Senior AI Engineer

Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

• →Deep knowledge of AI and ML frameworks, with a focus on NLP, predictive modeling, data analysis, and generative AI.
• →Design, build, and deploy advanced Machine Learning and Generative AI solutions on AWS Bedrock, with emphasis on Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), and large-scale search.
• →Integrate and optimize foundation models on AWS Bedrock for enterprise use cases, ensuring scalability, security, and compliance in dedicated AWS environments.
• →Collaborate with data scientists, data engineers, and product teams to transform complex problems into cloud-native, production-ready AI solutions on AWS.
• →Run experiments, explore novel algorithms, and leverage AWS Generative AI and Bedrock capabilities to maximize performance, user experience, and business outcomes.
• →Ensure the adoption of ethical and responsible AI practices across all solutions.

Must-have Skills

• →5+ years of hands-on experience in AI/ML development and deployment.
• →Strong expertise in Generative AI, LLMs, AI Agents, and RAG architectures.
• →Proven experience designing and deploying solutions on AWS Bedrock.
• →Strong programming skills in Python
• →Experience in cloud-native architectures and enterprise-scale solutions.
• →Familiarity with data pipelines, vector databases, and large-scale search systems.
• →Demonstrated ability to collaborate with cross-functional teams (scientists, engineers, product managers).
• →Commitment to responsible and ethical AI practices.

Nice-to-Have Skills

• →AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.
• →Experience with LangChain, llama-index, or similar orchestration frameworks for RAG/LLM pipelines.
• →Knowledge of multi-cloud or hybrid cloud environments.
• →Exposure to MLOps best practices (CI/CD for ML, monitoring, observability).
• →Familiarity with security and compliance frameworks in regulated industries
• →Advanced degree (MSc/PhD) in Computer Science, Machine Learning, or related field.