Senior AI Engineer

• Design and implement AI architectures based on LLM/GenAI technologies
• Build end-to-end AI solutions including assistants, recommendations, and automation systems
• Design and implement RAG (Retrieval-Augmented Generation), embeddings, vector stores, and data pipelines
• Integrate AI solutions with backend systems (microservices, REST APIs, event-driven architectures)
• Select appropriate models, pipelines, and tooling for specific use cases
• Set up and manage AI tools like ChatGPT Enterprise, Cursor, and emerging platforms
• Mentor engineers, define best practices, and perform code reviews
• Monitor model performance, quality, cost, and safety in production environments
• Create dashboards to track usage, adoption, team productivity, and AI system metrics
• Co-create and execute the AI roadmap with product and business stakeholders
• Advise product and business teams on AI capabilities and opportunities
• Build and test AI prototypes and experiments, turning ideas into practical solutions
• Keep AI guides, prompts, and examples up to date in a shared knowledge hub
• Support training and onboarding to help teams adopt AI tools and best practices quickly
• Work closely with engineering, product, and support teams across multiple countries

• 5+ years of experience as a Software Engineer
• 2+ years hands-on experience in AI/ML or LLM-based projects
• Strong Python experience (3+ years commercially)
• Practical experience with OpenAI, Azure OpenAI, HuggingFace, or open-source LLMs
• Experience with LangChain, LlamaIndex, or similar orchestration frameworks
• Hands-on experience with vector databases (Pinecone, Qdrant, Weaviate, pgvector)
• Strong understanding of RAG and data pipeline design and implementation
• Experience with system architecture, APIs, integrations, and event-driven design
• Hands-on experience in AWS-first environments for AI or data solutions (AWS Bedrock, serverless, IAM)
• Technical leadership and mentoring skills with proven ability to guide engineering teams
• Skilled in modern LLM tools and workflows, including prompt engineering and model evaluation
• Strong understanding of data flows, telemetry, and metrics in engineering contexts
• Excellent written and spoken English with ability to engage stakeholders across countries
• Familiarity with AI governance, security, and compliance considerations
• Proven ability to work effectively in multi-country or distributed organizations

• Experience with fine-tuning, LoRA, and quantization techniques
• Knowledge of MLOps (monitoring, drift detection, CI/CD for AI)
• Experience building AI-first products in startup or high-ownership environments
• Background in data engineering, analytics, or platform engineering
• Experience measuring developer productivity or evaluating ROI of AI tooling

100% remote work