Digital AI Development Engineer
Position Overview:
APEX TK is looking for an amazingly talented Digital AI Development Engineer to join our team! In this role you will be part of Parsons' Federal Solutions 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.
What You'll Be Doing:
- 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
What Required Skills You'll Bring:
- 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
- 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
What Desired Skills You'll Bring:
- 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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