AI Solution Architect
Summary
Designs and documents secure, scalable cloud-native solutions, translating business needs into technical architectures while guiding engineering teams on AWS/Azure/GCP, APIs, microservices, and DevOps practices.
Role Name: AI Solution Architect
Qualifications
- 5 to 8 Years of experience
- Translate business requirements into technical architecture and design specifications
- Define and document the solution architecture, including high-level components, interfaces, and data flows
- Design and implement advanced frameworks using Lang Chain and related technologies.
- Develop document ingestion, chunking, embedding, indexing, and retrieval pipelines. Implement hybrid search architectures
- Familiar with Python software implementation and skilled in leveraging Lang graph workflow
- Good exposure on Responsible AI principles and how that is put into practice on live AI systems
- Evaluate technology options and recommend optimal tools, platforms and approaches
- Ensure alignment with enterprise standards, security and governance policies
- Collaborate with engineering, DevOps, and infrastructure teams to ensure successful implementation
- Provide guidance and oversight during development, integration, and deployment phases
- Engage with stakeholders to validate architecture decisions and manage trade-offs
- Support troubleshooting of technical issues and provide solution-level guidance during project execution.
Job Description
Responsible for designing and overseeing the implementation of end-to-end technology solutions that align with business objectives and technical constraints. Acting as a key technical leader, the Solution Architect bridges business needs and technical execution, ensuring that solutions are scalable secure, cost-effective, and fit-for-purpose across the enterprise or project landscape.
General Experience and Technical skills:
- Strong architecture design skills across application, data, integration, and infrastructure domains
- Proficiency in cloud platforms (e.g., AWS/Azure/GCP), including cloud-native services
- Hands-on experience with APIs, microservices and integration patterns
- Knowledge of cybersecurity best practices and compliance requirements
- Experience with DevOps, CI/CD pipelines, containerization (e.g., Docker, Kubernetes)
- Ability to use modelling and documentation tools (e.g., ArchiMate, Lucidchart, Draw.io, UML)
- Strong Ability of both monolithic and distributed system architecture.