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.
Position Overview
We are seeking a highly motivated, visionary and technically accomplished AI engineer/Software developer to join our team and lead the design, development, deployment, and adoption of AI and machine learning solutions. This role will focus on building agentic AI systems, generative AI workflows, and scalable data platforms that power intelligent decision-making across the enterprise. The ideal candidate will possess deep expertise in AI/ML, software engineering, quality engineering, and cloud-native architectures, with a passion for solving complex problems using cutting-edge technologies.
Key Responsibilities
Develop Algorithms that enable AI agents to perform tasks without step-by-step instructions.
Design and implement agentic AI systems capable of autonomous decision-making, learning from experience, and adapting to dynamic goals and contexts
Design and develop multi-agent frameworks using tools such as LangGraph, Crew AI, or Semantic Kernel to orchestrate intelligent workflows.
Design and develop machine learning techniques that allow agents to learn from experience and adapt over time.
Translate business requirements into agentic AI solutions.
Collaborate with data scientists, software engineers, business stakeholders, and product teams to integrate AI solutions into production systems.
Conduct context and prompt engineering using zero-shot, few-shot, and chain-of-thought techniques to enhance model performance and relevance.
Optimize agents based on different models for performance, scalability, and accuracy.
Ensure ethical AI practices and compliance with data privacy regulations.
Document processes, models, and code for transparency and reproducibility.
Conduct research and stay up to date with the latest advancements in AI/ML technologies.
AI-Driven Testing & Innovation
Evaluate, implement, and scale AI-powered testing tools (e.g., self-healing automation, test generation, predictive defect analytics).
Leverage machine learning and generative AI to improve:
Test case generation
Test data creation
Defect prediction and triaging
Root cause analysis
Drive adoption of intelligent test automation frameworks and autonomous testing strategies.
Collaboration & Stakeholder Management
Partner with Product Managers, Architects, and Engineering leaders to embed quality early in design.
Partner with Product Managers, Architects, Engineering leaders, and RTEs
Communicate status, risks, and improvements to leadership
Influence enterprise adoption of modern Engineering practices across multiple teams and programs.
Required Skills & Experience
- Proficiency in programming languages such as Python, Java, or C++.
- UI/End to End Test Automation with Playwright
- Performance Load testing
- Strong foundation in AI/ML algorithms, data structures, software & quality engineering principles.
- Understanding of cloud platforms (e.g., AWS, Azure, GCP) for deploying AI solutions.
- Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker for CI/CD).
- Solid knowledge of data structures, algorithms, and software engineering principles.
- Experience with agent orchestration, LLMOps, and model lifecycle management, vector search, information retrieval, graph algorithms and knowledge graph.
- Experience with version control systems (e.g., Git).
- Familiarity with agent orchestration platforms and enterprise integration.
- Strong problem-solving skills and ability to work independently and collaboratively.
Preferred Skills & Experience
- Experience with natural language processing (NLP), computer vision, or reinforcement learning.
- Knowledge of generative AI and foundation models (e.g., Gemini, Claude).
- Experience with real-time inference systems and edge AI.
- Background in mathematics, statistics, or computational neuroscience.
- Understanding of LLM (Large Language Model) & LRM (Large Reasoning Model)
- Understanding of AI ethics, bias mitigation, and explainable AI.
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:
$127,600 - $191,400Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits
Skills Required
- Proficiency in Python, Java, or C++.
- UI/End to End Test Automation with Playwright.
- Performance load testing.
- Strong foundation in AI/ML algorithms, data structures, software and quality engineering principles.
- Understanding of cloud platforms (AWS, Azure, GCP) for deploying AI solutions.
- Familiarity with MLOps tools and practices (MLflow, Kubeflow, Docker for CI/CD).
- Experience with agent orchestration, LLMOps, and model lifecycle management.
- Experience with vector search, information retrieval, graph algorithms and knowledge graph.
- Experience with version control systems (Git).
- Familiarity with multi-agent frameworks (e.g., LangGraph, Crew AI, Semantic Kernel) and enterprise integration.
- Prompt engineering (zero-shot, few-shot, chain-of-thought) and model optimization for performance and scalability.
- Strong problem-solving skills and ability to work independently and collaboratively.
- Experience with AI-powered testing tools and techniques (self-healing automation, test generation, defect analytics).
- Experience with natural language processing, computer vision, or reinforcement learning.
- Knowledge of generative AI and foundation models (examples: Gemini, Claude).
- Experience with real-time inference systems and edge AI.
- Background in mathematics, statistics, or computational neuroscience.
- Understanding of LLM and LRM concepts.
- Understanding of AI ethics, bias mitigation, and explainable AI.
The Hartford Financial Services Group, Inc. Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Hartford Financial Services Group, Inc. and has not been reviewed or approved by The Hartford Financial Services Group, Inc..
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Retirement Support — A 401(k) with matching plus an additional company contribution, alongside an employee stock purchase plan and no‑cost financial planning, signals robust long‑term savings support. HSAs/FSAs and related financial tools further strengthen overall financial well‑being.
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Leave & Time Off Breadth — At least 25 days of PTO to start, options to buy or roll over time, and paid parental leave indicate broad time‑off support. Paid leave for organ and bone marrow donation and generous disability coverage extend protection for significant life events.
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Healthcare Strength — Multiple medical, dental, and vision options with the company covering most medical and dental premiums reflect strong core health coverage. Wellness programs, fitness reimbursements, well‑being credits, and accessible behavioral health services expand depth and accessibility.
The Hartford Financial Services Group, Inc. Insights
What We Do
Human achievement is at the heart of what we do. We put our belief into action by not only ensuring individuals and businesses are well protected, but by going even further – making an impact in ways that go beyond an insurance policy
