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Open nowPosted 3 days agoWe saw it 107 min after it went up

Mid-Level Artificial Intelligence (AI) Engineer

Global Dimensions, LLC53 open roles

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Your applicationOpen nowMid-Level Artificial Intelligence (AI) EngineerGlobal Dimensions, LLC · Updated per job

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Global Dimensions, LLC's own form.

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. Global Dimensions, LLC postings stay open a median of 32 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 3 days ago

Global Dimensions, LLC median: 32 days open

The posting

Global Dimensions is currently seeking a highly skilled and innovative Mid-Level Artificial Intelligence (AI) Engineer to support mission-critical application development for an Intelligence Community (IC) customer in Annapolis Junction, Maryland; Washington, DC; or Reston, Virginia. The successful candidate will design, prototype, develop, and deploy advanced AI-enabled applications that enhance operational capabilities, streamline workflows, and support mission-driven decision-making.

The Mid-Level AI Engineer will leverage expertise in generative AI, agentic AI frameworks, prompt engineering, full-stack development, and modern cloud-native technologies to deliver secure, scalable, and reliable software solutions. This position requires strong technical proficiency in Next.js, React, TypeScript, Python, FastAPI, PostgreSQL, OpenSearch, Docker, and OpenShift, along with experience integrating AI capabilities into enterprise applications. The ideal candidate will demonstrate sound engineering judgment, strong problem-solving abilities, and the ability to collaborate with technical teams and mission stakeholders to deliver innovative AI solutions.

Essential Job Functions:

Design, prototype, develop, and deploy AI-enabled applications and solutions aligned with customer requirements, operational objectives, and existing enterprise application environments.

Collaborate with stakeholders to identify opportunities for integrating generative AI and agentic AI capabilities into mission-critical workflows and applications.

Design, develop, implement, and maintain full-stack applications using Next.js, React, TypeScript, FastAPI, Python, PostgreSQL, OpenSearch, and other approved technologies.

Develop and integrate generative AI frameworks, large language models (LLMs), and AI-powered services to support intelligent automation, data processing, and mission-focused applications.

Design and implement agentic AI solutions, including tool integrations, context management, agent orchestration, and communication between AI agents and external systems.

Develop, evaluate, and refine prompts and prompt management strategies to improve AI application accuracy, consistency, reliability, and performance.

Utilize Pydantic for Python and Zod for TypeScript to implement robust data validation, enforce application schemas, and maintain data integrity.

Develop and maintain backend services and RESTful APIs to support application functionality, AI integrations, and communication between frontend and backend components.

Design and optimize PostgreSQL databases and OpenSearch integrations to support efficient data storage, retrieval, indexing, and application performance.

Build, configure, and maintain Docker images and containerized applications, including writing Dockerfiles, managing dependencies, and troubleshooting container-related issues.

Deploy, configure, monitor, and troubleshoot applications within OpenShift and Kubernetes-based environments to support secure and reliable application delivery.

Investigate, diagnose, and resolve production issues across user interfaces, backend services, databases, AI integrations, and application deployment environments.

Collaborate with customers, product owners, software engineers, and mission stakeholders to clarify requirements, identify technical dependencies, evaluate implementation approaches, and estimate development efforts.

Participate in technical design discussions, architecture reviews, and code reviews to promote software quality, maintainability, security, and adherence to engineering best practices.

Develop and maintain automated tests, technical documentation, and software development artifacts to support application reliability, maintainability, and continuous improvement.

Work closely with development, operations, and cybersecurity teams to ensure AI-enabled applications meet mission requirements, performance expectations, and applicable security standards.

Required Skills:

Due to the sensitivity of customer related requirements, U.S. Citizenship is required.

Active Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance with an active Counterintelligence (CI) Polygraph is required.

Nine (9) years of relevant professional experience in computer science, data science, software engineering, or a closely related technical field with comparable responsibilities and scope.

Education may substitute for professional experience as follows: A bachelor's degree may substitute for four (4) years of experience, and a master's degree may substitute for six (6) years of experience.

Demonstrated proficiency with at least one generative AI development framework, such as LangChain, Haystack by deepset, LlamaIndex, or a comparable framework.

Strong expertise in prompt engineering, prompt optimization, and prompt management, including developing effective prompts for generative AI applications.

Hands-on experience designing and developing agentic AI solutions, including Model Context Protocol (MCP), AI tool development, context engineering, and agent-to-agent (A2A) communication.

Strong proficiency in React.js and TypeScript, including functional components, React hooks, reusable component architecture, state management, and API integration.

Demonstrated experience developing and maintaining backend services and RESTful APIs using Node.js or Python.

Proficiency with PostgreSQL, including relational database modeling, SQL development, schema migrations, indexing, and query performance optimization.

Hands-on experience with Docker and containerized application development, including writing Dockerfiles, building container images, configuring environments, and troubleshooting containers.

Understanding of full-stack application architecture, API integration, data validation, and modern software development practices.

Strong analytical, problem-solving, and technical communication skills, with the ability to translate customer requirements and business objectives into clear, actionable technical specifications.

Ability to collaborate effectively with software engineers, AI developers, product owners, and mission stakeholders in a fast-paced, mission-focused development environment.

Desired Skills:

Experience designing, developing, or deploying applications using Amazon Web Services (AWS) products and cloud services.

Experience implementing AI observability, monitoring, evaluation, and performance tracking using platforms such as Langfuse or LangSmith.

Hands-on experience using agentic AI coding tools and development environments, such as OpenAI Codex, to support software engineering workflows.

Experience developing AI-enabled applications using the Next.js AI SDK and FastMCP.

Familiarity with software development supporting the U.S. Department of Defense and Intelligence Community.

Experience working in Linux environments and familiarity with Kubernetes concepts, container orchestration, and OpenShift application deployments.

Demonstrated experience improving application security, accessibility, performance, scalability, and reliability.

Experience working in an Agile software development environment, including collaboration with product management, engineering, operations, and cybersecurity teams.

Familiarity with secure AI development practices, automated testing, software quality assurance, and modern DevSecOps methodologies.

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