AI Integration Engineer

About UVS Infotech:

UVS Infotech is a Laurel, Maryland-based, IT System Integrator with expertise in Emerging Technologies: Artificial Intelligence, Machine Learning, Robotic Process Automation, Blockchain, Identity & Access Management, Identity Proofing

Position Description:

The AI Integration Engineer is responsible for designing, developing, and deploying end-to-end artificial intelligence (AI) and machine learning (ML) solutions to enhance operational efficiency, automation, and data-driven decision-making across enterprise functions. This role focuses on building scalable AI-enabled platforms that integrate with existing systems, transform structured and unstructured data into actionable insights, and support mission-critical business processes.

The position requires a blend of advanced AI/ML expertise, software engineering, data engineering, and systems integration capabilities. The individual will work collaboratively with cross-functional stakeholders to align AI solutions with strategic objectives, ensure compliance with cybersecurity and governance standards, and deliver measurable business value.

This role also supports continuous improvement through model optimization, system sustainment, and user enablement, ensuring long-term adoption and operational success of AI-driven capabilities.

Role and Responsibilities:

• Design, develop, train, validate, and deploy AI/ML models to address complex operational challenges.
• Build AI-driven applications for:
  • Document and Contract Analysis: Analyze historical documents to identify patterns, discrepancies, and optimization opportunities.
  • Energy Optimization: Develop predictive models to monitor and optimize energy consumption and system performance.
  • Operational Readiness Platforms: Implement predictive analytics and resource optimization tools for operational planning and response.
• Develop scalable, modular AI architectures that integrate with enterprise systems and workflows.
• Perform data acquisition, cleansing, transformation, and feature engineering from diverse data sources.
• Build and maintain ETL pipelines and data processing workflows.
• Apply advanced analytics and predictive modeling techniques to generate actionable insights
• Integrate AI solutions into existing enterprise environments, including legacy and modern platforms.
• Deploy solutions across cloud and hybrid infrastructures using containerization technologies.
• Develop APIs and interfaces for seamless system interoperability.
• Implement secure AI/ML pipelines aligned with industry cybersecurity standards (e.g., ISO 27001).
• Ensure data protection, confidentiality, and secure handling of sensitive information.
• Apply AI ethical principles and governance frameworks in all solution designs.
• Establish and maintain CI/CD pipelines for AI model development and deployment.
• Monitor model performance, conduct retraining, and manage version control.
• Automate testing, deployment, and infrastructure provisioning.
• Develop comprehensive system documentation, including technical guides and user manuals.
• Translate complex AI concepts into clear, user-friendly materials.
• Conduct regular training sessions to enable end users and stakeholders.
• Provide ongoing support, including bug fixes, performance tuning, and system upgrades.
• Monitor system performance and implement enhancements based on user feedback and evolving requirements.
• Drive innovation through continuous evaluation of emerging AI technologies.

Required Skills:

• Expertise in machine learning and deep learning techniques (supervised, unsupervised, reinforcement learning).
• Proficiency with frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
• Strong experience in predictive modeling, statistical analysis, and data science methodologies.
• Advanced programming skills in Python.
• Experience with backend frameworks such as Django and asynchronous processing tools like Celery.
• Familiarity with database systems such as PostgreSQL.
• Strong experience with data wrangling, feature engineering, and ETL pipeline development.
• Proficiency with big data tools such as Apache Spark, Databricks, and Hadoop ecosystems.
• Experience with cloud platforms such as AWS and Microsoft Azure.
• Hands-on expertise with containerization technologies (Docker, Kubernetes).
• Knowledge of deploying AI solutions in distributed and hybrid environments.
• Experience developing and integrating APIs (REST, GraphQL, MQTT).
• Ability to integrate AI solutions into enterprise and legacy systems.
• Knowledge of secure coding practices and cybersecurity standards (e.g., ISO 27001).
• Understanding of AI governance and ethical AI principles.
• Experience with CI/CD pipelines, version control (Git), and infrastructure-as-code.
• Familiarity with automated testing and deployment frameworks.
• Working knowledge of HTML, CSS, and JavaScript.
• Understanding of secure web application design principles.
• Strong analytical and problem-solving abilities.
• Excellent communication and technical documentation skills.
• Ability to translate complex technical concepts into business-friendly language.
• Collaborative mindset with experience working in cross-functional teams.

Education and Experience:

• Minimum of 5 10 years of experience in AI/ML development, software engineering, or data science roles.
• Proven experience designing and deploying AI/ML solutions in production environments.
• Hands-on experience with cloud platforms, data engineering pipelines, and enterprise system integration.
• Experience working in secure or compliance-driven environments is highly preferred.
• Prior experience with MLOps, DevSecOps, and scalable AI system deployment is strongly desired.
• Prior experience in Defense domain environments is preferred.