Join Sri Lanka’s Great Place to Work Awarded organization, Tech One Lanka!
We are an organization that celebrates the diversity of our teams, where everyone can be themselves and are empowered to do their best work. Our purpose is to build an empowered community with empathy and a growth mindset to build innovative solutions to achieve remarkable results. We foster a safe space for everyone to learn, grow, and have fun. This is why our people can’t believe that their work here is actually a job. That’s because innovation is at the heart of everything we do. Every day our people get to imagine new possibilities, take magnificent risks, fail spectacularly, and succeed in spaces no one has dared to venture into before
What’s in it for you:
Here at Tech One, you’ll have the opportunity to make an impact by contributing to our global projects and working with diverse talented individuals across our offices. We promote an always-learning culture and provide our people with vast opportunities for growth. Got any suggestions to make Tech One an even better place to work at? We have a team who listens; share your thoughts and contribute to the changes. Got the skills and right qualities to be part of our awesome team? Competitive remuneration awaits you!
The roll in nutshells
The AI Engineer is responsible for designing, developing, deploying, and maintaining scalable AI and machine learning solutions that address real-world business challenges. This role works closely with data scientists, data engineers, software engineers, architects, and business stakeholders to translate requirements into robust AI-powered systems.the position has a strong focus on the Microsoft Azure AI ecosystem, including Azure Machine Learning, Azure OpenAI Service, Cognitive Services, and Microsoft Fabric, and applies best practices in MLOps, Responsible AI, and production-grade model deployment.
Duties and responsibilities
- AI & Machine Learning Development
- Design, develop, train, evaluate, and optimize machine learning models, including traditional ML, deep learning, and Generative AI / LLM-based solutions.
- Select appropriate algorithms, architectures, and evaluation metrics based on business and technical requirements.
- Apply feature engineering, data preprocessing, and data augmentation techniques to improve model performance.
- Solution Design & Delivery
- Translate business problems and requirements into end-to-end AI solutions.
- Collaborate with architects and engineering teams to design scalable, secure, and maintainable AI systems.
- Clearly communicate technical concepts, model behavior, and results to both technical and non-technical stakeholders.
- Deployment & MLOps
- Deploy AI/ML models into production environments using Azure-native services.
- Implement and maintain MLOps practices including model versioning, CI/CD pipelines, monitoring, logging, and automated retraining.
- Ensure models are reliable, scalable, and performant in production.
- Model Monitoring & Maintenance
- Monitor deployed models for accuracy, drift, bias, and performance degradation.
- Lead or contribute to model retraining and improvement cycles based on monitoring insights.
- Troubleshoot and resolve issues in production AI systems.
- Responsible & Secure AI
- Apply Responsible AI principles throughout the model lifecycle, including fairness, transparency, privacy, and security.
- Conduct bias and fairness assessments and propose mitigation strategies.
- Ensure compliance with organizational and regulatory AI governance standards.
- Knowledge Sharing & Continuous Improvement
- Contribute to AI engineering best practices, standards, and reusable frameworks.
- Maintain clear and comprehensive documentation for models, data pipelines, and deployment processes.
- Stay current with advancements in AI/ML research, tools, and Azure AI services, and proactively share knowledge with the team.
Required Qualifications
- Strong proficiency in Python and common ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with Azure AI services (Azure ML, Azure OpenAI, Cognitive Services, Microsoft Fabric).
- Experience deploying and maintaining ML models in production. Solid understanding of MLOps, CI/CD, and cloud-native architectures.
- Knowledge of data processing, feature engineering, and model evaluation techniques.
- Familiarity with Responsible AI concepts such as fairness, bias, explainability, and security.
Experience & Qualifications
- 3–5 years of hands-on experience in AI/ML engineering, data science, or applied machine learning roles.
- Proven experience designing, training, and deploying machine learning models in production environments.
- 1+ year of experience working with cloud-based AI platforms, preferably within the Microsoft Azure AI ecosystem (Azure ML, Azure OpenAI Service, Cognitive Services, Microsoft Fabric).
- Practical experience with MLOps practices, including CI/CD pipelines, model monitoring, versioning, and retraining workflows.
- Experience collaborating with cross-functional teams (engineering, data, product, business stakeholders) to deliver AI-driven solutions.
- Exposure to Responsible AI practices, including bias detection, fairness checks, model explainability, and secure AI design.
Nice to Have
- Azure AI certifications (AI-900, AI-102, or equivalent).
- Experience with LLM orchestration, prompt engineering, or RAG-based systems.
- Exposure to data engineering tools or big data platforms.
- Experience working in Agile/Scrum environments.
Preferred Qualifications
- Microsoft certifications: MS-102, MS-700, SC-300, MD-102 (all strongly preferred at this level); MS-900, SC-400, and AI-900 or Copilot-related credentials are a plus
- Experience operating at a senior level within a Microsoft MSP/LSP environment, managing concurrent multi-customer engagements and contributing to practice-level decisions
- Deep familiarity with Microsoft 365 licensing constructs on E3/E5, frontline worker SKUs, Copilot add-ons, CSP commercial structures, and license optimization advisory to enable confident licensing conversations during pre-sales
- Working knowledge of Microsoft security fundamentals relevant to M365, including Defender for Office 365, basic Entra ID security posture, and M365 compliance center
How to get in touch with us:
Address: Tech One Global Lanka (Pvt) Ltd, No:185/4, Havelock Road, Colombo 05
E-mail your CV to hr@techoneglobal.com along with the contact details of two non-related referees