Senior AI Platform Engineer - Technology R&D

Careers Signant Health

About The Position

We are seeking a Senior AI Engineer focusing on automation responsible for designing, building, and optimizing AI-powered applications and agents that automate workflows across Signant Health. This role combines deep expertise in workflow automation platforms, prompt engineering, and context engineering to deliver intelligent automation solutions that improve operational efficiency and accuracy. The Senior AI Engineer will lead the development of n8n workflows, AI agent architectures, and integration patterns while mentoring team members and establishing best practices. Working closely with cross-functional teams, this individual will identify high-impact automation opportunities, architect scalable solutions, and drive the adoption of AI-powered automation throughout the organization. The ideal candidate brings extensive experience in building production-grade automation systems, a strong foundation in Python development, and proven ability to optimize LLM-based agents for reliability and accuracy in enterprise environments.

Requirements

7+ years of software engineering experience with strong proficiency in Python and production system development
3+ 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
Demonstrated expertise in prompt engineering and context engineering techniques for production systems
Strong experience designing and implementing evaluation frameworks for AI systems
Proven track record of delivering complex, enterprise-scale automation solutions
Experience with RESTful API design, webhooks, and system integration patterns
Solid understanding of LLM inference optimization, including techniques for latency reduction and cost management
Experience with vector databases, embeddings, and RAG architectures
Proficiency with version control (Git), CI/CD pipelines, and DevOps practices
Experience leading technical teams or projects and mentoring engineers
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

Nice To Haves

Experience building and deploying AI/ML applications in production environments
Experience in healthcare, life sciences, or clinical trials industry
Familiarity with clinical trial workflows, regulatory requirements (GxP, 21 CFR Part 11), and healthcare data standards
Familiarity with modern AI frameworks (Strands, LangChain, CrewAI, LlamaIndex)
Knowledge of model fine-tuning techniques and MLOps practices
Experience with AWS services (Lambda, Step Functions, SQS, EventBridge) for automation
Familiarity with Agentic AI patterns and autonomous agent architectures
Experience with enterprise integrations (Salesforce, ServiceNow, Workday, Jira, Confluence)
Background in natural language processing, information extraction, or document AI
Experience building automation centers of excellence
AWS Solutions Architect or Developer certification preferred
AWS AI/ML certifications are a plus

Responsibilities

Architect and develop sophisticated AI applications and agents that automate complex business workflows across the organization
Design and implement end-to-end automation solutions using n8n, custom Python integrations, and LLM-based agent frameworks
Build robust, scalable automation pipelines that integrate with internal systems, third-party APIs, and enterprise applications
Develop reusable automation components, templates, and libraries that accelerate solution delivery
Create intelligent document processing, data extraction, and content generation workflows using advanced AI techniques
Lead the design of multi-agent systems that coordinate complex, multi-step automation processes
Establish coding standards, design patterns, and architectural guidelines for automation development
Design and implement comprehensive evaluation frameworks to measure agent accuracy, reliability, and performance
Develop monitoring systems, observability dashboards, and alerting mechanisms for production automation workflows
Optimize n8n workflow performance through efficient node design, error handling, and resource management
Conduct systematic prompt engineering and context engineering to maximize automation accuracy and reduce hallucinations
Lead A/B testing and experimentation to continuously improve automation outcomes
Establish benchmarking methodologies and success metrics for automation initiatives
Perform root cause analysis on automation failures and implement systematic improvements
Lead selection and evaluation of LLMs and SLMs for specific automation use cases
Design and implement inference optimization strategies to reduce latency and cost while maintaining quality
Develop fine-tuning pipelines and approaches for domain-specific automation tasks
Create and maintain evaluation datasets and test suites for model performance assessment
Implement retrieval-augmented generation (RAG) patterns and knowledge base integrations
Research and prototype emerging AI technologies for automation applications
Establish model versioning, deployment, and rollback procedures
Ensure all automation solutions adhere to Signant Health's security policies and healthcare industry regulations
Implement secure credential management, data handling, and access control patterns in automation workflows
Conduct security reviews of automation architectures and third-party integrations
Design audit logging and compliance monitoring for automated processes
Ensure proper data classification and handling throughout automation pipelines
Collaborate with security teams to address vulnerabilities and maintain compliance certifications
Mentor and provide technical guidance to AI Engineers and other team members on automation best practices
Lead technical design reviews and architecture discussions for automation initiatives
Partner with business stakeholders to identify automation opportunities and translate requirements into technical solutions
Collaborate with the broader AI team to ensure alignment on standards, tools, and approaches
Present technical concepts and automation capabilities to non-technical audiences
Contribute to the AI automation roadmap and technology strategy
Foster a culture of innovation, experimentation, and continuous improvement
Represent Signant Health's AI automation capabilities to external partners and vendors