Senior AI Engineer

As a Senior AI Engineer, you will play a central role in shaping how AI is adopted across a fast-growing, technology-driven organization. You will design and deliver practical AI solutions, with a strong focus on LLMs, generative AI, and modern machine learning. From defining problems and building data pipelines to deploying, monitoring, and continuously improving production systems, you will own the full AI lifecycle. You will work closely with product, engineering, and business teams to embed AI into products, services, and internal processes. The role offers significant autonomy and the opportunity to identify where AI can create measurable business value. You will also help educate stakeholders and champion responsible, effective AI adoption across the organization. This is an ideal opportunity for an experienced engineer who combines strong technical expertise with a passion for innovation and real-world impact. Accountabilities:

• Design, build, and deploy AI solutions focused on LLMs, generative AI, and modern machine learning to solve real-world business challenges.
• Own the end-to-end lifecycle of AI features, including problem definition, data understanding, modeling, evaluation, deployment, monitoring, and iteration.
• Develop and optimize LLM-powered applications such as RAG systems, AI agents, chatbots, and document-understanding solutions.
• Design and contribute to data pipelines supporting efficient data collection, preprocessing, analytics, and AI/ML workflows.
• Deploy AI solutions within cloud infrastructure, ensuring scalability, security, reliability, and strong performance.
• Collaborate with cross-functional teams to integrate AI capabilities into products, services, and internal tools.
• Identify and prioritize opportunities where AI and machine learning can deliver measurable improvements across business processes and operations.
• Educate and advise stakeholders on AI capabilities, use cases, and best practices while helping foster an AI-first culture.
• Continuously improve systems, processes, and ways of working while maintaining high standards for engineering quality.

• 5+ years of professional software development experience, including at least 2 years focused on AI/ML engineering or a closely related field, with a proven record of delivering AI solutions.
• Demonstrated experience building and deploying production-grade AI/ML systems, including batch and/or real-time applications.
• Strong practical experience with LLMs and generative AI, including prompt engineering, fine-tuning, RAG, or LLM orchestration frameworks.
• Hands-on experience with vector databases and semantic search technologies such as Pinecone, Weaviate, Qdrant, Elasticsearch, or OpenSearch.
• Proven understanding of RAG architectures, retrieval pipelines, and evaluation approaches for LLM-based systems.
• Experience designing and managing data pipelines for AI/ML applications.
• Strong Python programming skills, including practical experience with FastAPI and asynchronous programming using async/await.
• Experience with major cloud platforms such as AWS, Azure, or Google Cloud and integrating AI solutions into cloud-based environments.
• Proficiency in database management, data wrangling, distributed systems, algorithm design, statistics, and data science.
• Experience advocating for technology adoption and helping organizations understand and implement new technical capabilities.
• Familiarity with MLOps practices, including ML CI/CD, monitoring, experiment tracking, and AI/ML workflow management.
• Excellent communication, presentation, and documentation skills, with the ability to educate and influence stakeholders at different levels.
• A pragmatic, problem-solving mindset focused on building scalable solutions that create tangible value.
• Strong ownership, continuous-improvement mindset, and enthusiasm for driving innovation.
• Ability to set high standards, lead by example, and contribute positively to a collaborative, supportive engineering environment.

• Competitive salary.
• Asynchronous working environment designed to support autonomy and flexibility.
• Remote-first working model, with hybrid arrangements depending on the nature of the role.
• Opportunity to work abroad for short periods.
• Career development and growth opportunities within a rapidly expanding organization.
• Hardware provided to new joiners so you have the tools needed to succeed from day one.
• Opportunity to work on impactful technology that helps enable greater access to global career opportunities.
• International, diverse, and collaborative working environment.