AI Solution Engineer

1 day ago

Ahmedabad, Gujarat, India Xapton Solutions Full time

We are looking for an experienced
AI Solution Engineer
who can act as a critical bridge between industry-focused architects who identify AI opportunities and the engineering teams responsible for delivering solutions.

In this role, you will take AI concepts from early ideation through to technical prototypes, ensuring solutions are both
commercially valuable and technically viable
. As a trusted advisor, you will help clients understand how AI can address real business challenges—demonstrating not only technical depth, but also the art of what's possible.

You will collaborate closely with sales teams, architects, and technical specialists to design, validate, and showcase AI and machine learning solutions built on leading hyperscaler platforms.

What You'll Be Doing

  • Support early-stage sales and discovery conversations by helping non-technical stakeholders understand AI capabilities and solution approaches
  • Design, build, and demonstrate cloud-based AI prototypes that bring proposed solutions to life
  • Translate customer business challenges into practical, scalable AI/ML solutions that deliver measurable outcomes
  • Advise clients on technical requirements, dependencies, risks, and success criteria for AI initiatives
  • Demonstrate strong technical credibility during proposals, presentations, and client engagements

This Role Is a Strong Fit If You Have

  • Proven experience partnering closely with sales teams to shape enterprise-grade software or AI solutions
  • Strong expertise in AI model architectures, including
    LLMs and SLMs
    , with an understanding of performance trade-offs, suitability, training needs, and deployment strategies
  • Hands-on experience with at least two major hyperscaler AI platforms, such as:
  • AWS Bedrock / SageMaker
  • Google Vertex AI
  • Azure ML
  • OpenAI
  • Solid foundation in statistics, machine learning, data science fundamentals, data engineering, and big data concepts
  • Clear understanding of the processes, data prerequisites, and success factors required to deliver AI solutions aligned with business objectives
  • Working knowledge of cloud security, landing zones, and FinOps principles—particularly as they relate to AI cost optimisation

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