipeline patterns, and ensuring consistent engineering practices.
• Partner with Data Scientists, Data Engineers, Asset Owners, Underwriting, Pricing stakeholders to understand requirements, validate outputs, resolve data issues, and ensure model solutions fit business workflows.
• Maintain model and pipeline governance artifacts, including lineage, model inputs/outputs, monitoring metrics, validation evidence, operational controls, and handoff documentation.
• Identify risks, bottlenecks, and operational gaps in deployed AI/ML solutions and recommend practical improvements under the guidance of senior technical leadership.

Minimum Requirements

• Bachelor’s degree in related field or 6+ years of equivalent experience in software engineering, data engineering, ML/DevOps engineering, applied AI engineering, or closely related technical roles.
• Master’s degree in computer science, engineering, information technology, MIS, data science, or related discipline preferred.
• Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing, and production-grade code delivery.
• Experience deploying and operating data, AI, or ML workloads in AWS and GCP, including cloud storage, managed compute, orchestration, IAM-aware access patterns, logging, and monitoring.
• Experience with ML engineering concepts such as feature pipelines, model training workflows, batch scoring, inference services, model monitoring, drift detection, validation, retraining, and production support.
• Ability to work within defined architecture, enterprise security standards, data governance expectations, coding standards, and operational controls.
• Ability to lead implementation work, guide junior engineers, communicate tradeoffs, and manage multiple model/pipeline deliverables with limited day-to-day direction.

Preferred Experience

• Experience in insurance, employee benefits, pricing, underwriting, risk selection, sales enablement, or policy lifecycle analytics.
• Experience supporting predictive model portfolios that require periodic refreshes, performance tracking, business validation, and governed production deployment.
• Experience with generative AI or agentic AI implementation patterns, including RAG, prompt evaluation, LLM application integration, AI safety controls, human-in-the-loop workflows, and model output validation.
• Experience with orchestration and workflow tools such as Airflow, Cloud Composer, Step Functions, Vertex AI Pipelines, or comparable enterprise platforms.
• Experience with CI/CD, containers, APIs, infrastructure-as-code concepts, observability, and production incident management.

Success Profile

A successful candidate will be a hands-on engineering lead who can take a generated or approved architecture, convert it into deployable assets, keep predictive AI models running reliably, and help the team move into applied AI delivery. The candidate should be comfortable doing implementation work across pricing and underwriting under senior supervision, while also raising the capability of junior engineers through practical technical guidance.

This role will have a Hybrid work schedule, with the expectation of working in an office 3 days a week.

Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $117,200 - $175,800

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

Culture & Values

Every day, a day to do right. Showing up for people isn't just what we do. It's who we are - and have been for more than 200 years. We're devoted to finding innovative ways to serve our customers, communities and employees - continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it's these values that drive all of us to do more and to do better every day.