Forward Deployed Engineer - Agentic AI for Clinical Development

Medable is dedicated to accelerating the delivery of effective therapies to patients through their innovative clinical trial platform. The Forward Deployed Engineer will lead technical engagements with clients, design and implement AI systems for clinical development, and ensure compliance and integration of agentic AI solutions in healthcare settings.

Responsibilities:

• Lead technical engagements with prospective and existing customers, acting as the primary solution consultant, technical advisor, and embedded engineer for agentic AI and agent system deployments
• Partner directly with customer stakeholders—from clinical operations, data science, and IT teams to C-level executives—to scope requirements and deploy agentic AI systems that enable autonomous clinical development workflows with built-in human oversight
• Design, architect, and implement tailored solutions integrating Medable’s platform with eClinical systems (EDC, eCOA, CTMS, RTSM/IWRS), enterprise environments, and agentic AI frameworks to build autonomous systems powered by agent systems for end-to-end trial automation
• Demonstrate Medable capabilities through live demos, technical deep dives, proof-of-concepts, and production deployments of agentic AI, showcasing autonomous agents, reasoning loops, multi-agent orchestration, and goal-driven adaptation in clinical contexts
• Build, deploy, and optimize agentic AI and agent systems in regulated environments, enabling autonomous capabilities such as real-time patient matching, adaptive protocol execution, predictive risk mitigation, automated data reconciliation, and trial simulation—while enforcing human-in-the-loop safeguards (supervision loops, safety gates, audit trails, and escalation protocols)
• Incorporate robust human-in-the-loop systems throughout agentic deployments, including intervention points, validation workflows, and hybrid decision-making to maintain compliance, ethical standards, and human accountability in autonomous clinical operations
• Wrangle large-scale clinical, real-world, and operational data to power agentic AI reasoning and agent coordination, accelerating autonomous insights while ensuring seamless integration with human review processes
• Develop custom integrations, APIs, configurations, and tooling to support agentic AI autonomy and agent system interoperability, addressing customer-specific needs like decentralized trial flows or adaptive designs
• Troubleshoot and refine agentic AI deployments on-site or remotely, optimizing for scalability, reliability, low-latency reasoning, and effective human-AI collaboration in production clinical environments
• Collaborate with product, engineering, and go-to-market teams to relay field insights from agentic AI deployments, prioritizing features for autonomous clinical systems with human safeguards, and influencing roadmap decisions
• Contribute to RFPs, technical proposals, solution designs, and executive presentations highlighting the transformative impact of agentic AI and agent systems in enabling autonomous yet compliant clinical development
• Drive adoption, quantify impact (e.g., reduced enrollment timelines, minimized protocol deviations, improved data integrity), and expand customer relationships to support revenue growth and sustained success
• Other duties as assigned in a fast-evolving, AI-driven environment

Requirements:

• 10+ years of hands-on experience in technical consulting, solution engineering, forward deployed engineering, or implementation roles—ideally in life sciences, clinical research, health tech, or regulated AI-intensive industries (or equivalent combination of education and experience)
• Proven track record deploying agentic AI systems and agent systems, including autonomous agents, goal-oriented reasoning, multi-agent orchestration, adaptive planning, tool-use integration, and iterative execution in complex, dynamic environments
• Extensive experience designing and deploying regulated agentic AI with strong governance, auditability, compliance (e.g., GCP, 21 CFR Part 11, GDPR), and human-in-the-loop mechanisms to enable safe autonomous clinical development workflows (e.g., automated monitoring, adaptive trials, real-time decision support)
• Demonstrated expertise in agent systems and agentic AI patterns—such as reasoning loops, multi-agent collaboration, retrieval-augmented execution, and guardrail frameworks—applied to clinical or life sciences use cases
• 1+ years of post-college software engineering experience with end-to-end ownership in high-stakes, dynamic projects involving AI agent deployments
• Strong background in enterprise integrations, cloud platforms (AWS/Azure/GCP), APIs, data pipelines, modern architectures, and large-scale data handling to support agentic AI autonomy
• Deep expertise in eClinical technologies (EDC, eCOA, CTMS, RTSM/IWRS) and interoperability standards (e.g., FHIR, CDISC, HL7), with proven ability to integrate them into agentic AI-driven autonomous systems
• Proficiency in technical platform implementation for building, deploying, and orchestrating agent systems and agentic AI automations
• Strong knowledge of data structures, storage systems, cloud infrastructure, front-end frameworks, and AI tooling (e.g., LLMs, vector databases, agent frameworks) for reasoning, planning, and multi-agent coordination
• Exceptional ability to translate complex agentic AI and autonomous system concepts into clear business value for clinical stakeholders
• Outstanding communication, presentation, relationship-building, and stakeholder management skills across technical and executive levels
• Highly analytical mindset with eagerness to solve ambiguous, high-impact problems using agentic AI in regulated clinical settings
• Comfort thriving in fast-paced, evolving environments with shifting priorities and direct customer exposure, particularly in deploying human-supervised autonomous systems
• Team collaboration skills in mixed technical/non-technical settings
• Bachelor's, Master's, or PhD in Computer Science, Engineering, Life Sciences, Data Science, Mathematics, Physics, or a related field
• Direct experience in clinical trials, decentralized trials, digital health, or pharma/biotech operations with agentic AI-enabled autonomy
• Familiarity with enterprise LLM/agent frameworks, advanced agentic tooling, or platforms for regulated multi-agent deployments
• Prior exposure to large-scale data/AI platforms in regulated industries