Generative AI Solutions Architect

• B.Sc. in Computer Science & Engineering, any other engineering discipline, Mathematics, Statistics, or a similar field from a reputed university. 
• Note: Education requirements are not limited to the above. Candidates with the right skills and experience are encouraged to apply. 

The ideal candidate will have 8+ years of professional experience in AI engineering, machine learning, software engineering, advanced analytics, or related fields, with experience in technical architecture or technical leadership roles. 

• Architect and deliver production-grade Generative AI and ML systems. 
• Build reliable, scalable, and maintainable AI solutions from experimentation to production. 
• Design and support practical Generative AI use cases such as LLM-powered applications, AI assistants, RAG, and agentic workflows. 
• Translate business and client requirements into practical AI solution architectures. 
• Work with Data Scientists, Data Engineers, and Software Engineers to turn prototypes into production-ready systems. 
• Guide teams on responsible use of AI tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, and similar platforms. 
• Mentor software teams and help them use Generative AI tools effectively in their day-to-day engineering work. 
• Define and improve LLMOps and MLOps practices, including deployment, monitoring, evaluation, retraining, and feedback loops. 
• Build CI/CD pipelines for AI/ML workflows, including data validation, feature engineering, model validation, prompt evaluation, and drift detection. 

• Practical experience designing LLM-powered applications such as AI assistants, RAG systems, agentic workflows, or AI-assisted engineering tools. 
• Strong knowledge of LLM APIs and/or locally hosted LLMs, including tools such as LM Studio, Ollama, vLLM, Hugging Face, Azure OpenAI, or similar platforms. 
• Experience with LangSmith, LangChain, LangGraph, foundation models, RAG, MCP, vector databases, or prompt evaluation. 
• Hands-on experience with production ML/AI systems and MLOps or LLMOps practices. 
• Experience with orchestration and containerization tools such as Docker, Kubernetes, or similar. 
• Hands-on experience with monitoring, evaluation, drift detection, and feedback loops in production environments. 
• Experience using tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, or similar tools. 
• Ability to review, debug, test, and validate AI-generated code before using it in production. 
• Ability to mentor engineers and explain Generative AI concepts in a practical, easy-to-understand way. 
• Strong programming skills in Python or similar languages. 

• Strong experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar. 
• Experience with internal AI assistant development, AI coding workflows, or enterprise AI enablement. 
• Exposure to recommendation systems, search, or personalization platforms. 
• Exposure to data warehouses such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse. 
• Notable experience in Kaggle or other machine learning competitions. 
• Hands-on expertise in MLOps tooling such as MLflow, SageMaker, or similar. 

• Lead cross-functional teams and establish enterprise-wide AI best practices. 
• Opportunity to architect mission-critical AI/ML solutions for global clients. 
• Very competitive salary and excellent career opportunity in a focused and stable organization. 
• Most importantly, a friendly work environment with opportunity to learn from a number of highly skilled mentors. 

If you believe you are the right candidate, then send your CV to career@relisource.com with this exact line as email's subject “GEN_AI_31102025” by June 30, 2026.

IMPORTANT: Resume attached without above subject line will not be processed. Your CV must include your photograph.