Senior AI Security Automation Engineer - full time

Role : Senior AI Security Automation Engineer ( R-794576)



Locations : Quincy, MA : Princeton, NJ : Boston, MA : Clifton, NJ

Job Type: Full-Time

Work Arrangement

Hybrid - 2 4 days per week in office , based on the organization's hybrid work policy.

Work Hours: 8:00 AM 5:00 PM local time



Additional Requirement: Occasional Level 2 3 escalation support for operational incidents.

Position Overview

Client team is seeking a Senior AI Security Automation Engineer to help build the next generation of cybersecurity data, analytics, and AI-powered platforms.

This role sits at the intersection of Artificial Intelligence, Cybersecurity, Data Engineering, and Full-Stack Software Development , with a focus on enabling secure, scalable, and governed AI adoption across the enterprise.

The engineer will work closely with Global Cyber Security, Infrastructure, and Enterprise Continuity teams to develop AI platforms, autonomous agents, security automation solutions, and data-driven applications that strengthen cyber resilience and transform cybersecurity operations.

Key Responsibilities

• Architect and deliver scalable, reliable agentic AI platforms for security workflows.
• Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool orchestration.
• Develop retrieval and context-engineering solutions using:
  • Embeddings
  • Semantic search
  • Grounding
  • Summarization
  • Prompt/version management
• Engineer cloud-native AI services across AWS, Azure, and GCP .
• Work with containers, serverless architectures, event-driven messaging, and distributed data stores.
• Optimize platform performance, scalability, latency, throughput, caching, context efficiency, and cost.
• Build secure, reusable APIs and integrations connecting AI capabilities with cybersecurity platforms and business processes.
• Establish AI evaluation, regression testing, monitoring, and observability frameworks.
• Define engineering standards for reliability, security, governance, and safe AI operations.
• Mentor junior engineers and provide technical leadership through architecture reviews and code reviews.
• Utilize enterprise-approved AI-assisted development tools for code generation, refactoring, testing, and documentation while validating outputs through secure coding practices and automated testing.
• Develop reusable automation and engineering patterns across the organization.

Required Skills & Experience

• Production experience architecting and deploying Generative AI / LLM solutions .
• Strong experience with agentic AI, intelligent agents, and enterprise AI tool integration .
• Strong software engineering and cloud-native application development experience.
• Experience with:
  • Containers
  • Serverless architectures
  • Distributed systems
  • Event-driven architectures
  • Asynchronous processing
  • Durable messaging
  • High-performance data access
• Hands-on RAG experience, including:
  • Embeddings
  • Semantic search
  • Knowledge grounding
  • Context engineering
  • Prompt optimization
  • Prompt lifecycle management
• Experience with AI evaluation, testing, monitoring, and observability.
• Strong API design and integration experience.
• Strong understanding of Responsible AI , data privacy, security, governance, resiliency, and risk management.
• Deep understanding of cybersecurity data sources including:
  • Endpoint
  • Network
  • Application
  • Cloud
  • System telemetry
• Experience with SIEM platforms and cybersecurity analytics.
• Strong knowledge of cybersecurity operations including:
  • Threat detection
  • Incident response
  • Threat hunting
  • Security analytics
  • Security automation
• Experience with CI/CD tools such as Jenkins, Harness, Spinnaker, or Argo CD .
• Strong programming/automation experience with:
  • Python
  • JavaScript/TypeScript
  • Rust
  • Go
  • Bash
  • PowerShell
• Proven ability to lead complex technical initiatives while remaining hands-on .
• Experience developing cybersecurity, analytics, or operational intelligence solutions.

Preferred / Additional Technologies

AI & Agentic Frameworks

• LangGraph
• Semantic Kernel
• CrewAI
• AutoGen
• LangChain

Data & Analytics

• Databricks
• Snowflake
• Spark
• Kafka
• Delta Lake
• Iceberg
• Airflow

AI/ML

• Vector databases
• Semantic search
• Enterprise RAG platforms
• MLOps
• LLMOps
• AI observability
• AI evaluation frameworks

Security

• Responsible AI
• Data governance
• Model risk management

Education & Experience

• Bachelor's or Master's degree in:
  • Computer Science
  • Software Engineering
  • Artificial Intelligence
  • Data Science
  • Cybersecurity
  • Related discipline
• 7+ years of professional software engineering experience.
• 3+ years developing AI, Machine Learning, or Generative AI solutions.
• Experience designing and deploying enterprise-scale applications and platforms .
• Experience developing cybersecurity, analytics, or operational intelligence solutions.

Ideal Candidate Profile

Looking for a senior, hands-on AI/software engineering leader who combines:

Generative AI + Agentic AI + Cloud Engineering + Cybersecurity + Software Engineering + Automation

The strongest candidates will have experience building production-grade AI/LLM platforms , not just using ChatGPT or other AI tools. They should also understand enterprise cybersecurity environments, SIEM/security data, cloud infrastructure, APIs, RAG, CI/CD, and AI governance .

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