Technical AI Requirements Systems Engineer

General Dynamics

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Annapolis Junction, MD
Salary
$170,000–$230,000 / yr
Posted
73 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $200k
$133k $240k
below market most similar roles pay here above market

This role pays more than 66% of similar roles. Most pay $147,925–$214,000 — the blue band above. At the midpoint, this role pays about $200k versus about $181k for comparable roles.

Based on 240 similar postings.

Employer

About General Dynamics

General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.

General Dynamics currently has 1377 open roles on FindRole.

Listed pay typically runs $124,093–$150,385 across 1184 roles with salary data.

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At a glance

TL;DR · Technical AI Requirements Systems Engineer

The Technical AI Requirements Systems Engineer joins the IT Infrastructure and Operations team to support the integration of AI-enabled capabilities into enterprise applications. This role involves performing hands-on technical execution, including low-level requirements definition and functional validation of new features. You will collaborate with customers, systems engineers, and developers to elicit, analyze, and document detailed functional requirements, converting them into actionable Jira user stories and epics. Key technical skills include familiarity with Java or JavaScript frameworks, RESTful microservices, and Amazon Web Services cloud architecture. You will serve as a technical liaison, evaluating AI architectures and model performance while identifying practical opportunities to apply emerging machine learning advancements. The work focuses on solving complex problems by ensuring seamless integration of AI-driven solutions into existing software architectures.

What you'll do

  • Perform hands-on technical execution and low-level requirements definition for AI-enabled enterprise applications.
  • Elicit, analyze, and document detailed functional requirements from customers to create technical specifications.
  • Translate high-level requirements into actionable Jira user stories and epics for development teams.
  • Conduct functional testing of new application features to ensure mission-driven software capabilities.
  • Serve as a technical liaison to present AI approaches and implementation tradeoffs to technical and non-technical stakeholders.
  • Identify practical opportunities to apply emerging AI/ML capabilities to existing enterprise software architectures.
  • Coordinate the design and development of AI-driven solutions from initial conception through to deployment.
  • Evaluate AI architectures and assess model performance to identify system-level integration tradeoffs.

What we're looking for

  • Must possess an active Top Secret SCI with Polygraph security clearance.
  • Must be a US citizen.
  • Must have a Bachelor of Arts or Bachelor of Science degree.
  • Must have 8+ years of related experience.
  • Must have familiarity with Java or JavaScript frameworks, RESTful microservices, and AWS cloud architecture.
  • Must be able to elicit, analyze, and document functional requirements and convert them into technical specifications.
  • Must be able to translate high-level requirements into Jira user stories and epics.
  • Must have experience conducting functional testing of application features.
  • Must be able to serve as a technical liaison to collaborate with cross-functional teams and stakeholders.
  • Must have awareness of modern AI/ML advancements to identify practical opportunities for enterprise applications.
  • Experience designing or refining technical artifacts specifically for AI integration (preferred).
  • Ability to evaluate AI architectures, assess model performance, and identify system-level integration tradeoffs (preferred).
  • Ability to coordinate the design and development of AI-driven solutions from conception to deployment (preferred).

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