Senior AI Engineer – AI Automation & Agent Implementation
Summary
VeriZ Services seeks a hands-on Senior AI Engineer / implementation consultant to design, build, test, and deploy production AI automations and agents, converting manual workflows into LLM-powered solutions using Python, cloud platforms (AWS, Azure, AliCloud), and tools like Cursor, Copilot, Bedrock, and OpenAI APIs, with emphasis on measurable business outcomes.
Compensation: $20k – $28k • No equity
We are seeking a hands-on Senior AI Engineer / AI Automation and Agent Implementation Consultant to identify, design, build, test, and deploy AI-powered solutions that improve business processes and operational efficiency. This is an #implementation-focused role, not a strategy-only or advisory position. The ideal candidate is a builder who can take AI solutions from prototype to production and demonstrate measurable business outcomes. The candidate should have practical experience with #Generative AI, #LLMs, #AI agents, automation, #cloud technologies, and #AI development tools such as Cursor, GitHub Copilot, Microsoft Copilot, AI agents, and LLM-based solutions to transform manual workflows into production-ready, AI-supported capabilities.
Key Responsibilities • Identify manual and repetitive business workflows that can be improved through AI automation. • Design, prototype, implement, test, and deploy AI-powered solutions. • Build and implement AI agents and workflow automations. • Use tools such as Cursor, GitHub Copilot, Microsoft Copilot, LLM platforms, APIs, and automation tools. • Integrate AI solutions with enterprise applications, APIs, data sources, and business workflows. • Develop production-ready AI solutions with appropriate security, privacy, monitoring, and human oversight. • Implement evaluation, observability, fallback, and support mechanisms for AI solutions. • Measure business outcomes such as productivity improvement, reduced cycle time, quality improvement, cost savings, and operational efficiency. • Collaborate with architecture, engineering, platform, data science, finance, and business teams. • Support AI/ML and GenAI workload cost optimization and FinOps activities. • Create dashboards, reports, and KPIs to monitor AI usage, costs, utilization, and business value. Required Qualifications • Bachelor's degree in an engineering or computer science discipline and/or equivalent experience/certification • 7+ years of experience in Information Technology including experience in cloud technologies (AWS, Ali Cloud, Azure), OS scripting, and automation using Python, Bash, or similar languages • Hands-on experience designing and implementing AI automation or AI agent solutions. • Experience taking AI solutions from experimentation/prototyping through production deployment. • Experience with Python, Bash, or similar scripting languages. • Experience with cloud platforms such as AWS, Azure, or Alibaba Cloud (AliCloud). • Practical experience with one or more of Cursor,GitHub Copilot,Microsoft Copilot ,AI Agents ,LLM-based platforms ,Generative AI • Experience integrating AI solutions with APIs, enterprise systems, workflows, and data sources. • Strong problem-solving and communication skills. • Ability to work independently and collaborate with cross-functional teams. • Experience with services such as Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Google Vertex AI, OpenAI APIs, Anthropic, Databricks, Snowflake AI, or similar platforms.. • Experience with AI agent frameworks, retrieval-augmented generation, prompt and context engineering, model evaluation, observability, responsible AI controls, secure deployment patterns, and human-in-the-loop workflows.. • Experience defining and tracking implementation success measures, documenting reusable solution patterns, and transitioning AI-enabled capabilities to operations and support teams.. • Experience supporting generative AI or large language model workloads, including token-based pricing models and inference cost optimization.. • Experience in developing and implementing FinOps/Cloud Cost Optimization strategies analysis is a plus