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Ai Software Engineer Jobs (NOW HIRING)

Bishop Fox

AI Software Engineer

San Francisco, CA · On-site

Who You Are The Agentic AI Software Engineer - Cybersecurity Systems designs, develops, and deploys advanced AI-driven software solutions to enhance cybersecurity detection, response, analysis, and ...

Cottingham & Butler

AI Software Engineer

Dubuque, IA

Cottingham & Butler is seeking a highly motivated Software Engineer with deep AI expertise to join our IT team. This role is central to our mission of transforming how we deliver brokerage, claims ...

Bishop Fox

AI Software Engineer

San Francisco, CA

Who You Are The Agentic AI Software Engineer - Cybersecurity Systems designs, develops, and deploys advanced AI-driven software solutions to enhance cybersecurity detection, response, analysis, and ...

unitQ

AI Software Engineer

San Francisco, CA

About the Opportunity We're looking for an AI Software Engineer to lead features that use AI and conventional methods to intelligently analyze user feedback. You will work closely with fellow ...

Ford Motor Company

AI Software Engineer

Dearborn, MI · On-site

As an AI-focused Software Engineer in Marketing Enterprise Analytics, you will architect systems where autonomous agents navigate complex marketing business logic, utilize the Model Context Protocol ...

Knexus

AI Software Engineer (Remote)

Vienna, VA · On-site +1

We're looking for an experienced AI Software Engineer with 6-8 years of experience to join our AI applications team. This is a fully remote position for candidates in the continental U.S., with work ...

Cottingham & Butler

AI Software Engineer

Dubuque, IA · On-site

Cottingham & Butler is seeking a highly motivated Software Engineer with deep AI expertise to join our IT team. This role is central to our mission of transforming how we deliver brokerage, claims ...

Cottingham & Butler

AI Software Engineer

Dubuque, IA

Cottingham & Butler is seeking a highly motivated Software Engineer with deep AI expertise to join our IT team. This role is central to our mission of transforming how we deliver brokerage, claims ...

Numerator

Numerator is looking for a passionate AI Software Engineer to join our growing Machine Learning team . This is a unique opportunity where you will get a chance to work with an established and rapidly ...

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How much do ai software engineer jobs pay per year?

As of Jun 29, 2026, the average yearly pay for ai software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the typical day-to-day responsibilities of an AI Software Engineer?

AI Software Engineers typically spend their days designing, building, and optimizing machine learning models, writing code to support AI system integration, and analyzing large data sets for training algorithms. They frequently collaborate with data scientists, product managers, and other software engineers to align technical solutions with business goals. Regular responsibilities also include reviewing code, troubleshooting model performance, and staying up-to-date on the latest research in artificial intelligence. This role often involves a mix of independent technical work and team-based project collaboration, providing variety and opportunities for skill growth.

Which 5 jobs will survive AI?

AI Software Engineers are likely to continue to be in demand as they develop, maintain, and improve AI systems, requiring specialized skills in programming, machine learning, and data analysis. Jobs that involve complex problem-solving, creativity, emotional intelligence, and human interaction—such as healthcare professionals, educators, skilled trades, mental health counselors, and research scientists—are also expected to persist despite AI advancements. These roles often require nuanced judgment and interpersonal skills that AI cannot easily replicate.

What do AI software engineers do?

AI software engineers develop, implement, and optimize artificial intelligence models and algorithms for various applications. They work with machine learning frameworks, programming languages like Python, and data processing tools to create intelligent systems that can learn from data and improve over time.

What are the key skills and qualifications needed to thrive in the Ai Software Engineer position, and why are they important?

To thrive as an AI Software Engineer, you need a strong background in computer science, mathematics, and machine learning principles, often backed by a relevant degree and experience with programming languages like Python or C++. Familiarity with frameworks such as TensorFlow or PyTorch, and experience deploying models in cloud environments or obtaining certifications in AI/ML, are highly valued. Strong problem-solving abilities, communication, and teamwork are important soft skills to bridge technical gaps and collaborate effectively. These skills and qualities enable the design, development, and deployment of effective AI solutions in dynamic, results-driven environments.

What does an AI Software Engineer do?

An AI Software Engineer designs, develops, and maintains software applications that incorporate artificial intelligence and machine learning technologies. They work with algorithms, data models, and programming languages such as Python, TensorFlow, and PyTorch to build intelligent systems. Their responsibilities include data preprocessing, model training, optimization, and deployment. Additionally, they collaborate with data scientists and software engineers to integrate AI solutions into real-world applications.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position such as an AI research director, senior machine learning engineer, or AI executive, often found in large tech companies or specialized firms. These roles usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and sometimes leadership or strategic responsibilities.

What engineers make $500,000?

Senior AI software engineers, especially those with expertise in machine learning, deep learning, and large-scale systems, can earn $500,000 or more annually, often through a combination of base salary, bonuses, and stock options. High compensation is typically associated with experience, specialized skills, working at top tech companies, or in leadership roles within AI development teams.
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Ai Software Engineer jobs near you
Infographic showing various Ai Software Engineer job openings in the United States as of June 2026, with employment types broken down into 95% Full Time, 1% Part Time, 1% Temporary, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
AI Software Engineer

AI Software Engineer

Bishop Fox

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 15 days ago

Key responsibilities

  • Architect, implement, and maintain agent-based AI systems for autonomous cybersecurity tasks such as vulnerability analysis, threat detection, alert triage, and secure code review.

  • Utilize large language models to generate, review, and refine secure software components, scripts, detection logic, and test cases, implementing guardrails and validation frameworks for AI-generated outputs.

  • Develop and integrate scalable, secure APIs, microservices, and distributed systems to enable AI-powered security tools within enterprise environments and ensure robust system performance.

Job description

Bishop Fox is the leading authority in offensive security, providing solutions ranging from continuous penetration testing, red teaming, and attack surface management to product, cloud, and application security assessments. We've worked with more than a quarter of the Fortune 100, half of the Fortune 10, eight of the top 10 global technology companies, and all of the top global media companies. Our managed service platform, service innovation, and culture of excellence continue to gather accolades from industry award programs including Fast Company, Inc., SC Media, and others. For more than 16 years, we've been contributing and giving back to the security community. We've published more than 16 open source tools and 50 security advisories in the last five years alone. Learn more at bishopfox.com or follow us on social media.
Who You Are
The Agentic AI Software Engineer - Cybersecurity Systems designs, develops, and deploys advanced AI-driven software solutions to enhance cybersecurity detection, response, analysis, and automation capabilities. This role focuses on building and maintaining agent-based artificial intelligence systems capable of autonomously generating code, conducting security analyses, triaging alerts, identifying vulnerabilities, and recommending remediation strategies, with structured human oversight and validation.
The position requires the application of advanced knowledge in computer science, artificial intelligence, machine learning, secure software engineering, distributed systems, and cybersecurity principles. The role involves complex system design, secure AI integration, and the development of enterprise-grade security automation platforms.
What You Will Do
1. Design and Develop Agentic AI Systems for Cybersecurity
  • Architect and implement AI-powered systems that perform autonomous or semi-autonomous cybersecurity tasks, including vulnerability analysis, threat detection, alert triage, log analysis, and secure code review.
  • Design multi-agent architectures capable of orchestrating specialized AI agents (e.g., vulnerability scanning agents, log analysis agents, exploit pattern detection agents).
  • Develop retrieval-augmented generation (RAG) pipelines to enable AI systems to securely query internal knowledge bases, threat intelligence feeds, CVE databases, and security documentation.

2. AI-Assisted Secure Code Generation & Review
  • Utilize large language models (LLMs) to generate secure software components, scripts, detection logic, and test cases.
  • Review and refine AI-generated code to ensure compliance with secure coding standards (e.g., OWASP Top 10, secure SDLC practices).
  • Implement automated guardrails to detect insecure outputs, prompt injection vulnerabilities, model hallucinations, and data leakage risks.
  • Design validation frameworks to benchmark AI-generated security outputs against known vulnerability patterns.

3. Human-in-the-Loop AI Governance & Model Optimization
  • Design and implement reinforcement learning from human feedback (RLHF) workflows for cybersecurity use cases.
  • Develop evaluation metrics for AI accuracy in threat detection, vulnerability identification, and remediation recommendations.
  • Continuously refine prompt engineering strategies, model tuning parameters, and system architecture to improve security reliability and precision.
  • Implement explainability mechanisms to support auditability and defensibility of AI-driven security decisions.

4. Secure System Architecture & Integration
  • Develop and maintain APIs and microservices to integrate AI-powered security tools into enterprise platforms.
  • Architect scalable and fault-tolerant distributed systems to support real-time security event processing.
  • Deploy AI-enabled services within secure cloud environments (e.g., AWS, Azure, GCP) using containerization and orchestration technologies (Docker, Kubernetes).
  • Integrate AI systems with SIEM, SOAR, vulnerability management, and endpoint detection platforms.

5. Security Engineering & Threat Modeling
  • Conduct threat modeling for AI systems to identify adversarial risks, model exploitation vectors, and prompt injection vulnerabilities.
  • Implement secure authentication, authorization, encryption, and data governance controls.
  • Develop safeguards to prevent misuse of AI systems in exploit development or unintended security bypass scenarios.
  • Perform security reviews and penetration testing of AI-driven software components.

6. Testing, Validation & Performance Optimization
  • Design automated test pipelines for AI-driven security workflows.
  • Conduct adversarial testing to evaluate resilience against malicious inputs.
  • Monitor system performance metrics (latency, false positive rates, detection accuracy).
  • Optimize inference pipelines and distributed systems for reliability and scalability.

7. Documentation & Cross-Functional Collaboration
  • Produce detailed architectural documentation for AI security systems.
  • Collaborate with cybersecurity researchers, product teams, software engineers, and cloud architects to translate threat intelligence and security requirements into scalable AI-enabled solutions.
  • Provide technical guidance on AI governance, responsible AI deployment, and secure AI lifecycle management.

Your Experience
  • Required Education
    • Bachelor's degree or higher in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Cybersecurity, Information Security, or a closely related technical field.
  • Required Experience & Technical Skills
    • Strong foundation in algorithms, data structures, and object-oriented programming.
    • Proficiency in programming languages such as Python, Java, C++, or similar.
    • Experience developing AI or machine learning systems for security-related applications.
    • Experience working with large language models (LLMs) and prompt engineering techniques.
    • Experience with AI orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar).
    • Experience implementing secure software development lifecycle (SSDLC) practices.
    • Knowledge of cybersecurity concepts including vulnerability management, threat modeling, penetration testing, SIEM/SOAR platforms, and common attack vectors.
    • Experience deploying applications in cloud environments (AWS, Azure, or GCP).
    • Familiarity with containerization and orchestration tools (Docker, Kubernetes).
    • Experience building RESTful APIs and microservices architectures.
  • Preferred Qualifications
    • Master's degree in Computer Science, Artificial Intelligence, or Cybersecurity.
    • Experience designing AI systems for automated threat detection or exploit analysis.
    • Experience with reinforcement learning, fine-tuning, or model evaluation frameworks.
    • Experience integrating AI systems with cybersecurity tooling ecosystems.
    • Familiarity with NIST, ISO 27001, or similar security standards.

Our Values
We strive to live by our values every day, in support of our core tenets, which are to deliver the highest quality of work for our clients, quality of life for our team, and quality of business for our industry and our future.
  • Be Excellent to Each Other
  • Do the Right Thing
  • Do What You'll Say You'll Do
  • Get Better Together
  • Give a Sh*t

We offer a variety of benefits and perks, such as:
  • Generous Time Off and Company-Wide Holidays
  • Health Insurance options including Medical, Dental, Vision
  • Retirement; 401k matching for Traditional and Roth accounts in the US
  • Work From Home Support
  • Monthly allowance for cell phone and internet
  • Training Budget
  • Paid Parental Leave

Specialty Occupation Justification
The duties of this position require the theoretical and practical application of specialized knowledge in computer science, artificial intelligence, distributed systems, and cybersecurity engineering. The design and implementation of AI-driven, agent-based cybersecurity systems necessitate advanced understanding of algorithms, machine learning methodologies, secure system architecture, threat modeling, and secure coding standards. Such knowledge is typically acquired through completion of at least a bachelor's degree in a specific technical field such as Computer Science, Artificial Intelligence, or Cybersecurity.
The complexity of developing autonomous AI systems that analyze vulnerabilities, evaluate exploit patterns, and integrate securely with enterprise cybersecurity infrastructure requires a highly specialized educational background and cannot be performed without advanced technical training.
Bishop Fox is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. All new hires must pass a background check as a condition of employment.

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