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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 Software Engineer II, AI works with cross\-functional teams and customers to understand business requirements and translates into technical specifications. Discovers the true requirements underlying feature requests and recommends alternative technical approaches. Partners with cross\-functional technical teams to launch projects and provide ongoing technical support. Collaborates with management to identify opportunities to streamline technology processes and develop new procedures that support the business unit/department.
Responsibilities:
- Establishes a technical roadmap for the platform and/or capability strategy and lifecycle that considers value\-based outcomes, costs to maintain, supportability, and performance.
- Ensures sound integration, data, security, and business architecture design throughout all stages within the platform and/or capability lifecycle.
- Provides rapid delivery and development of technical solutions that align with business and/or platform desired outcomes.
- Troubleshoots and resolves technical issues related to platform or capability systems, solutions, and services.
- Innovates and drives continuous improvements of implementation methodology and technical service offerings based on customer or employee experiences and enterprise objectives.
- Participates in a Community of Interest for engineers across all capability and platform teams to share information and strengthen understanding of business needs and technology\-based solutions.
- Develops and maintains deep technical knowledge and expertise related to domain area systems, solutions, services, and applications.
Qualifications:
- Bachelor’s degree (or equivalent experience) in Information Technology, Computer Science, Engineering, or a related field.
- 2\+ years of experience with Generative AI concepts, including embeddings, large language models (LLMs), retrieval\-augmented generation (RAG), vector databases, and tokenization
- 3\+ years of experience working with public cloud platforms, preferably Amazon Web Services (AWS)
- 4\+ years of experience with DevOps pipelines, including Git\-based repositories (e.g., GitHub, Bitbucket), static and dynamic code analysis, Infrastructure as Code (e.g., AWS CloudFormation), and deployment strategies such as blue/green deployments
- 2\+ years of experience with agentic systems, including various agent architectures, frameworks such as LangGraph, orchestration patterns, and building/hosting agents (e.g., orchestrator agents, agents as tools)
- 3\+ years of experience architecting, designing, developing, deploying, and monitoring large\-scale distributed and parallel systems using cloud\-native technologies (e.g., AWS Lambda, EKS, S3\)
- 4\+ years of hands\-on programming experience with languages such as Python, Java, Rust, SQL, and/or Node.js
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 judgment in evaluation options to make sound decisions.
- Home office environment with the ability to work effectively surrounded by moderate home environment noise.
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 $144K-$160K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $190K across 193 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,824 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At AARP, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $234,620 based on 682 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($152K) sits 35% below the category median. Disclosed range: $144K to $160K.
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 Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
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 Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
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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