Senior AI Engineer

Senior AI Engineer2 Technical Skills Engineering Stack: Strong hands-on proficiency in Python and/or .NET (C#, Core) , Java , or Node.js . AI & GenAI: Practical experience with GenAI APIs (OpenAI, Azure OpenAI), LangChain, LlamaIndex, RAG patterns, or agentic workflow frameworks. Cloud & DevOps: Hands-on experience with AWS, Azure, or GCP—microservices, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps). Automation: Exposure to workflow orchestration engines, RPA tools, or custom automation scripts. Enterprise Platforms: Familiarity with enterprise systems (Oracle, SAP, Salesforce, or ServiceNow) is a plus. Certifications: Cloud Certification (AWS, Azure, or GCP) at associate/developer level is a plus. Soft Skills Clear technical communication—able to explain code implementation to teammates and project managers. Collaborative team player accustomed to working across global/offshore time zones. Curious and self-motivated — proactively explores new AI tools, frameworks, and engineering patterns. Experience Experience: 4–6 years of hands-on software engineering experience, with 2+ years as, Senior AI engineer Hands-on experience building and delivering enterprise-grade solutions across cloud, AI/ML, and application engineering. Experience working in client-facing delivery environments within IT services or consulting organizations is preferred. Key Responsibilities 1. Hands-on Engineering & Delivery Write production-grade code to build component-level features and API integrations based on technical designs and blueprints. Actively contribute to daily engineering deliverables—developing backend microservices, driving unit testing, refactoring code, and resolving technical debt. Conduct peer code reviews to ensure code quality, performance, maintainability, and adherence to team engineering standards. Troubleshoot and resolve complex bugs, API integration issues, and performance bottlenecks within application microservices. AI & Engineering Framework Adoption Learn, implement, and integrate for AI-native feature— including GenAI integration patterns, agentic workflows, and intelligent automation Contribute to the development and maintenance of AI engineering frameworks, solution accelerators, and reusable technical assets. Evaluate and experiment with new tools, APIs, and platforms in the AI and cloud-native space. Technical Consulting & Problem Solving Engage with client technical teams to understand system landscapes, integration requirements, and technical constraints. Propose pragmatic, technology-forward solutions to complex engineering challenges across application modernization, AI integration, and cloud migration. Support the Solution and Principal Architect in pre-sales activities including technical assessments, proof-of-concept design, and effort estimation. Cloud & Automation Execution Develop and deploy cloud-native services on AWS, Azure, or GCP using containers (Docker, Kubernetes), serverless functions, and event-driven patterns. Implement intelligent automation components using workflow orchestration engines, RPA integrations, or custom AI-driven pipelines. Engineering Community & Mentoring Mentor junior engineers—supporting technical upskilling on AI tools, cloud platforms, and modern engineering practices. Contribute to Jade's internal community of practice through knowledge sharing, documentation, and participation in architecture discussions. Education Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related technical field is required .