Medecision is looking to solve the problem of providing market-transforming solutions for businesses, care teams, and consumers to interactively manage health and care by building a scalable, secure, and compliant AI foundation
Requirements
- 10+ years in software engineering, with at least 5 focused on AI/ML infrastructure and MLOps
- Proven track record of building and scaling AI/ML platforms in healthcare, life sciences, or other regulated industries
- Deep expertise with modern AI stacks (vector DBs, orchestration frameworks, distributed training, RAG pipelines, LLM ops)
- Strong understanding of cloud environments (Azure, AWS, GCP) and compliance frameworks (HIPAA, HITRUST, SOC 2)
- Experience leading cross-functional engineering teams and partnering with data scientists and product managers
- Ability to operate at both strategic and hands-on levels in a fast-moving environment
- Evaluate and integrate third-party AI platforms (e.g., OpenAI, Vertex, Azure AI, Mistral)
Responsibilities
- Design and build Medecision’s AI/ML infrastructure (data pipelines, embeddings store, orchestration, monitoring, vector DBs, and model registry)
- Establish MLOps best practices for deploying, monitoring, and updating AI models at scale
- Build and lead a team of AI/ML engineers, data engineers, and platform architects
- Partner with Applied AI Research to accelerate the transition from innovation to production
- Collaborate with Product and Clinical teams to embed AI seamlessly into workflows
- Implement frameworks for explainability, bias mitigation, auditability, and compliance with CMS, HIPAA, and payer standards
- Ensure data privacy and security are foundational to every AI initiative
Other
- Location: Remote (US based)
- Reports to: Chief Executive Officer
- Dotted line to: Head of Applied AI Research (Medecision AI)
- 10+ years in software engineering
- Ability to operate at both strategic and hands-on levels in a fast-moving environment
