AI Automation Engineer - Technology R&D at Signant Health

About the Role

• We are seeking an AI Engineer focusing on automation responsible for building and optimizing AI-powered applications and agents that automate workflows across Signant Health. This role focuses on developing reliable automation solutions using n8n workflows, AI agents, and custom integrations to improve operational efficiency and accuracy. The AI Engineer will work with Python, LLM APIs, and workflow automation platforms to create intelligent automation that integrates with existing systems and tools. Working as part of the AI team, this individual will implement prompt engineering and context engineering techniques to optimize agent performance, develop evaluation methods to measure automation accuracy, and contribute to the continuous improvement of automation capabilities. The ideal candidate brings solid experience in workflow automation development, a strong Python foundation, and enthusiasm for building AI-powered solutions that deliver tangible business value.

What you will do:

Application Development

• Develop AI applications and agents that automate business workflows using n8n and custom Python integrations
• Build automation pipelines that integrate with internal systems, third-party APIs, and enterprise applications
• Implement document processing, data extraction, and content generation workflows using AI techniques
• Create and maintain reusable automation components, templates, and integrations
• Develop and deploy LLM-based agents for specific automation use cases
• Write clean, well-documented code following established standards and patterns
• Participate in code reviews and contribute to improving codebase quality

Platform Optimization & Evaluation

• Implement evaluation methods to measure agent accuracy, reliability, and performance
• Develop and maintain monitoring dashboards for production automation workflows
• Optimize n8n workflow performance through efficient node design and error handling
• Apply prompt engineering and context engineering techniques to improve automation accuracy
• Support A/B testing and experimentation to improve automation outcomes
• Document automation performance metrics and track improvement over time
• Troubleshoot automation failures and implement fixes

Model Development & Fine-Tuning

• Support selection and evaluation of LLMs and SLMs for automation use cases
• Implement inference optimization strategies to improve latency and reduce costs
• Develop and maintain evaluation datasets for model performance assessment
• Implement retrieval-augmented generation (RAG) patterns for knowledge-intensive automation tasks
• Stay current with emerging AI technologies and recommend applications for automation
• Assist with fine-tuning and model customization for domain-specific tasks

Security & Compliance

• Follow Signant Health's security policies and healthcare industry regulations in all automation development
• Implement secure credential management and data handling patterns in automation workflows
• Ensure proper data classification and handling throughout automation pipelines
• Maintain audit logging for automated processes
• Participate in security reviews of automation solutions

Collaboration & Technical Leadership

• Collaborate with team members to develop and improve automation solutions
• Partner with business stakeholders to understand requirements and deliver solutions
• Work with the broader AI team to align on standards, tools, and approaches
• Communicate technical concepts and automation capabilities to non-technical audiences
• Contribute to documentation, knowledge sharing, and team learning initiatives
• Participate in agile ceremonies, sprint planning, and team discussions
• Support onboarding of new team members on automation tools and practices

Preferred Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience
• Strong candidates without formal degrees will be considered based on demonstrated expertise through portfolio, open-source contributions, or professional track record
• AWS Solutions Architect or Developer certification preferred
• AWS AI/ML certifications are a plus

Experience

Required:

• 5+ years of software engineering experience with strong proficiency in Python and production system development
• 2+ years of hands-on experience with workflow automation platforms, with strong expertise in n8n or similar tools (Zapier, Make, Temporal, Airflow)
• Extensive Python development experience with focus on automation, integrations, and API development
• Strong Python development experience with focus on automation, scripting, and API integrations
• Working knowledge of prompt engineering techniques for production systems
• Experience developing and implementing tests and evaluations for software systems
• Experience with RESTful APIs, webhooks, and system integration patterns
• Proficiency with version control (Git) and CI/CD concepts
• Solid understanding of software development best practices

Desired Qualifications

• Experience building and deploying AI/ML applications in production environments
• Experience in healthcare, life sciences, or clinical trials industry
• Familiarity with clinical trial workflows or healthcare data standards
• Familiarity with modern AI frameworks (Strands, LangChain, CrewAI, LlamaIndex) and model providers (Amazon Bedrock, Anthropic, OpenAI, Gemini)
• Knowledge of vector databases, embeddings, and RAG architectures
• Experience with AWS services (Lambda, Step Functions, API Gateway)
• Familiarity with containerization (Docker) and cloud deployment
• Experience with enterprise integrations (Salesforce, ServiceNow, Jira, Confluence)
• Background in natural language processing or document processing
• Experience with agile development methodologies