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About This Role
We're looking for a Senior Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you'll build the next generation of AI\-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents.This role is based in our New York City office with an office\-centric hybrid schedule.
The standard in\-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in\-office requirements.
What you'll achieve
- Design and build AI\-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence.
- Design and scale autonomous cloud agents that take on complex, multi\-step engineering tasks to reduce toil and enable engineers to focus on higher\-leverage work.
- Build and refine IDE, editor, and CLI integrations that make AI\-assisted development feel intuitive in engineers' daily work.
- Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent.
- Improve AI\-assisted code review workflows so engineers get faster, higher\-quality feedback before and during review.
- Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement.
### About you
- 5\+ years of working in large codebases
- Experience building developer tools, internal platforms, infrastructure, IDE/editor integrations, CLIs, or workflow automation.
- Hands\-on experience with AI\-assisted development tools (such as Cursor, Claude Code, or Codex), or extending coding agents, MCP\-based integrations, AI\-powered code review systems, or agent skill/tool ecosystems.
- Experience building evaluation and quality frameworks for AI\-generated outputs.
- Strong technical judgment and systems design skills, with the ability to make pragmatic tradeoffs in ambiguous or rapidly changing environments.
- Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision\-making.
At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
What we'll offer
Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
For this role, the estimated base salary range is between $202,000 \- $230,000\. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
- Mental health, wellness \& fitness benefits
- Career coaching \& support
- Inclusive family building benefits
- Long\-term savings or retirement plans
- In\-office culinary options to cater to your dietary preferences
These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
\#LI\-Hybrid \#LI\-AS2
About us
Asana is a leading platform for human \+ AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7\+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office\-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13\+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
Join Asana's Talent Network to stay up to date on job opportunities and life at Asana.
Salary Context
This $202K-$230K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 219 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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Asana, 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 $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($216K) sits 7% below the category median. Disclosed range: $202K to $230K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Asana AI Hiring
Asana has 3 open AI roles right now. They're hiring across AI Software Engineer. Positions span New York, NY, US, Hoboken, NJ, US. Compensation range: $223K - $282K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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