Senior AI Engineer

*Only candidates based in APAC will be considered for this position.

About DevSavant

DevSavant 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 Responsibilities

Agentic AI & Conversational Systems

• 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.

Voice Automation & Infrastructure

• 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.

Healthcare AI & Compliance

• 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.

Platform & Developer Enablement

• 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.

Required Qualifications

• 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.