Job Title : Senior AI Solution Architect

Employment Type : Full-time

Role Summary :

The Senior AI Solution Architect will design and drive the enterprise AI technical roadmap, ensuring seamless integration of AI capabilities into production-grade systems. The role focuses on selecting the right AI models and architectures while balancing performance, cost, scalability, and security, and bridging experimental AI with robust enterprise software built on .NET and Java microservices.

Key Responsibilities :

- Design end-to-end AI solution architectures covering data ingestion, orchestration, model lifecycle, and API delivery

- Define and implement scalable AI architectures using LangChain-based orchestration and production-ready deployment patterns

- Evaluate and select AI technologies including Azure AI Services, OpenAI APIs, and open-source models from Hugging Face

- Lead development of advanced AI solutions such as RAG systems and fine-tuned/custom models

- Design and implement high-concurrency REST APIs and microservices to integrate AI services with C#, Java, and JavaScript applications

- Ensure AI systems meet enterprise standards for scalability, performance, security, and compliance

- Establish technical standards, best practices, and architectural governance for AI development

- Provide technical leadership and mentorship to AI and engineering teams

- Collaborate with product, engineering, and business stakeholders to translate AI use cases into production solutions

Key Result Areas (KRAs) :

- Delivery of scalable, secure, and production-ready AI architectures

- Successful integration of AI services with enterprise .NET and Java microservices

- Performance, reliability, and cost-efficiency of deployed AI solutions

- Adoption of standardized AI development and deployment practices

- Reduced time-to-production for AI features and enhancements

- High-quality technical guidance and upskilling of engineering teams

Required Skillsets :

- Strong expertise in LLM orchestration using LangChain or LlamaIndex

- Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch

- Proficiency in model serving using FastAPI or Flask with low-latency design

- Strong understanding of RAG architectures, embeddings, vector databases, and fine-tuning techniques

- Experience integrating Python-based AI services with .NET (C#) and Java (Spring Boot) ecosystems

- Solid knowledge of microservices architecture, event-driven systems, and REST API design

- Hands-on experience with Docker and containerized deployments

- Strong understanding of AI security, data privacy, and compliance requirements such as GDPR

- Excellent problem-solving, architectural thinking, and stakeholder communication skills