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About This Role
Who Are We?
Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.
Compensation Overview
The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance\-based cash incentive awards.
Salary Range
$120,400\.00 \- $198,700\.00Target Openings
2What Is the Opportunity?
What Is the Opportunity?
As a member of the Enterprise AI and Emerging Technology organization at Travelers, you'll be joining a strategic and collaborative team focused on transforming our business and technology capabilities leveraging best in class AI\-enabled technology. We're looking for a Software Engineer II in the Enterprise AI Platforms organization to join our team focused on delivering the agent harnesses and platform capabilities that enable and accelerate the development of generative AI applications across the enterprise.
- Will embed with partner teams to accelerate high\-priority agentic delivery, moving to where the need is greatest and leaving those teams able to sustain the work. Engineers at this level work across the full architecture of product delivery from requirements gathering to maintenance and enhancement of existing systems.
- Will lead solution design for assigned workstreams, participate in stakeholder conversations, and build collective ownership across engineering, architecture, and product.
- This role is for engineers who become productive quickly in unfamiliar codebases and who bring production\-ready delivery experience to a fast\-paced environment.
What Will You Do?
- Design and deliver production\-grade harness capabilities that engineering teams leverage to build and deploy generative AI applications.
- Drive architecture and system design for agentic components across multiple teams, advancing the technical patterns and engineering standards adopted across the enterprise.
- Help teams align to enterprise standards and practices in source code management, testing, CI/CD, and modern engineering principles.
- Advance test automation and raise the quality bar on the harness and the systems it serves.
- Apply systems thinking to identify and resolve the cross\-team dependencies and bottlenecks that slow delivery down.
- Mentor engineers inside and outside the team and contribute reusable capabilities rather than one\-off solutions.
- Engage directly in stakeholder conversations and translate technical direction into terms the business can act on.
- Participate in cross\-organizational engineering events and technical forums to share harness patterns and practices across the enterprise.
- Perform other responsibilities as assigned.
What Will Our Ideal Candidate Have?
- 4\+ years of hands\-on software development experience, including demonstrated production delivery of AI solutions you have supported at scale.
- Proficiency in Python, with experience in additional languages such as TypeScript, particularly for building AI integrations.
- Hands\-on experience building, deploying, and evaluating generative AI applications, including the runtime concerns around them: orchestration, tool interfaces, context and memory management, and guardrails.
- Experience using agentic coding tools, with an informed point of view on where they help and where they fall short.
- Hands\-on experience across the cloud delivery stack: AWS and/or Azure, Kubernetes, infrastructure as code such as Terraform or CDK, and CI/CD tooling such as GitHub Actions or Jenkins.
- Hands\-on experience designing, delivering, and maintaining large, distributed, production\-grade applications in an enterprise setting, including third\-party vendor software and secure\-by\-design development practices.
- SME\-level depth in multiple technical disciplines, with the ability to get productive quickly in an unfamiliar codebase and operate across multiple projects at once.
- Strong communication skills with the ability to lead technical conversations with non\-technical business stakeholders and translate complex capabilities into measurable business outcomes.
- Experience with agentic runtimes and harness platforms such as AWS AgentCore.
- OSS agent frameworks such as Strands Agents or LangGraph experience.
- Helm for Kubernetes application deployment experience.
- Observability tooling and distributed tracing in production environments experience.
Zero\-trust security principles when building and deploying enterprise systems experience.
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What is a Must Have?
- Bachelor’s degree in computer science, related STEM field, or its equivalent in education and/or work experience.
- 4 additional years of software engineering experience.
What Is in It for You?
- Health Insurance: Employees and their eligible family members – including spouses, domestic partners, and children – are eligible for coverage from the first day of employment.
- Retirement: Travelers matches your 401(k) contributions dollar\-for\-dollar up to your first 5% of eligible pay, subject to an annual maximum. If you have student loan debt, you can enroll in the Paying it Forward Savings Program. When you make a payment toward your student loan, Travelers will make an annual contribution into your 401(k) account. You are also eligible for a Pension Plan that is 100% funded by Travelers.
- Paid Time Off: Start your career at Travelers with a minimum of 20 days Paid Time Off annually, plus nine paid company Holidays.
- Wellness Program: The Travelers wellness program is comprised of tools, discounts and resources that empower you to achieve your wellness goals and caregiving needs. In addition, our mental health program provides access to free professional counseling services, health coaching and other resources to support your daily life needs.
- Volunteer Encouragement: We have a deep commitment to the communities we serve and encourage our employees to get involved. Travelers has a Matching Gift and Volunteer Rewards program that enables you to give back to the charity of your choice.
Employment Practices
Travelers is an equal opportunity employer. We value the unique abilities and talents each individual brings to our organization and recognize that we benefit in numerous ways from our differences.
In accordance with local law, candidates seeking employment in Colorado are not required to disclose dates of attendance at or graduation from educational institutions.
If you are a candidate and have specific questions regarding the physical requirements of this role, please send us an email so we may assist you.
Travelers reserves the right to fill this position at a level above or below the level included in this posting.
To learn more about our comprehensive benefit programs please visit http://careers.travelers.com/life\-at\-travelers/benefits/.
Salary Context
This $120K-$198K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $200K across 33 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Travelers, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $240,000 based on 96 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($159K) sits 34% below the category median. Disclosed range: $120K to $198K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Travelers AI Hiring
Travelers has 5 open AI roles right now. They're hiring across AI Agent Developer, AI Software Engineer, AI/ML Engineer, Data Engineer. Positions span Atlanta, GA, US, Hartford, CT, US. Compensation range: $198K - $230K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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