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About This Role
About Delinea:
Delinea is a pioneer in securing human and machine identities through intelligent, centralized authorization, empowering organizations to seamlessly govern their interactions across the modern enterprise. Leveraging AI\-powered intelligence, Delinea’s leading cloud\-native Identity Security Platform applies context throughout the entire identity lifecycle – across cloud and traditional infrastructure, data, SaaS applications, and AI. It is the only platform that enables you to discover all identities – including workforce, IT administrator, developers, and machines – assign appropriate access levels, detect irregularities, and respond to threats in real\-time. With deployment in weeks, not months, 90% fewer resources to manage than the nearest competitor, and a 99\.995% uptime, Delinea delivers robust security and operational efficiency without compromise. Learn more about Delinea on Delinea.com, LinkedIn, X, and YouTube.
Join our passionate, global team at Delinea and help us make the world a safer and more secure place. Our success is driven by world\-class product leadership, outstanding engineers, and strategic investment from TPG. We value diversity, innovation, and a culture of respect and fairness. If you're ready to push boundaries and challenge the status quo in security, we want to hear from you.
Apply today to help us achieve our mission.
### Summary:
AI agents are appearing across the enterprise faster than anyone can keep track of them, and you cannot secure what you cannot see. In this role you will build the capabilities that find AI agents wherever they run, across cloud platforms and on endpoints, and assess their security posture so the rest of our AI security platform can govern them. This role will report directly into our Director of Engineering, Securing AI.
### What You'll Do:
- Build AI agent discovery on top of Delinea's existing cloud discovery rather than standing up a separate inventory, covering Microsoft Azure today and expanding to AWS and Google Cloud as the platform adds those clouds.
- Build discovery for AI agents running on endpoints, a newer surface for the team.
- Assess the security posture of discovered agents: how they are configured, what they can access, and where they create risk.
- Feed discovered agents and their context into our identity and attribution layer so they can be governed.
- Partner closely with the platform teams whose discovery services your work builds on.
### What You'll Need:
- Typically 8 or more years building production cloud or SaaS backend systems.
- Hands\-on experience with cloud provider APIs (Azure, AWS, or Google Cloud) and asset discovery or inventory systems.
- Experience extending or integrating with an existing platform, not only greenfield builds.
- Strong skills in a modern backend language such as C\#, Go, Java, or Python.
- Ability to break down complex, ambiguous problems and select sound technical approaches with limited direction.
### We'd Love to See:
- Experience with endpoint agent or device management technologies.
- Background in security or posture management such as CSPM or CIEM.
- Familiarity with AI agent frameworks and how agents authenticate and act.
For this Job, Delinea is not considering candidates that need any type of US work authorization now or in the future. This includes, but is not limited to: F1\-OPT, F1\-CPT, H\-1B, TN, L\-1, J1, etc.
Why work at Delinea?
- We're passionate problem\-solvers helping the world's largest organizations protect what matters most: their human and machine identities.
- We invest in people who are smart, self\-motivated, and collaborative.
- What we offer in return is meaningful work, a culture of innovation and great career progression.
At Delinea, our core values are STRONG and guide our behaviors and success:
- Spirited \- We bring energy and passion to everything we do
- Trust \- We act with integrity and deliver on our commitments
- Respect \- We listen, value different perspectives, and work as one team
- Ownership \- We take initiative and follow through
- Nimble \- We adapt quickly in a fast\-changing environment
- Global \- We embrace diverse people and ideas to drive better outcomes
We believe weaving these core values into our day\-to\-day actions, and our process for hiring, evaluating, and promoting employees, helps us cultivate a work environment that embraces collaboration and camaraderie.
We take care of our employees. We offer competitive salaries, a meaningful bonus program, and excellent benefits, including healthcare insurance, as well as pension/retirement matching, comprehensive life insurance, an employee assistance program, time off plans, and paid company holidays.
*Delinea is an Equal Opportunity and Affirmative Action employer and prohibits discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.*
*Upon conditional offer of employment, candidates are required to complete comprehensive criminal background check, verification of education, and verification of employment, per employment policy. In addition, all publicly posted social media sites may be reviewed.*
Compensation Range: $129K \- $162K
Salary Context
This $129K-$162K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Delinea, 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. This role's midpoint ($145K) sits 34% below the category median. Disclosed range: $129K to $162K.
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.
Delinea AI Hiring
Delinea has 6 open AI roles right now. They're hiring across AI Product Manager, AI Software Engineer, AI/ML Engineer. Based in Redwood City, CA, US. Compensation range: $162K - $220K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 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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