Forward Deployed Engineer – Agentic AI for Clinical Development

• 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.

• 6+ 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.

Preferred:

• 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.

• Up to 75% travel required (customer sites, industry events, internal meetings); flexible to accommodate personal preferences where possible.
• Blend of remote work, on-site customer embedding, and occasional office collaboration (if applicable).