Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com
Job DescriptionWe are looking for an AI Engineer with hands-on experience designing and deploying scalable AI solutions. In this role, you will be part of a cross-functional team working on cutting-edge projects involving Retrieval-Augmented Generation (RAG), agentic frameworks, and end-to-end MLOps workflows.
You’ll play a key role in developing AI applications using tools like LangChain, CrewAI, and Google ADK, while applying advanced prompt engineering techniques and ensuring robust monitoring and performance tracing. Your collaboration with other engineering will help align innovative AI systems with broader development goals.
What is this position about?
- Analyze business problems and design AI solutions from scratch, including architecture, approach selection, and technical feasibility assessment.
- Design, develop, and deploy production-ready AI solutions with focus on scalability and reliability.
- Implement Retrieval-Augmented Generation (RAG) systems and fine-tuning techniques.
- Build and integrate AI frameworks and agentic systems to solve complex business problems.
- Apply advanced prompt engineering techniques and output post-processing strategies.
- Design and implement MLOps/LLMOps pipelines including CI/CD, model versioning, and monitoring.
- Lead end-to-end project delivery and mentor junior engineers.
- Work with transformer-based models and optimize LLM integration patterns.
- Design APIs, microservices, and event-driven architectures for AI systems.
- Collaborate across teams to translate AI capabilities into business value.
- Stay current with AI trends and contribute to best practices
- 4+ years total experience with at least 1 year as a Data Scientist and remaining years in ML/AI Engineering or MLOps roles.
- Proven experience working with early LLM architectures (BERT, RoBERTa, GPT-2, T5, or similar transformer models).
- Demonstrable track record of deploying LLM-based models to production environments.
- Proven ability to design AI solutions from scratch given business problems, including architecture design and approach selection.
- Expert-level Python programming and strong software engineering fundamentals.
- Experience with Azure cloud services and containerization for AI/ML workloads.
- Hands-on experience with MLOps tools and practices (model deployment, monitoring, experiment tracking).
- Strong understanding of both data science methodologies and production system design.
- Experience with version control (Git) and Agile/Scrum development practices.
- Excellent communication and stakeholder management skills.
- Ability to lead projects independently and mentor team members.
Additional Information
Our Perks and Benefits:
📚 Learning Opportunities:
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
- English lessons to support your professional communication.
👩🏫 Mentoring and Development:
Career development plans and mentorship programs to help shape your path.
🎁 Celebrations & Support:
- Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
- Company-provided equipment.
⚖️ Flexible working options to help you strike the right balance.
