Drimva

Morgan Stanley

Agentic AI Developer, Cybersecurity

$140K–$195K

Baltimore, Maryland · On-site · Full-time · Posted Sep 29, 2026

Experience
10+ years of software development experience; preferably with Python and one or more additional languages.
Education
Bachelor degree in Computer Science, Software Engineering, Data Science or a related field, or equivalent practical experience.

About the job

Designs, builds, and supports enterprise AI applications and workflow automation, with a focus on secure, responsible delivery and improved productivity.

What you'll do

  • Develop AI-powered applications, agents, workflow automations, and Generative AI solutions using enterprise data and approved platforms.
  • Build Python services, APIs, integrations, and reusable components; participate in the full software delivery lifecycle.
  • Work with engineering, data, security, platform, cyber, and governance teams to deliver, evaluate, and support AI solutions.

What they ask for

  • Bachelor degree in Computer Science, Software Engineering, Data Science or a related field, or equivalent practical experience.
  • 10+ years of software development experience, preferably with Python and one or more additional languages.
  • Understanding of software engineering best practices, SDLC processes, source control, automated testing, and code review standards.
  • Working knowledge of Large Language Models, Generative AI concepts, prompt engineering, and AI-assisted development tools.

Nice to have

  • Awareness of retrieval augmented generation, vector search, agentic AI patterns, or AI orchestration frameworks.
  • Experience in financial services, cybersecurity, data analytics, cloud platforms, or enterprise AI platforms.

Pay

$140,000 and $195,000 per year (base salary)

Tools

Python, LLMs, Generative AI, APIs, retrieval augmented generation, vector search

AI focus

Builds and supports Generative AI applications, agents, and workflow automations using LLMs, prompt design, retrieval-based patterns, and enterprise data; contributes to responsible AI quality, governance, security, and operational readiness.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)