Job Description
About the Role We are looking for an AI Solutions Architect to join our AI team in delivering innovative enterprise AI solutions. This is a hands-on role focused on the design, development, and implementation of Generative AI, RAG (Retrieval-Augmented Generation), and agentic AI solutions for real business use cases. You will work closely with cross-functional teams to build scalable AI applications, integrate them with enterprise systems, and support deployment in hybrid and on-premises environments. This role is ideal for someone who solving practical business problems and growing their career in a fast-evolving AI practice. Key Responsibilities - Design, develop, and implement AI solutions with a focus on Generative AI, RAG, and agentic workflows - Build and optimize AI applications using LLM frameworks, and vector database technologies - Develop end-to-end pipelines for document ingestion, indexing, retrieval, prompt orchestration, and response generation - Implement and integrate AI solutions with enterprise applications, APIs, and data sources - Support deployment of AI applications in on-premises and hybrid cloud environments - Containerize and deploy solutions using Docker and Kubernetes - Work with cloud and AI platforms and LLM services where applicable - Collaborate with project teams and stakeholders to translate business requirements into technical solutions - Participate in PoCs, MVPs, and production implementation for client AI projects - Troubleshoot, test, and improve AI solution performance, scalability, and reliability - Maintain technical documentation and contribute to delivery best practices Requirements - Degree in Computer Science, Engineering, Data Science, or a related discipline - Hands-on experience in software development, with strong proficiency in Python - 1+ year of experience in GenAI-related work - Understanding of LLMs, prompt engineering, and AI application development patterns - Familiarity with RAG architecture, document retrieval, embeddings, and vector databases - Exposure to agentic AI solutions, orchestration frameworks, or multi-step AI workflows - Experience with Docker and/or Kubernetes - Familiarity with Azure, AWS, or similar cloud platforms - Understanding of API integration and enterprise application development - Strong problem-solving skills and ability to work in a project delivery environment - Good communication and teamwork skills Preferred Qualifications - Experience delivering AI/ML or GenAI projects in enterprise environments - Hands-on experience with LLM ecosystems and tooling such as model APIs, orchestration frameworks, retrieval pipelines, and RAG solutions leveraging ontology/knowledge graph approaches - Knowledge of software engineering best practices, including version control, testing, and deployment workflows What We Offer - Opportunity to work on exciting and impactful enterprise AI transformation projects - Exposure to emerging technologies across GenAI, RAG, and agentic AI - A collaborative environment with strong opportunities for learning and career growth in AI practice - Hands-on involvement from proof-of-concept through to production delivery - Competitive compensation and benefit package
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