Advanced AI/ML Applications Specialist

You will be a part of a team at Tezo, a Digital & AI solutions provider, focused on creating exceptional outcomes for customers using cutting-edge analytics, data proficiency, technology, and digital excellence. Key Responsibilities: - Agentic System Development - Build and implement agentic AI components such as tool-using agents, multi-step reasoning and execution flows, and planner, executor, and validator agent patterns. - Translate architectural designs into working, maintainable code to ensure agent behavior aligns with intent. - Prompt, Memory & Retrieval Engineering - Develop prompts as versioned, testable software artifacts. - Implement and optimize retrieval-augmented generation (RAG), memory and context-management strategies, and input/output constraints. - Evaluation, Testing & Reliability - Build evaluation harnesses to assess accuracy, relevance, and regression across prompt and model changes. - Implement automated testing and validation for AI workflows to monitor drift and degradation over time. - Deployment & Operations - Package and deploy AI components into production environments. - Integrate AI logic into APIs, services, and workflows and instrument solutions for performance, usage, and cost-to-serve. - Collaboration Within the AI Pod - Work closely with the AI Product Lead, Lead AI Architect, and Automation/Integration Engineers to align implementation, design decisions, and real-world execution. - Contribute to reusable components, templates, and patterns within the AI Factory. Required Qualifications: - Experience - 48+ years of experience in software engineering, data engineering, or applied AI development. - Hands-on experience building and deploying systems into production environments. - Comfort working in agile, fast-moving delivery teams. - AI & Agentic Skills - Practical experience with generative AI and LLMs, agentic frameworks, tool calling, and action execution. - Solid understanding of common LLM failure modes and mitigation techniques. - Technical Skills - Strong proficiency in Python. - Experience with API development and integration, event-driven or workflow-based systems, CI/CD, modern DevOps practices, and familiarity with cloud-native architectures (Azure preferred). You will be a part of a team at Tezo, a Digital & AI solutions provider, focused on creating exceptional outcomes for customers using cutting-edge analytics, data proficiency, technology, and digital excellence. Key Responsibilities: - Agentic System Development - Build and implement agentic AI components such as tool-using agents, multi-step reasoning and execution flows, and planner, executor, and validator agent patterns. - Translate architectural designs into working, maintainable code to ensure agent behavior aligns with intent. - Prompt, Memory & Retrieval Engineering - Develop prompts as versioned, testable software artifacts. - Implement and optimize retrieval-augmented generation (RAG), memory and context-management strategies, and input/output constraints. - Evaluation, Testing & Reliability - Build evaluation harnesses to assess accuracy, relevance, and regression across prompt and model changes. - Implement automated testing and validation for AI workflows to monitor drift and degradation over time. - Deployment & Operations - Package and deploy AI components into production environments. - Integrate AI logic into APIs, services, and workflows and instrument solutions for performance, usage, and cost-to-serve. - Collaboration Within the AI Pod - Work closely with the AI Product Lead, Lead AI Architect, and Automation/Integration Engineers to align implementation, design decisions, and real-world execution. - Contribute to reusable components, templates, and patterns within the AI Factory. Required Qualifications: - Experience - 48+ years of experience in software engineering, data engineering, or applied AI development. - Hands-on experience building and deploying systems into production environments. - Comfort working in agile, fast-moving delivery teams. - AI & Agentic Skills - Practical experience with generative AI and LLMs, agentic frameworks, tool calling, and action execution. - Solid understanding of common LLM failure modes and mitigation techniques. - Technical Skills - Strong proficiency in Python. - Experience with API development and integration, event-driven or workflow-based systems, CI/CD, modern DevOps practices, and familiarity with cloud-native architectures (Azure preferred).