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The AI Solution Engineer will maintain, optimize, and expand the company's automation ecosystem by integrating various platforms and developing intelligent AI-powered workflows. This role involves troubleshooting existing integrations, building new AI agents, and ensuring reliable data synchronization across the technical stack.
AI Solution Engineer
Work Type: Part-time.
Schedule: U.S. business hours (CST preferred).
Location: 100% Remote.
We are looking for an AI Automation & Integration Engineer to maintain, optimize, and expand our existing automation ecosystem while developing new AI-powered features and intelligent workflows.
The company currently operates on an interconnected technology stack that includes Trello, a custom-built in-house CRM, Jotform, Zapier, and Make. The initial priority for this role will be to understand how these systems work together, troubleshoot existing integrations, identify inefficiencies, and improve the reliability of our current workflows.
Beyond maintenance, this person will help build the next generation of our internal operations by transforming manual, multi-step business processes into intelligent workflows powered by AI agents and automation. The goal is to create systems where agents can execute tasks, coordinate information, interact with external tools, and escalate decisions to humans when necessary.
This is a hands-on engineering role for someone who can work independently, understand inherited systems, make sound architectural decisions, and take AI-powered solutions from concept to production.
1. Automation Debugging & System Maintenance
Take ownership of existing automations and integrations across Trello, the custom CRM, Jotform, Zapier, and Make.
Diagnose workflow failures, identify root causes, and implement sustainable fixes rather than temporary workarounds.
Evaluate existing automation architecture and identify opportunities to improve performance, reliability, and maintainability.
Recommend whether existing workflows should be optimized, repaired, or rebuilt.
2. Systems Integration & API Development
Build and maintain integrations between project management, CRM, form platforms, and external applications.
Work with REST APIs, webhooks, authentication mechanisms, rate limits, retries, and data mapping.
Analyze undocumented or custom-built systems by reviewing schemas, existing implementations, and available technical resources.
Ensure accurate and consistent data synchronization across connected platforms.
3. AI Agents & Context Engineering
Develop AI-powered agents capable of executing multi-step business processes with minimal human intervention.
Implement context retrieval, memory management, conversation state, and relevant information injection.
Optimize context windows and retrieval strategies to maintain accuracy and consistency across complex workflows.
Design human-in-the-loop mechanisms for reviewing outputs, approving sensitive actions, and escalating exceptions.
4. Workflow Automation & Orchestration
Audit, maintain, rebuild, and extend workflows using Zapier and Make.
Leverage n8n or comparable orchestration platforms when they provide a more effective solution.
Coordinate AI models, APIs, external tools, and business logic across multi-step workflows.
Design task decomposition, execution sequences, dependencies, error handling, and recovery mechanisms.
5. AI Feature Development
Build new internal tools, integrations, and automation features that support business operations.
Develop maintainable solutions using Python, TypeScript, or comparable programming languages.
Integrate LLMs and third-party APIs based on performance, reliability, complexity, and cost considerations.
Translate operational requirements into practical technical solutions.
6. Testing, Evaluation & Optimization
Test AI agents against representative business scenarios and measurable performance criteria.
Identify failure patterns and improve accuracy, consistency, response times, and overall reliability.
Validate structured outputs, tool calling, and automated decision-making.
Continuously refine prompts, workflows, and agent behavior based on real-world performance.
7. Deployment & Production Monitoring
Take solutions from prototype through testing, deployment, and ongoing optimization.
Monitor production workflows, troubleshoot failures, and implement safeguards.
Maintain version control, technical documentation, and code quality standards.
Apply appropriate security practices when handling credentials, API keys, and sensitive business information.
8. Continuous Technical Improvement
Stay current with emerging AI models, agent frameworks, orchestration tools, and context engineering practices.
Evaluate new technologies and determine their practical value for the company's existing infrastructure.
Identify opportunities to replace repetitive manual processes with reliable, AI-assisted workflows.
Professional Experience: 3–5 years of professional software engineering experience, including maintaining, debugging, and extending systems originally developed by other engineers.
AI & Intelligent Automation: Hands-on experience building AI-powered applications, intelligent automations, or agent-based workflows.
Debugging & Troubleshooting: Proven ability to take ownership of inherited automations, trace failures across interconnected platforms, and explain technical issues and their root causes.
Systems Integration: Experience integrating CRM, project management, and form platforms through REST APIs, webhooks, and custom integrations.
Programming: Strong proficiency in Python or TypeScript, including writing maintainable code and troubleshooting complex application issues.
Databases & Data Modeling: Experience with SQL, database structures, data modeling, and designing reliable data synchronization between systems.
Workflow Automation: Practical, hands-on experience with both Zapier and Make is required.
LLM Integration: Experience integrating LLM provider APIs, structured outputs, tool calling, and prompt engineering into real-world applications.
Context Engineering: Understanding of memory management, retrieval, conversation state, and context optimization for multi-step AI workflows.
Software Engineering Practices: Familiarity with Git, GitHub, API design, testing, debugging, and collaborative development.
Architecture & Technical Judgment: Ability to evaluate existing systems, identify inefficiencies, and determine when to optimize, repair, or rebuild.
Production Experience: Ability to take solutions from initial development through testing, deployment, monitoring, and continuous improvement.
Security Awareness: Understanding of secure credential management, API key protection, least-privilege access, and responsible handling of sensitive information.
Autonomy: Comfortable making technical decisions, prioritizing competing requirements, and delivering results with limited supervision.
Strong written English communication skills. C1 or High.
Ability to conduct technical discovery and ask the right questions before proposing or developing solutions.
Comfortable translating operational challenges into technical requirements and practical implementation plans.
Strong analytical and problem-solving abilities, particularly when working with undocumented or inherited systems.
Understands when AI-generated outputs require human verification, approval, or escalation.
Able to communicate technical limitations, trade-offs, risks, and recommendations to non-technical stakeholders.
Self-directed, accountable, and proactive in following up on blockers and pending decisions.
Experience with Trello, Jotform, or comparable project management and form platforms.
Experience administering or integrating custom-built CRM platforms.
Familiarity with agent frameworks and orchestration libraries such as LangGraph and LangChain.
Experience with Model Context Protocol (MCP) and connecting AI agents to external services.
Knowledge of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
Experience with AI evaluation frameworks, observability, tracing, guardrails, and automated testing.
Familiarity with cloud environments such as AWS, Google Cloud, or Microsoft Azure.
Experience with MLOps, CI/CD pipelines, and scalable application deployment.
Familiarity with React and modern application development environments.
environment.
Work with international clients while maintaining your independent contractor status.
Minimum 5 paid days off annually, plus US holidays.
Free access to career growth learning modules through Hyre Academy.
Scheduled rate increases based on applicable contract terms and performance.
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