Security Research Engineering Technical Leader

$151K - $307K Austin, TX, US Mid Level Research Engineer

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Skills & Technologies

Kubernetes

About This Role

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The application window is expected to close on: 10/22/2026This is a remote role and work may be performed anywhere in the contiguous United States.

Meet the Team

We're the team behind the security of Cisco's platforms, tools, and applications. Our portfolio spans applications, networking platforms, cloud solutions, and automation platforms. We're AI-forward. We're building a framework that puts AI to work at every step, a framework that drives a risk-based Security Development Lifecycle and clears away the manual bottlenecks that slow security down, so security scales right alongside the business. We own software security across the full range of product technology in scope, spanning application, cloud, identity, data, and supply chain. We act as a strategic partner to Product Management, Engineering, and Product leadership. Together, we keep software security risk understood, managed, and aligned with Cisco's broader business risk posture.

Your Impact

As a Security Research Engineering Technical Leader, you are the security authority for the product portfolio. You are the person engineering and platform teams turn to when security, architecture, and delivery pressures collide. Earning that trust requires a sharp, risk-based instinct and the independence to act on it. You will be responsible for the full arc of portfolio risk, maintaining a current, data-backed view of security posture. You will translate threat trends, architectural shifts, and security debt into priorities that product and engineering leadership can act on, while advising and influencing across Product Management, Engineering, IT/Enterprise Operations, and Business Information Security Officer partners to align security priorities with business objectives. You will set the architecture bar, reviewing and approving secure designs across the portfolio, adapting"security by desig" and"security by defaul" to each context, and making architecture trade-off calls. You will lead threat modeling portfolio-wide, adjusting depth and technique to the system at hand, ensuring every model is defensible, evidence-based, and tied directly to design decisions. AI adds a new frontier, and you will meet it head-on by integrating AI securely into in-scope platforms, applying Software Security AI frameworks, and advocating for AI capabilities that strengthen security outcomes. You will threat-model and think like an attacker, coordinating Security SMEs in areas like cryptography and identity, and presenting prioritized lists of unmitigated security risks at release or delivery. Finally, you will define and lead all aspects of the security engineering metrics that drive the portfolio, including risk reduction, mean time to remediate, security debt, and developer adoption, turning data into sharper decisions.

Minimum Qualifications

  • Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related experience, or equivalent related work experience.
  • Proven experience leading threat modeling and secure design/architecture reviews for complex software systems, including AI- and LLM-enabled features.
  • Demonstrated experience interpreting SAST, DAST, and SCA results and translating findings into risk-based, evidence-backed remediation guidance.
  • Extensive experience integrating security controls into modern CI/CD pipelines and cloud-native environments, including Kubernetes and containers.
  • Validated ability to influence engineering and product leadership and drive security outcomes across teams without direct authority.

Preferred Qualifications

  • Depth in one or more specialized areas: identity and access management, cryptography, data security, application security, or software supply chain security (including SBOM generation, artifact signing, and SLSA-aligned practices).
  • Experience partnering with internal information technology, operations, or platform engineering teams on applications and workflow/automation platforms.
  • Experience defining and using security metrics to influence roadmap and investment decisions.
  • Advanced knowledge of emerging security threats, vulnerability research, and industry-standard security frameworks.
  • Relevant industry certifications such as CISSP, CSSLP, CCSP, or GIAC.

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 $151,600.00 to $222,400.00 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:

$186,900.00 - $307,800.00

Non-Metro New York state& Washington state:

$166,300.00 - $274,100.00

  • 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-$307K range is above the 75th percentile for Research Engineer roles in our dataset (median: $185K across 72 roles with salary data).

View full Research Engineer salary data →

Role Details

Company Cisco
Title Security Research Engineering Technical Leader
Location Austin, TX, US
Experience Mid Level
Salary $151K - $307K
Remote No

About This Role

Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.

The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.

Across the 11,520 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Cisco, this role fits into their broader AI and engineering organization.

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

What the Work Looks Like

A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

Skills Required

Kubernetes (5% of roles)

Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.

Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.

Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.

Compensation Benchmarks

Research Engineer roles pay a median of $252,000 based on 476 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($229K) sits 9% below the category median. Disclosed range: $151K to $307K.

Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.

Cisco AI Hiring

Cisco has 29 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Engineer, AI Product Manager. Positions span San Jose, CA, US, Austin, TX, US, Richardson, TX. Compensation range: $172K - $449K.

Location Context

AI roles in Austin pay a median of $208,000 across 317 tracked positions. That's 3% below the national median.

Career Path

Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.

From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.

This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.

What to Expect in Interviews

Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.

When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.

AI Hiring Overview

The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.

The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).

Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.

The AI Job Market Today

The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 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 476 roles with disclosed compensation, the median salary for Research Engineer positions is $252,000. Actual compensation varies by seniority, location, and company stage.
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
About 6% of the 11,520 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 Research Engineer positions include Senior Research Engineer, Research Scientist, ML Architect. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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