Lead AI Platform Engineer

Location: Blue Bell

About Signant Health
At Signant Health, we help bring life-changing treatments to patients faster. We are a global evidence generation company that supports clinical trials with smart technology, scientific expertise, and hands-on operational support - so better data leads to better decisions in healthcare. We embrace AI and advanced technologies to enhance every aspect of what we do, from data analysis to operational efficiency.
Our teams work at the intersection of science, technology, and patient experience, delivering digital solutions powered by AI innovation that make clinical trials more efficient, more accurate, and more accessible around the world. Trusted by leading pharmaceutical companies and CROs, our platforms and services support studies across more than 90 countries and have contributed to hundreds of new drug approvals.
If you are motivated by meaningful work, global impact, and innovation in clinical research and digital health - including the opportunity to work with cutting-edge AI technologies - you will find purpose and opportunity at Signant Health.
Lead AI Platform Engineer
We are seeking a Lead AI Platform Engineer to build and optimize Signant Health's AI Platform and agents that automate workflows across our organization. This role sits at the intersection of application development and model optimization, requiring both strong software engineering fundamentals and expertise in generative AI technologies. You'll be responsible for developing and optimizing our AI platform components, developing intelligent agents, implementing RAG systems, and ensuring high-quality, secure, and compliant AI responses through rigorous evaluation frameworks and robust guardrails.
This position offers the opportunity to shape how AI transforms our organization's operations, working on production systems that directly impact efficiency and innovation across multiple teams while maintaining the highest standards of data security, privacy, and regulatory compliance.

Essential Duties and Responsibilities
Application Development

Design and implement AI-powered agents that automate complex, multi-step workflows across the organization
Build RAG (Retrieval-Augmented Generation) systems using vector stores and knowledge bases to ground AI responses in organizational knowledge
Develop prompt engineering strategies and context optimization techniques to maximize accuracy and reliability of AI outputs
Create integrations between AI systems and existing tools, APIs, and data sources
Implement memory systems and state management for conversational agents and long-running workflows

Platform Optimization & Evaluation

Develop comprehensive evaluation frameworks to measure accuracy, relevance, and quality of AI system responses
Design and execute experiments to optimize agent performance, including A/B testing of different prompting strategies
Monitor production AI systems and implement improvements based on performance metrics and user feedback
Optimize inference costs and latency while maintaining quality standards
Build tooling and dashboards for observability into AI system behavior

Model Development & Fine-Tuning

Engineer datasets for training and fine-tuning language models on organization-specific tasks
Implement and evaluate fine-tuning pipelines for LLMs and SLMs (Small Language Models)
Optimize model inference for production environments, balancing speed, cost, and quality
Conduct experiments to determine when fine-tuning, prompt engineering, or RAG approaches are most appropriate
Stay current with advances in language models and evaluate new models for potential organizational use

Security & Compliance

Design and implement guardrails and content filtering mechanisms to prevent harmful or inappropriate AI outputs
Develop hallucination detection and mitigation strategies to ensure factual accuracy and reliability of agent responses
Establish security policies for AI systems including data access controls, prompt injection prevention, and sensitive information handling
Create compliance frameworks that align AI systems with regulatory requirements (GDPR, HIPAA, SOC2, etc.) and industry standards
Implement monitoring and alerting systems to detect anomalous AI behavior, security incidents, or compliance violations
Conduct AI safety assessments and red-teaming exercises to identify vulnerabilities and edge cases
Document AI decision-making processes and maintain audit trails for regulatory review and internal governance
Collaborate with security, legal, and compliance teams to ensure AI systems meet organizational risk management standards

Collaboration & Technical Leadership

Partner with business stakeholders to identify high-impact automation opportunities
Document AI system architectures, design decisions, and best practices
Contribute to technical standards and guidelines for AI development across the organization
Mentor team members on AI technologies and share knowledge through internal presentations or documentation
Participate in code…