- We are looking for an experienced AI Solution Engineer to act as the link between our industry architects, who identify AI business cases, and the firm's development capabilities.

- This role shapes AI solutions, meets client needs, and delivers measurable business value and technically feasible solutions.

- The AI Solution Engineer is a key technical resource responsible for selecting, designing, demonstrating, and delivering prototype solutions that align with customer needs and business goals during early engagement.

- As a trusted advisor, the Solution Engineer has a strong mix of technical expertise, problem-solving skills, and business acumen to effectively create cloud prototypes to demonstrate and communicate the value of solutions to both technical and non-technical stakeholders.

- They provide experience in identifying viable and feasible AI solutions to address specific client issues and demonstrate technical capability as part of proposals.

- They demonstrate extensive knowledge of hyperscaler AI offerings, understanding all of the technical requirements and dependencies of a product/solution and explaining them to potential clients 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, demonstrates 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 and 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 optimization.

Primary skills:

- Hands-on delivery focused

Strong experience building real GenAI solutions, including:

a. RAG implementations

b. LangChain / LangGraph

c. Prompt engineering

d. Vector databases & embeddings

- Comfortable leading delivery and making technical decisions.

- Can code, prototype, and guide teams by example.

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