Full stack Engineer with Python AI

Responsibilities

• Lead the design, development, and deployment of enterprise AI solutions integrating data, applications, APIs, and business workflows.
• Develop and implement GenAI applications, LLM integrations, AI agents, RAG solutions, and intelligent automation.
• Provide hands-on technical leadership, mentor five developers, and establish engineering standards and best practices.
• Translate business requirements into scalable AI solutions that improve productivity, quality, operational efficiency, and cost effectiveness.
• Drive end-to-end engineering delivery, including solution architecture, development, CI/CD, automated testing, integration, and production readiness.
• Leverage AI-assisted development tools to automate repetitive tasks, accelerate development, and improve software quality.

Skills Must-Have

• Python
• Full-Stack Development
• Modern UI Development
• Generative AI
• LLM Integration
• AI Agents
• RAG
• Intelligent Automation
• REST APIs
• Cloud Technologies
• System Integration
• Solution Architecture
• CI/CD
• Automated Testing
• Technical Leadership

Mandatory Skills Description

• 5+ years of progressive software engineering experience, with strong hands-on expertise in Python, full-stack development, modern UI technologies, APIs, cloud platforms, and system integration.
• Proven experience designing and delivering AI/Generative AI solutions, LLM integrations, AI agents, RAG/grounding, and intelligent automation.
• Solid understanding of solution architecture, CI/CD, automated testing, and production deployment.
• Demonstrated ability to lead engineering teams, mentor developers, establish technical standards, and deliver secure, scalable solutions from concept through production.
• Experience leading small engineering teams of approximately five developers, driving enterprise AI adoption, and implementing AI-assisted development practices to improve engineering productivity.
• Strong background in business process automation, workflow optimization, and delivering measurable improvements in cycle time, quality, cost avoidance, and operational efficiency.
• Experience integrating enterprise data, knowledge systems, and applications into AI-powered solutions is highly desirable.
• AI Tool Expectations: Consistent use of enterprise-approved AI tools, including GitHub Copilot, Microsoft 365 Copilot, and other approved GenAI platforms, targeting a minimum of 90% weekly utilisation to accelerate development, improve quality, and reduce manual effort.