Responsibilities
- Identify and showcase high-impact AI opportunities, developing proof of concepts to validate feasibility and demonstrate real-world value.
- Explore, collect, clean, and prepare datasets for prompt engineering, model training and evaluation (Data Engineering).
- Design and create robust data pipelines (Data Engineering).
- Develop, test and iterate prompts to optimise performance across relevance, accuracy, consistency and other areas (Prompt Engineering).
- Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development).
- Integrate and deploy scalable AI based applications, backend services and APIs (Deployment).
- Develop automated mechanisms and tools for continuous evaluation, benchmarking and optimising of AI solutions, prompts, and models (Eval).
- Improve AI solutions and enhance real-world applicability through qualitative user feedback (Eval).
- Ensure that all AI solutions and tools align with organisational policies, security protocols, and relevant regulations (Compliance).
- Stay up to date with the latest AI advancements and best practices, and drive AI culture empowering your colleagues to apply AI to their own projects.
Essentials
- Software development experience using Python, and GoLang.
- Proven track record leveraging Generative AI to build / enhance products with real user adoption.
- Experience in developing and fine-tuning Gen AI models, including prompt engineering, model fine tuning and deployment.
- Knowledge and use of LLM and statistical evaluation techniques such as G-Eval, Bleu, Perplexity and/or others for prompt and model optimisations.
- Comfortable working with databases (relational & vector), and large-scale data sets and pipelines (e.g. AWS Glue, Redshift, RDS, Pinecone, Opensearch).
- Hands-on experience with AI Cloud Infrastructure for MLOps (e.g.Google Vertex AI / AWS Bedrock), including deploying AI applications and managing AI cloud-based services.
- Expert knowledge of REST, and proficiency in designing and writing APIs.
Nice-To-Have
- Experience with Automatic Prompt Engineering frameworks such as Textgrad or DSPy.
- Knowledge of agentic systems and autonomous multi-agent frameworks.
- Knowledge of Git or other source control software
- Knowledge of using JIRA and Confluence
- Experience with multi-modal AI (audio, image, video).

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