AI Solutions Architect

Role & responsibilities

• Lead customer discovery sessions, ask probing questions, and translate business requirements into AI-driven solutions.
• Design AI architectures using LLMs, RAG, AI agents, vector databases, and cloud platforms.
• Develop and deploy production-grade AI applications using Python and modern AI frameworks.
• Integrate AI solutions with Salesforce, CRM/ERP systems, APIs, and enterprise data platforms.
• Optimise LLM performance through prompt engineering, RAG optimisation, evaluation frameworks, and feedback loops.
• Work with OpenAI, Claude, Gemini, and other LLM platforms.
• Support technical demonstrations, proof of concepts (PoCs), and customer workshops.
• Mentor engineering teams and establish reusable AI frameworks and best practices.
• Ensure AI solutions are scalable, reliable, secure, and aligned with business objectives.

Preferred candidate profile

• 8+ years of software engineering experience.
• 3+ years of hands-on experience delivering enterprise AI solutions.
• Strong programming skills in Python and experience building APIs.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Hands-on experience with AI frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
• Strong understanding of LLMs, RAG pipelines, AI agents, embeddings, and vector databases.
• Experience with prompt engineering, LLM evaluation, and AI application optimisation.
• Experience integrating AI solutions with enterprise applications, CRM/ERP systems, and APIs.
• Excellent communication, solutioning, stakeholder management, and customer-facing consulting skills.

Success Measures

• Deliver scalable AI solutions that demonstrate measurable business value.
• Improve LLM accuracy, reliability, and user adoption.
• Accelerate implementation through reusable AI frameworks and best practices.
• Enable successful enterprise AI deployments and improve customer satisfaction.

Interested candidates: Please share your updated resume highlighting relevant enterprise AI implementation experience, technical expertise, and project achievements.