Senior AI Engineer
Data Edge
ai-engineering
machine-learning-engineering
senior-ai-engineer
ai-solutions-development
ai-ml-infrastructure
senior-ai-engineering
senior-lead-ai-engineer
senior-ai-software-engineer
senior-ai-ml-engineer
senior-applied-ai-engineer
senior-ai-analytics-engineer
senior-staff-ai-engineer
ai-assisted-engineering
Job details
- Company
- Data Edge
- Location
- Romania
- Remote
- Yes
- Field
- Data
- Source
- via Himalayas
Posted
June 20, 2026
Is the job expired?
About this role
Senior AI Engineer
We are looking for a Senior AI Engineer who will lead the design, development and deployment of AI-driven solutions that enhance business operations and deliver measurable value. You will work across the full AI lifecycle, from data processing and model development to enterprise integration and production optimisation, while promoting AI-assisted engineering best practices.
Key Responsibilities:
AI Engineering & Solution Development
- Design, build, and maintain scalable AI and machine learning solutions for enterprise applications.
- Develop and optimise document intelligence, data extraction, and intelligent automation workflows.
- Integrate AI models and services into existing business platforms and operational systems.
- Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
- Ensure AI solutions are reliable, secure, and aligned with organisational standards.
AI-Assisted Engineering & Innovation
- Leverage AI-assisted development tools to accelerate software delivery, testing, and optimisation.
- Apply advanced AI techniques to improve automation, model accuracy, and operational efficiency.
- Drive the adoption of AI-assisted engineering practices across development teams.
- Evaluate and implement emerging AI technologies to enhance business capabilities and delivery outcomes.
- Promote the responsible, ethical, and secure use of AI in accordance with enterprise policies and governance frameworks.
- Monitor and maintain AI model performance throughout the lifecycle.
- Implement model validation, performance measurement, and continuous improvement processes.
- Ensure compliance with AI governance, security, and data protection requirements.
- Support scalable AI architectures using cloud-native technologies and services.
- Contribute to DevOps and MLOps practices for efficient deployment and operational management.
Required Skills & Experience:
- Proven experience designing, developing, and deploying AI and machine learning solutions in production environments.
- Strong proficiency in Python and experience with APIs, data processing frameworks, and AI development libraries.
- Experience with document intelligence, intelligent automation, and data extraction technologies.
- Solid understanding of machine learning model validation, performance evaluation, monitoring, and governance.
- Experience integrating AI capabilities into enterprise-scale applications and platforms.
- Knowledge of cloud-based AI services and scalable distributed architectures.
- Familiarity with Agile delivery methodologies and DevOps/MLOps practices.
Analytical & Professional Skills:
- Strong problem-solving and analytical capabilities.
- Ability to work collaboratively with technical and business stakeholders.
- Excellent communication and documentation skills.
- Commitment to continuous learning and staying current with AI industry trends and emerging technologies.
Originally posted on Himalayas
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