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About This Role
JOB CODE
TEC4017
Staff Software Engineer
MANAGEMENT LEVEL
6 Senior Manager
DISCIPLINE
Software Engineering
REPORTS TO
Director of Engineering
FSLA CLASSIFICATION
Exempt
The Staff Software Engineer provides technical leadership for complex, scalable systems. This role drives architecture, code quality, and reliability across critical services while mentoring engineers and aligning solutions with business outcomes. The engineer partners with product, security, and operations to design resilient platforms, reduce risk, and accelerate delivery. Success requires hands\-on development, thoughtful tradeoffs, and clear communication that advances engineering standards and unlocks team effectiveness.StaffSoftware Engineer
Location:hybrid in Nashville, TN, Sterling, VA, Bay Area hub or REMOTE
At Asurion, we don’t just redefine—we reinvent. We began by establishing a culture that rewards results and isn’t confined by a hierarchy. As a result, we have achieved phenomenal growth. Today, this entrepreneurial spirit is as strong as ever. It’s in our DNA. We foster a culture where our team members are encouraged daily to make a difference—for our clients, customers, and themselves. Our dynamic and rewarding environment ensures that each of our 19,000\+ team members has the opportunity to reach their full potential, while at the same time fulfilling the needs of more than 300 million consumers.
Generative AI is now a proven, production capability in modern digital experiences—not an experiment. Customers increasingly expect fast, conversational, and personalized help across web and support journeys, and our platform is actively incorporating GenAI to meet those expectations at scale. The Intelligence Org team builds and operates GenAI\-centered digital experiences for new and existing Asurion clients, and internally on Asurion.com (millions of monthly visitors), focusing on reliable, secure, measurable outcomes\*\*—improving self\-service success, accelerating issue resolution, and maximizing the value of every customer engagement that starts in the digital channel.\*\*
The opportunity
We are seeking a Staff Software Engineer who can provide technical leadership across Asurion’s customer service AI platform, partnering with internal stakeholders, product managers, designers, QA, data science, and engineering teams to design and scale production GenAI capabilities across expert tooling, conversational workflows, and digital customer support experiences.
Someone who wants to build a world\-class platform that makes Asurion stand out. From architecture and technical strategy through implementation, testing, launch, and production support, you’ll help define durable patterns for workflow orchestration, AI grounding, config management, integrations, observability, and reliable customer\-facing outcomes at scale.
Join us and you’ll be part of a team that loves trying out new ideas, creating impactful solutions, thinking big, and working at the intersection of GenAI, customer service, workflow orchestration, and production\-grade platform engineering.
WhatYou’llBe Doing
- Build and own core platform capabilities, user\-facing experiences and backend services— delivering end\-to\-end features from requirements to production.
- Drive architecture and technical direction for integration\-heavy systems, helping the team make durable decisions around scalability, reliability, maintainability, and operational safety.
- Own reliability and production\-grade behavior, including safe shutdown and edge\-case handling, and proactively debug issues across distributed systems.
- Build secure, compliant integrations and user experiences, including stronger validation, security hardening, and privacy\-minded product changes.
- Deliver user\-facing UX improvements that reduce friction and increase clarity, ensuring internal and external tools are fast, intuitive, and accessible.
- Collaborate cross\-functionally and drive projects to completion, partnering with Product, QA, Design, and other engineering teams to deliver roadmap items and high\-severity fixes.
- Raise engineering standards through code review and technical mentorship, setting patterns for maintainability, observability, and robust integration design.
WhatYou’llBring
- Ability to write extendable, maintainable, and traceable code, with clear boundaries and clean abstractions in integration\-heavy codebases.
- Strong full\-stack experience, with deeper strength in backend and platform development and comfort contributing to UI work to deliver complete features.—ideally using Node.js, React, and TypeScript and/or Python—to deliver complete features.
- Experience with real\-world integrations, including webhooks, third‑party APIs, “installation/configuration” flows, and robust handling of failures and edge cases.
- Event‑driven architecture expertise, including Kafka (or similar) producers/consumers, delivery guarantees, and designing for operational safety in distributed systems.
- Solid grounding in computer science fundamentals, including data structures, algorithms, and software design, and the ability to apply that knowledge to production systems.
- Strong experience with non‑relational databases such as MongoDB and familiarity with in‑memory tools such as Redis, including practical indexing and query design.
- Good understanding of common cloud‑native architectural and code design patterns, and how they impact reliability, scalability, and cost.
- Comfort with production operations and observability, using logs, metrics, and traces to diagnose issues and guide improvements.
- Great sense of ownership and productive autonomy, with good discernment around trade‑offs between speed and quality, especially under time pressure.
- Ethical decision‑making and user‑first thinking, consistently putting the end user at the center of technical and product decisions.
- Respect for all people, an open mind, and an open heart. We pride ourselves on building inclusive environments because it’s the diversity of thought that builds great products.
- Good familiarity with AI Coding Agents and how to leverage them to build reliable software: Claude Code, Cursor, or similar tools.
Experience and education
- 3\+ years of experience as a Full Stack or Backend Developer preferably with JavaScript/TypeScript focus.
- 3\+ years of experience building web applications deployed to a cloud environment
- Bachelor's degree in Computer Science or related field
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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Asurion, 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 $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Asurion AI Hiring
Asurion has 3 open AI roles right now. They're hiring across AI Software Engineer, AI Agent Developer. Positions span Remote, US, San Mateo, CA, US, Nashville, TN, US.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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