Forward Deployed AI Engineer - LLM

Job Overview :

We are seeking a highly motivated and technically skilled Forward Deployed AI Engineer to bridge the gap between our cutting-edge AI technologies and real-world healthcare applications.

In this role, you'll work directly with enterprise healthcare clients, deploying AI-powered voice and conversational solutions tailored to their workflows.

You'll collaborate cross-functionally with sales, customer success, and product teams to ensure successful integrations, optimize performance, and help shape the future of AI in healthcare.

This is a dynamic, hybrid role that combines software engineering, customer success, and AI experimentation. Perfect for someone who thrives in fast-paced environments and wants to make a tangible impact on patient outcomes and healthcare efficiencies.

Key Responsibilities :

• Collaborate with Sales, Solutions Engineering, and Customer Success teams to manage end-to-end AI solution deployments for healthcare clients.
• Customize integrations, resolve technical challenges, and guide clients through onboarding and deployment with a focus on rapid time-to-value.
• Provide technical consulting and act as a trusted partner for client teams throughout the solution lifecycle.
• Design, simulate, and deploy AI voice agents to mimic real-world and edge-case scenarios in healthcare environments.
• Identify workflow gaps, agent blind spots, and performance bottlenecks across clinical and operational use cases.
• Continuously fine-tune the performance of AI agents based on customer feedback and system-level metrics.
• Act as a customer advocate, collecting insights from real-world usage and collaborating with product and engineering teams to shape the roadmap.
• Translate client needs into actionable technical requirements, driving enhancements and new features.
• Participate in internal product reviews to share deployment challenges, successes, and industry trends.
• Lead technical workshops and training sessions with enterprise stakeholders and engineering teams.
• Build custom demos and prototypes for sales support and pilot evaluations.
• Create and maintain high-quality technical documentation, onboarding guides, and developer toolkits.
• Experiment with large language models (LLMs) and prompt engineering to improve conversational AI agent accuracy and contextual understanding.
• Explore voice AI enhancements to increase agent fluency, responsiveness, and adaptability in clinical interactions.
• Stay current with trends in GenAI, NLP, voice tech, and machine learning infrastructure.

Required Qualifications :

(ref : hirist.tech)