Apetan Consulting
Apetan Consulting

Lead AI Security Automation Engineer

Boston, MA, US • Posted 10 hours ago • Updated 10 hours ago
Full Time
No Travel Required
On-site
Depends on Experience
Fitment

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Job Details

Skills

  • Lead AI Security Automation Engineer

Summary

Lead AI Security Automation Engineer


Team: Cyber Data & Analytics (CyberDNA)
Location: Hybrid or Remote, depending on location
Experience: 10+ years in Software Engineering; 4+ years in AI/ML/GenAI

Position Overview

Cyber Data & Analytics (CyberDNA) team is seeking a Lead AI Security Automation Engineer to lead the development of next-generation AI-powered applications, intelligent agents, and automation platforms supporting enterprise cybersecurity operations.

This is primarily a hands-on application software engineering role for someone with strong AI/ML expertise. The ideal candidate will have experience designing, building, and deploying production-grade applications that embed Generative AI, Large Language Models (LLMs), agentic AI, and automation into business workflows to improve efficiency, scalability, and decision-making.

The successful candidate will lead a team of AI engineers while remaining technically hands-on with application architecture, software development, AI integrations, cloud-native platforms, and production deployment.

Important: We are not looking for candidates whose primary experience is assessing AI security risks, conducting AI security reviews, or establishing AI security standards and policies. Security knowledge is a plus, but the priority is strong application development and the ability to build AI-powered solutions.

Key Responsibilities

  • Lead, mentor, and develop a high-performing team of AI and application software engineers.

  • Architect, develop, and deploy production-grade Generative AI applications, LLM-powered services, intelligent agents, and agentic workflows.

  • Embed AI capabilities into existing applications and business processes to improve operational efficiency and automation.

  • Design AI agent architectures, tool integrations, memory patterns, guardrails, orchestration, and workflow automation.

  • Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, semantic search, context engineering, and knowledge grounding.

  • Build scalable cloud-native applications and APIs using AWS, Azure, or Google Cloud Platform, leveraging containers, serverless technologies, and event-driven architectures.

  • Develop distributed systems and asynchronous processing solutions using messaging platforms and scalable data stores.

  • Implement AI evaluation, testing, monitoring, observability, and regression testing frameworks to ensure application quality and reliability.

  • Optimize AI applications for latency, throughput, scalability, context efficiency, and cost.

  • Integrate AI applications with enterprise platforms, APIs, data sources, and operational tools.

  • Use enterprise-approved AI coding assistants to accelerate development, refactoring, testing, and documentation while validating generated outputs.

  • Establish software engineering best practices for application reliability, testing, deployment, and maintainability.

  • Drive architectural decisions, conduct code reviews, and collaborate with cybersecurity, infrastructure, data engineering, and business stakeholders.

  • Lead complex technical initiatives while maintaining a strong hands-on development contribution.

Required Qualifications

  • 10+ years of professional software engineering experience.

  • 4+ years of hands-on experience developing AI, Machine Learning, or Generative AI solutions.

  • Proven experience building and deploying enterprise-grade applications and production software platforms.

  • Strong programming skills in one or more of Python, JavaScript/TypeScript, Go, Rust, or Java, with Python preferred for AI development.

  • Hands-on experience building LLM-powered applications, intelligent agents, and agentic AI workflows.

  • Experience with AI orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen.

  • Strong experience with RAG, embeddings, semantic search, vector databases, prompt engineering, and context management.

  • Strong application architecture, API development, integration, and distributed systems experience.

  • Experience with public cloud platforms such as AWS, Azure, or Google Cloud Platform.

  • Familiarity with containers, serverless computing, asynchronous processing, messaging, and event-driven systems.

  • Experience implementing automated testing, CI/CD pipelines, application monitoring, and production observability.

  • Hands-on technical leadership, including mentoring engineers and driving architecture and engineering decisions.

  • Experience using enterprise-approved AI-assisted development tools to improve software delivery and engineering productivity.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10513292
  • Position Id: 74123-12895-1793051375
  • Posted 10 hours ago
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