Agentic AI Engineer

DeepSeas

$120K — $150K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong Python (or equivalent modern language) engineering skills
  • Deep understanding of language performance and internals like GIL and concurrency tradeoffs
  • Proven experience building production-grade AI agents that can scale
  • Thorough understanding of LLMs and agentic systems
  • Strong context engineering skills for effective LLM use
  • Experience with large-scale high-volume data workflows
  • Bachelor's degree in Computer Science/Engineering or equivalent

Responsibilities

  • Design and develop advanced agentic systems for cybersecurity
  • Handle large volumes of security event data efficiently
  • Ensure systems operate resiliently in noisy environments
  • Continuously evolve systems in response to new threats
  • Optimize performance, reliability, and ensure effective failure handling
  • Engineer robust data ingestion pipelines for LLMs
  • Rapidly iterate through the hypothesis, build, test, validate cycle

Benefits

  • Remote work flexibility
  • Opportunity to work with cutting-edge AI technologies
  • Involvement in innovative cybersecurity solutions
  • Access to a small, agile team environment
  • Focus on real-world impact and system performance
Full Job Description
Agentic AI Engineer

Department: Threat Management: Strategic Services

Employment Type: Full Time

Location: Remote - United States

Description

We're a small fast-moving team building AI Agents to solve real-world cybersecurity challenges - things like threat detection, log analysis, and incident response automation. This isn't about flashy demos. We care deeply about correctness, reliability, and systems that actually perform under pressure. We're looking for a talented engineer with expertise taking complex systems from design all the way to production. The right candidate is excited to tackle difficult challenges using a blend of out-of-the-box thinking and proven software engineering best practices.

Key Responsibilities

What will you do?Design, develop, and productionize advanced agentic systems that:
  • Handle large volumes of security event data
  • Operate with resilience in noisy, real-world environments
  • Continuously evolve as new attack patterns and tools emerge
  • Improve and harden existing agentic systems
  • Work with LLMs in production environments, not just prototypes
  • Engineer robust context pipelines for large-scale data ingestion and reasoning
  • Optimize systems for performance, reliability, and failure handling
  • Evaluate and integrate new agent frameworks, tools, and approaches
  • Rapidly hypothesize -> build -> test -> validate -> iterate


Skills, Knowledge, and Expertise

What do you need to succeed?
Must-have:
  • Strong Python (or equivalent modern language) engineering skills.
  • Deep understanding of language performance and internals (eg. GIL, concurrency tradeoffs, memory constraints).
  • Proven experience building production-grade AI agents. Not just demos. Systems that run, recover, and scale.
  • Thorough understanding of LLMs and agentic systems. You understand how they actually work under the hood.
  • Strong context engineering skills. Able to curate, compress, and structure large datasets for
    effective LLM use.
  • Experience evaluating, testing, and monitoring agents and LLM interactions using the latest
    techniques or frameworks.
  • Experience handling large-scale high-volume data workflows.
  • Portfolio of shipped work (GitHub, case studies, or equivalent).
  • Bachelor of Computer Science/Engineering or above.

Nice-to-have
  • Experience with cybersecurity tools (CrowdStrike, Splunk, Mandiant, etc.)
  • Familiarity with multiple agent frameworks (Claude Agent SDK, LangGraph, AutoGen, custom systems, etc.)
  • Experience evaluating tradeoffs between frameworks vs. custom orchestration.


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