*Only candidates based in APAC will be considered for this position.
About DevSavantDevSavant is an operating partner for startups and growth-stage companies, helping them turn ambition into execution.
We support founders and leadership teams with product engineering and global staffing, from early prototypes and MVPs to scaling high-performing teams. Our vetted talent across LATAM and Asia embeds directly into client teams, operating as true extensions rather than external vendors.
With over 8 years working in venture-backed ecosystems, DevSavant is trusted to accelerate delivery, scale teams efficiently, and support companies as they reach their next milestone.
Key ResponsibilitiesAgentic AI & Conversational SystemsDesign 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.
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.
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.
