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About Cogent
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Cogent is an Applied AI Lab building the next generation of AI agents for cybersecurity. AI has fundamentally changed how attacks happen, allowing malicious actors to operate at unprecedented speed and scale. Cogent’s "AI Taskforce" assesses petabytes of enterprise data to remediate these issues before critical breaches occur.
To stay at the cutting edge, we blend frontier research with real\-world execution. Alongside our core product work, Cogent Research serves as our applied AI lab, providing the research horsepower needed to make truly agentic security workflows a reality.
Since coming out of stealth, Cogent has experienced rapid growth. We partner with Fortune 500 companies to secure some of the most complex production environments in the world.
We’re backed by Greylock and we’ve built a team with the best minds in applied AI. Our team is comprised of people from:
- Top universities like Stanford, Berkeley, Penn, Duke, Carnegie Mellon, Waterloo
- Unicorn, high\-growth companies like Scale AI, Databricks, Stripe, Tesla, Coinbase
- World class cybersecurity experts from Wiz, Abnormal AI, Zscaler
- Preeminent research labs like Deepmind and SAIL
About the Role
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As we onboard our first design partners, Cogent is launching the world's first AI cyber taskforce, which is composed of AI agents capable of human\-caliber reasoning for cybersecurity tasks. We are looking for talented, ambitious AI/ML Engineers who are excited to build in the Applied AI space.
What You’ll Do \& Achieve
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- Architect and launch the world’s first AI Cyber Taskforce
+ Work closely with our design customers to design and launch our flagship AI agents that are capable of automating tasks in vulnerability management
+ Understand business goals, product and technology strategies, and customer requirements and implement business\-critical AI systems to achieve them
+ Identify appropriate datasets and data representations to support system development
+ Decompose existing enterprise security workflows into sub\-tasks that can be modeled as an autonomous system
+ Experiment with the latest advancements in long\-term reasoning and planning to design systems that allows Cogent to evolve the data flywheel of our AI products from initially highly supervised to eventually autonomous and managed by exception
- Build and extend Cogent’s Gen AI Platform
+ Implement reusable system components for ranking, retrieval and search systems powered by LLMs for agentic automation
+ Put in place frameworks to train, evaluate, and stress\-test ML systems, and extend improvements on Cogent’s Gen AI platform
+ Stay on top of and when appropriate, propose incorporating cutting edge developments in ML and Gen AI into Cogent’s AI systems
- Help create a robust engineering culture at Cogent
+ Onboard, support and uplevel future team members
+ Mentor and grow future junior team members
+ Actively contribute to Engineering Excellence, Operational Excellence and Recruiting initiatives
What You’ll Bring
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- Multiple years of relevant experience in developing and deploying AI\-driven systems, with a proven track record of architecting practical, production\-grade solutions that solve real\-world problems
- Expertise in machine learning, deep learning, and AI models, with a deep understanding of how to apply these technologies to build scalable, performant systems in production environments
- Experience with designing and deploying agentic systems and autonomous agents, as well as integrating these AI components into larger applications or products
- Ability to address and navigate real\-world scale and performance challenges, ensuring that AI models and systems are efficient, robust, and performant under production constraints
- Familiarity with cutting\-edge AI technologies, including reinforcement learning, natural language processing, computer vision, and large\-scale generative models
- Proven ability to work iteratively and collaborate with cross\-functional teams to evolve AI models and systems that meet evolving product needs and user expectations
- Passion for staying at the forefront of AI advancements, continuously learning and applying emerging techniques to improve product performance and drive innovation
For California Based Applicants
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The standard base salary range for this position is $100,000 \- $300,000 annually. Compensation offered will be determined by factors such as location, job level, job\-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We are committed to building an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
Salary Context
This $100K-$300K range is above the median for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At COGENT SECURITY, 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
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 $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($200K) sits 8% below the category median. Disclosed range: $100K to $300K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
COGENT SECURITY AI Hiring
COGENT SECURITY has 1 open AI role right now. They're hiring across AI Software Engineer. Based in New York, NY, US. Compensation range: $300K - $300K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 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
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