Senior AI Engineer
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Job Description
Senior AI Engineer at DevSavant designing healthcare-focused AI solutions for startups. Collaborating on AI systems, optimizing conversational agents, and ensuring healthcare compliance.
Responsibilities:
- Only candidates based in APAC will be considered for this position.
- Design and deploy healthcare-focused Agentic AI systems capable of autonomous, multi-step task execution (e.g., appointment scheduling, eligibility verification, intake automation, triage routing).
- Architect and optimize LLM-powered conversational agents across voice and digital channels.
- Develop Retrieval-Augmented Generation (RAG) architectures to power contextual, domain-specific healthcare knowledge systems.
- Engineer robust prompt frameworks, safety guardrails, and evaluation pipelines tailored to regulated healthcare environments.
- Continuously evaluate and improve agent performance, accuracy, and safety through structured experimentation and analytics.
- Architect advanced IVR modernization strategies and intelligent voice workflows.
- Optimize ASR (speech-to-text) and TTS (text-to-speech) systems to meet healthcare-grade accuracy and reliability standards.
- Integrate conversational AI into enterprise contact center platforms and CPaaS environments.
- Ensure seamless interoperability with EHR/EMR systems using healthcare standards such as FHIR and HL7.
- Design scalable, fault-tolerant architectures supporting high-availability healthcare operations.
- Develop NLP pipelines for clinical document summarization, coding support, PHI detection, and structured data extraction.
- Architect HIPAA-compliant AI systems with secure data handling, encryption, and role-based access controls.
- Implement monitoring, observability, and analytics frameworks to measure operational efficiency and patient experience outcomes.
- Maintain alignment with evolving healthcare AI regulatory and compliance requirements.
- Contribute reusable AI templates that power no-code and low-code deployment models.
- Build and maintain APIs and SDK integrations that allow enterprise customers to embed AI capabilities rapidly.
- Collaborate cross-functionally with product, solution engineering, and co-creation teams to accelerate customer time-to-value.
- Mentor junior engineers and define best practices for deploying Agentic AI in regulated industries.
- Provide internal technical leadership on scalable AI architecture and deployment standards.
Requirements:
- Design and deploy healthcare-focused Agentic AI systems capable of autonomous, multi-step task execution (e.g., appointment scheduling, eligibility verification, intake automation, triage routing).
- Architect and optimize LLM-powered conversational agents across voice and digital channels.
- Develop Retrieval-Augmented Generation (RAG) architectures to power contextual, domain-specific healthcare knowledge systems.
- Engineer robust prompt frameworks, safety guardrails, and evaluation pipelines tailored to regulated healthcare environments.
- Continuously evaluate and improve agent performance, accuracy, and safety through structured experimentation and analytics.
- Architect advanced IVR modernization strategies and intelligent voice workflows.
- Optimize ASR (speech-to-text) and TTS (text-to-speech) systems to meet healthcare-grade accuracy and reliability standards.
- Integrate conversational AI into enterprise contact center platforms and CPaaS environments.
- Ensure seamless interoperability with EHR/EMR systems using healthcare standards such as FHIR and HL7.
- Design scalable, fault-tolerant architectures supporting high-availability healthcare operations.
- Develop NLP pipelines for clinical document summarization, coding support, PHI detection, and structured data extraction.
- Architect HIPAA-compliant AI systems with secure data handling, encryption, and role-based access controls.
- Implement monitoring, observability, and analytics frameworks to measure operational efficiency and patient experience outcomes.
- Maintain alignment with evolving healthcare AI regulatory and compliance requirements.
- Contribute reusable AI templates that power no-code and low-code deployment models.
- Build and maintain APIs and SDK integrations that allow enterprise customers to embed AI capabilities rapidly.
- Collaborate cross-functionally with product, solution engineering, and co-creation teams to accelerate customer time-to-value.
- Mentor junior engineers and define best practices for deploying Agentic AI in regulated industries.
- Provide internal technical leadership on scalable AI architecture and deployment standards.
Benefits:
- Only candidates based in APAC will be considered for this position.
- 7+ years of experience in AI/ML engineering.
- 3+ years deploying AI solutions within healthcare or other regulated industries.
- Proven experience designing and deploying LLM architectures, including fine-tuning and advanced prompt engineering.
- Hands-on experience with voice automation systems (IVR, ASR, TTS).
- Experience integrating AI systems with enterprise platforms such as EHRs, CRMs, and contact centers.
- Strong Python expertise and experience with ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
- Experience deploying AI solutions in cloud-native environments (AWS, GCP, or Azure).
- Strong understanding of secure system design and data privacy principles.
- Nice to Have: Experience building AI agents capable of autonomous, multi-step workflows.
- Deep knowledge of healthcare interoperability standards (FHIR, HL7).
- Experience working with vector databases and semantic search architectures.
- Familiarity with FDA software guidance (SaMD).
- Background in conversational analytics and customer experience optimization.
- Experience contributing to reusable AI frameworks that support low-code/no-code platforms.
- Proven track record of delivering production-grade AI systems in high-compliance environments.
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