Technical Lead, AI-Native Software Engineering (hybrid) - 2025652

$151K - $250K San Jose, CA, US Senior AI Software Engineer

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About This Role

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The application window is expected to close on: 10/29/2026

Technical Lead, AI-Native Software Engineering (hybrid) - 2025652

  • hybrid role, some onsite activity required

Meet the Team

The Security Workflow Engineering team, as part of the Security& Trust Organization, is responsible for engineering and delivering tools that help discover, mitigate, and report on security engineering across every application, platform, and service that Cisco delivers to its customers. It is our responsibility to provide an end-to-end digital experience with automation to help engineering across Cisco.

At our core, we are a team of engineers, with a focus on AI assisted security tooling, committed to helping develop tools that strive to seamlessly integrate and support building security into the development workflow.

Your Impact

We're looking for a Technical Lead to set the technical direction across our team's full body of work. It's a role for someone whose depth of software engineering experience makes them the person the team turns to when an architectural decision actually matters.

You'll be front and center on the technology-heavy problems: the ones that need a strong, well-reasoned opinion, not just a functioning solution. You'll guide engineers on how to make sound technical and architectural choices, by bringing hard-won judgment that your reasoning holds up under scrutiny. You'll also work across team boundaries with other technical leaders, reasoning through shared problems and driving decisions that drive forward progress. This work moves fast, and you bring a real sense of urgency to it — treating technical debt and open decisions as things to resolve now, not eventually.

You will:

  • Set technical direction across the team's portfolio of work and be the person engineers escalate to when a decision genuinely needs deep expertise.
  • Take the lead on the hardest technical problems — the ones that call for a strongly reasoned, optimized, and defensible architecture.
  • Guide software engineers on making sound technical and architectural choices, sharing the judgment that comes from having made — and learned from — those choices many times before.
  • Collaborate with technical leaders on other teams to reason through cross-cutting problems and drive shared decisions forward, with urgency.
  • Stay hands-on enough to be credible: reviewing designs and code where it matters, not managing from a distance.

Who You Are

  • Software engineering is a passion for you, not just a skill you picked up — it shows in the depth and care behind your technical opinions.
  • You have vast, hands-on software engineering experience, and it shows in how quickly you can spot the right architecture for a problem versus one that will cause pain down the line.
  • You form strong, well-reasoned technical opinions and can defend them logically, while staying genuinely open to adapting to novel ideas for solving challenges.
  • You're comfortable being the person accountable for technical decisions, not just contributing an opinion among many.
  • You can guide and influence other engineers' technical judgment without formal authority over them.
  • You work well with other technical leaders who don't report to you, building enough credibility and trust that decisions get made rather than stalled.
  • You operate with a sense of urgency — you know the difference between a decision that deserves careful deliberation and one that's just sitting there costing the team time.

Minimum Qualifications

  • BS or MS degree in Computer Science, Computer Engineering, or a related technical field, or demonstrated equivalent experience.
  • Extensive, hands-on software engineering experience, with a track record of making architectural decisions for systems that mattered and held up.
  • Deep expertise in software engineering - design architecture, implementation, scale - sufficient to propose and defend highly optimized, well-reasoned technical designs under scrutiny.
  • Demonstrated experience guiding or mentoring other engineers on technical and architectural decision-making, without formal management responsibility.
  • Fluency in AI-native software development practices, since you'll be expected to model and guide the same judgment you're asking the team to develop.

Preferred Qualifications

  • Experience building tools in the security space — product/application security, threat intelligence, compliance/governance
  • Experience designing APIs, tools, or services that AI agents use directly (e.g., MCP servers or function/tool interfaces)
  • Experience setting up AI-native practices for an AI-native software engineering team.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:

The starting salary range posted for this position is $171,600.00 to $245,000.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:

  • 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
  • 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
  • Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
  • Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
  • 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
  • Additional paid time away may be requested to deal with critical or emergency issues for family members
  • Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

  • .75% of incentive target for each 1% of revenue attainment up to 50% of quota;
  • 1.5% of incentive target for each 1% of attainment between 50% and 75%;
  • 1% of incentive target for each 1% of attainment between 75% and 100%; and
  • Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$171,600.00 - $281,800.00

Non-Metro New York state& Washington state:

$151,300.00 - $250,900.00

  • For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.

Salary Context

This $151K-$250K range is above the median for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).

Role Details

Company Cisco
Title Technical Lead, AI-Native Software Engineering (hybrid) - 2025652
Location San Jose, CA, US
Category AI Software Engineer
Experience Senior
Salary $151K - $250K
Remote No

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 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Cisco, 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 in Demand for This Role

Python (18% of roles) Aws (10% of roles) Azure (8% of roles) Rag (7% of roles) Gcp (6% of roles) Pytorch (5% of roles) Claude (5% of roles) Kubernetes (4% of roles)

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 $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($201K) sits 9% below the category median. Disclosed range: $151K to $250K.

Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.

Cisco AI Hiring

Cisco has 24 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer. Positions span San Jose, CA, US, Milpitas, CA, US, San Francisco, CA, US. Compensation range: $172K - $431K.

Location Context

Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.

The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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

Based on 1,601 roles with disclosed compensation, the median salary for AI Software Engineer positions is $220,000. Actual compensation varies by seniority, location, and company stage.
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.
About 6% of the 9,079 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Cisco is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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