- Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
- Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously
- Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation, including MLOps
- Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI & agentic AI architectures into innovative, practical solutions that transform customer experiences
- Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy
- Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems
- Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem
- Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures
AWSArtificial IntelligenceGCP+8 more