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About This Role
Overview:
AARP is the nation's largest nonprofit, nonpartisan organization dedicated to empowering people 50 and older to choose how they live as they age. With a nationwide presence, AARP strengthens communities and advocates for what matters most to the more than 100 million Americans 50\-plus and their families: health and financial security, and personal fulfillment. AARP also works for individuals in the marketplace by sparking new solutions and allowing carefully chosen, high\-quality products and services to carry the AARP name. As a trusted source for news and information, AARP produces the nation's largest\-circulation publications, *AARP The Magazine* and the *AARP Bulletin*.
Information Technology Services is responsible for AARP enterprise\-wide technology and information security functions. Services range from infrastructure design and operations, system and software lifecycle implementations, enabling the mobile workforce and protecting AARP network, systems and data. A variety of technologies and practices are used including cloud computing, automation, artificial intelligence and machine learning within highly collaborative Agile teams.
The Engineer I, AI Agents is a technical resource on a platform/capability team responsible for supporting the day\-to\-day design, implementation and operational activities of the team.
Responsibilities:
- Assisting the team with processing transactions, resolving issues, and administering platform or capability systems, solutions, and services.
- Maintaining code repositories and Git\-based services, if applicable.
- Writing code, leveraging third\-party services, configuring systems, and implementing solutions in an agile way.
- Collaborating with team to identify technical solutions for business and enterprise needs.
- Developing technical knowledge and expertise related to domain area systems, solutions, services and applications.
Qualifications:
- Bachelor’s or Master’s in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience (including internships, academic projects, or self\-directed learning).
- 1\+ years experience and proficiency in one modern programming language (Python, JavaScript/TypeScript, C\#, or Java), with the ability to read, debug, and extend existing codebases.
- Familiarity with RESTful APIs, JSON, basic service integration patterns, and the ability to integrate with external data sources.
- Foundational understanding of Generative AI and LLMs, including prompts, tokens, context limits, strengths, limitations, and common failure modes; experience designing and iterating on prompts and structured outputs (e.g., JSON/schema\-based responses).
- Hands\-on exposure to LLM APIs or frameworks, including basic understanding of Retrieval\-Augmented Generation (RAG), document ingestion, chunking, embeddings, and grounding responses with enterprise data.
- Exposure to agent\-based or multi\-step AI systems, including tool/function calling, workflow orchestration concepts, human\-in\-the\-loop patterns, and awareness of the need for guardrails, controlled workflows, and error handling.
- Foundational understanding of cloud platforms (preferably Microsoft Azure), event\-driven or trigger\-based architectures, workflow automation tools (e.g., Power Automate, Power Apps), and basic logging, monitoring, and debugging practices.
- Analytical and problem\-solving skills, with the ability to structure ambiguous problems; demonstrated learning agility and curiosity; awareness of evaluating LLM outputs, data privacy, security, governance, and responsible AI principles.
*AARP will not sponsor an employment visa for this position at this time.* Additional Requirements*** Regular and reliable job attendance.
- Effective verbal and written communication skills.
- Exhibit respect and understanding of others to maintain professional relationships.
- Independent judgement in evaluation options to make sound decisions.
- Home office environment with the ability to work effectively surrounded by moderate home environment noise \- (Telework)
Compensation and Benefits
AARP offers a competitive compensation and benefits package including a 401(k); 100% company\-funded pension plan; health, dental, and vision plans; life insurance; paid time off to include company and individual holidays, vacation, sick, caregiving, and parental leave; performance\-based and peer\-based recognition and tuition reimbursement.
Equal Employment Opportunity
AARP is an equal opportunity employer committed to hiring a diverse workforce and sustaining an inclusive culture. AARP does not discriminate on the basis of race, ethnicity, religion, sex, color, national origin, age, sexual orientation, gender identity or expression, mental or physical disability, genetic information, veteran status, or on any other basis prohibited by applicable law.
Salary Context
This $97K-$108K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $212K across 45 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 3,824 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At AARP, 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 $252,000 based on 90 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($102K) sits 59% below the category median. Disclosed range: $97K to $108K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
AARP AI Hiring
AARP has 2 open AI roles right now. They're hiring across AI Agent Developer, AI Software Engineer. Based in Washington, DC, US. Compensation range: $108K - $160K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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