About the job
About MySigrid
At MySigrid, we are dedicated to enhancing productivity for busy professionals by providing exceptional executive support that merges top-tier human assistance with cutting-edge intelligent systems. As we transition from a smart task management console to an AI-native platform, we are integrating advanced technologies such as large language models (LLMs), agentic workflows, and intelligent automation. If you've ever imagined, "I could create something superior using GPT over a weekend," then this is your opportunity.
The Opportunity
We are looking for a talented AI Agent Engineer to conceptualize, develop, and implement intelligent AI agents that automate workflows, boost productivity, and enhance user experiences across our platforms. The ideal candidate will possess a deep understanding of AI models, prompt engineering, API integrations, and workflow automation. We value a blend of strong technical skills with creativity and curiosity, enabling you to utilize tools like OpenAI, Anthropic, or similar LLMs to create transformative solutions.
Key Responsibilities:
- Design and Build AI Agents: Develop, train, and deploy tailored AI agents to automate business processes, manage conversations, and execute multi-step workflows.
- Integrate APIs and Tools: Seamlessly connect AI systems with third-party applications (e.g., Slack, Make.com, Airtable, Google Workspace, CRMs) to facilitate dynamic automation.
- Workflow Automation: Create and enhance comprehensive AI-driven automations for both internal and client-centric use cases.
- Prompt Engineering: Design, test, and refine sophisticated prompts and system instructions to ensure optimal performance of LLMs.
- Model Customization: Fine-tune or adapt pre-trained language models to meet specific business requirements.
- Testing & Evaluation: Assess agent performance, accuracy, and response quality; implement enhancements based on feedback and data insights.
- Documentation: Produce and maintain thorough technical documentation for AI workflows, processes, and model configurations.
- Collaboration: Partner closely with developers, product teams, and operations to pinpoint AI opportunities and design practical, scalable solutions.
- Data Privacy & Ethics: Ensure AI systems adhere to data security, privacy, and ethical use regulations.
