AI Solution Engineer
I am currently seeking for up to x5 experienced and senior AI Solution Engineers.
To join my Top Four Consultancy client at a very exciting and interesting time.
You will act as the link between industry architects, who identify AI business cases and ensure development capabilities.
This role shapes AI solutions, meets client needs and delivers measurable business value and technically feasible solutions.
As an AI Solution Engineer you will be a key technical resource responsible for selecting, designing, demonstrating and delivering prototype solutions that align with customer needs and business goals during early engagement.
You will be trusted to bring a strong mix of technical expertise, problem-solving skills and business acumen. You will effectively create cloud prototypes to demonstrate and communicate the value of solutions to both technical and non-technical stakeholders.
You will provide experience in identifying viable and feasible AI solutions, to address specific client issues and demonstrate technical capability as part of proposals. Demonstrating extensive knowledge of hyperscaler AI offerings, understanding all of the technical requirements and dependencies of a product/solution and explaining them to potential clients accordingly.
What your days will look like:
Primarily sales-oriented, this role is focused on supporting the sales process by bridging the gap between technical teams and non-technical salespeople. The role helps sales teams select and prospects understand, the AI/ML solution. Clearly evidencing how it solves their business problems and assists in demonstrating AI technical excellence to the client in the early sales process.
This role is for you if you have:
- Extensive experience working with sales teams and shaping viable and feasible software solutions as part of process change for enterprise customers
- AI Model Architecture – Evidenced expertise in LLMs, SLMs, (Large Language Models/Small Language Models) performance, suitability, training requirements and deployment
- Cloud & Hyperscalers – Practical experience with at least two of the following is required: AWS Bedrock/Sagemaker, Google Vertex AI, OpenAI and Azure ML is required
- An understanding of underlying statistics, machine learning and data science, data engineering and big data concepts is required
- An understanding of the process and data complexities, prerequisites and success criteria needed; to deliver a solution that meets user and business needs
- Cloud Security & FinOps – Knowledge of landing zones, security and AI cost optimisation
