Digital AI Development Engineer

MTSI is looking for a talented Digital AI Development Engineer to join our team! In this role you will be part of our team providing Systems Engineering Technical Assistance to the Ground-based Midcourse Dense (GMD) Product Office under the Teams-Next Missile Defense Systems Engineering (TN-MDSE) contract managed by the Missile Defense Agency.

Job Responsibilities:
Design and implement AI pipelines for data ingestion, processing, and model deployment using frameworks like LangChain and Open WebUI
Develop and manage embeddings databases to support semantic search, recommendation systems, and other AI-driven applications
Integrate AI solutions with cloud platforms such as Azure Foundry to ensure scalability, reliability, and security
Collaborate with cross-functional teams to identify requirements and deliver AI solutions tailored to business needs
Optimize AI workflows for performance and efficiency, ensuring seamless integration with existing systems
Stay updated on the latest advancements in AI tools, frameworks, and methodologies to continuously improve pipeline performance
Document processes, workflows, and best practices for AI pipeline development and maintenance

Required Qualifications:
Bachelor's degree in computer science, Engineering, or a related STEM field
3+ years of related work experience
Working understanding of AI pipelines, including data processing, model deployment, and integration
ship and an Active Secret Clearance
Understanding of frameworks such as LangChain, Open WebUI, and embeddings databases
Strong programming skills in Python or similar languages, with a focus on AI and data processing libraries
Ability to work independently while collaborating effectively with team members.
Excellent problem-solving skills and attention to detail

Desired Qualifications:
Experience with cloud platforms like AWS, Bedrock, SageMaker, or Azure Foundry for AI solution deployment
Familiarity with semantic search and recommendation systems
Knowledge of distributed systems and scalable architectures for AI pipelines
Experience with containerization tools like Docker and orchestration platforms like Kubernetes
Understanding of MLOps practices for continuous integration and deployment of AI models
Strong written and verbal communication skills to document and present technical solutions
Solid understanding of full-stack development principles, including front-end technologies (HTML, CSS, JavaScript, React, Angular, or Vue.js) and back-end technologies (Python, Node.js, Java, Go) with relevant frameworks (Django, Express.js, Spring Boot, Gin)
Experience in designing, implementing, and managing relational (MySQL, PostgreSQL) or NoSQL (Mongo DB) databases
Experience developing and consuming RESTful APIs
Demonstrated ability to build and maintain CI/CD pipelines using tools like Jemkins, GitLab CI, CircleCI, or similar, and integrating Terraform and Ansible for automated deployments
Experience with cloud monitoring and logging tools (such as Prometheus, Grafana, ELK Stack, CloudWatch, Azure Monitor, Google Cloud Logging)
Understanding of software architecture patterns, design principles, and security best practices for cloud environments and web applications
Strong troubleshooting and problem-solving skills across the entire technology stack
Experience working in an Agile development environment and collaborating effectively with cross-functional teams
Ability to clearly and concisely document infrastructure, configurations, and deployment processes
Experience with Linux and/or Windows system administration
Motivated and customer oriented

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