Responsibilities
- Design and build AI solutions (with a strong focus on LLMs and modern ML) for real-world business problems.
- Own the end-to-end lifecycle of AI features: problem definition, data understanding, modeling, evaluation, deployment, monitoring, and iteration.
- Develop and optimize LLM-based applications (e.g. RAG, agents, chatbots, document understanding).
- Participate in the design and management of data pipelines for efficient data collection, preprocessing, and analytics.
- Develop and deploy AI solutions into the company’s cloud infrastructure, ensuring scalability, security, and performance.
- Work closely with cross-functional teams to integrate AI capabilities into products, services, and internal tools.
- Identify and prioritize areas where AI and machine learning can add measurable value to business processes, products, and operations.
- Educate and guide stakeholders on the potential applications of AI, fostering a culture of innovation.
Requirements
- Minimum of 5 years in a Software Development role, including at least 2 years in AI/ML engineering or a related field, with a track record of delivering AI solutions.
- Proven experience building and deploying production-grade AI/ML systems (batch and/or real-time).
- Practical experience with LLMs and generative AI (e.g. prompt engineering, fine-tuning, RAG pipelines, or LLM orchestration frameworks).
- Experience with vector databases and semantic search (e.g. Pinecone, Weaviate, Qdrant, Elasticsearch, OpenSearch).
- Experience implementing RAG architectures, retrieval pipelines, and evaluation for LLM-based systems.
- Background in building and managing data pipelines for AI/ML systems.
- Strong programming skills in Python, including hands-on experience with FastAPI and asynchronous programming (async/await).
- Experience with cloud platforms (e.g. AWS, Azure, Google Cloud) and integrating AI solutions into cloud-based systems.
- Proficiency in database management, data wrangling, and working with distributed systems.
- Solid foundation in algorithm design, statistics, and data science.
- Previous experience promoting and advocating for technology adoption in a corporate setting.
Nice to Have
- Familiarity with MLOps practices and tools for managing AI/ML workflows (e.g. CI/CD for ML, monitoring, experiment tracking).
- Strong communication skills, with the ability to educate and influence stakeholders at all levels of the organization.
- Problem-solving mindset with a focus on delivering practical, scalable AI solutions.
- Passion for driving innovation and fostering an AI-first culture within the organization.
- High ownership mindset, always striving for improvements in systems, processes, and ways of working.
- Excellent presentation and documentation skills.
- Set high standards for yourself and others, and lead by example.
Work Arrangement
Remote (Worldwide)
Additional Information
- Asynchronous working environment
- Ability to work from abroad for a short period of time
- Growth opportunities within the company
- We provide all new joiners with the necessary hardware to ensure you have the tools you need to succeed from day one
