Company
Healthcare
SeniorSoftwareEngineer-AI/ML
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer - AI/ML. Skills: AI/ML systems, Generative AI, Large Language Models, Backend systems. Design AI/ML-enabled systems. Develop AI/ML-enabled systems”
What You'll Achieve.
Improve effectiveness; Improve reliability; Improve accuracy; Ensure system reliability; Ensure system performance
Industry & Context.
Problem-solving; Analytical skills
What They're Looking For.
Must Have
Bachelor’s degree in Computer Science, 4+ years software engineering experience, 2+ years technical decision-making, 2+ years mentoring engineers, Hands-on AI/ML systems experience, Experience designing backend systems, Experience implementing backend systems, Experience implementing APIs, Commitment to security, Commitment to compliance, Commitment to data handling
Nice to Have
Experience with generative AI, Experience with LLM-based applications, Understanding of ML infrastructure, Understanding of data pipelines, Understanding of model deployment, Familiarity with prompt engineering, Familiarity with applied AI optimization
What You'll Do.
Design AI/ML-enabled systems
Develop AI/ML-enabled systems
Implement AI/ML-enabled systems
Improve AI/ML infrastructure
Evolve AI/ML infrastructure
Enhance model capabilities
Develop prompt engineering strategies
Refine prompt engineering strategies
Collaborate with product managers
Collaborate with engineering leaders
Collaborate with stakeholders
Define technical roadmaps
Execute technical roadmaps
Contribute to API design
Contribute to system integration
Embed AI capabilities
Analyze system performance
Analyze product trends
Maintain observability practices
Mentor junior engineers
Coach junior engineers
Provide technical guidance
Solve problems collaboratively
Protect patient information
How You'll Work.
Team & Collaboration
Cross-functional teams; Product managers; Engineering leaders; Cross-functional stakeholders; Product teams; Engineering teams; Business teams
Communication Scope
Translate technical concepts
Process & Methodology
Agile methodologies, Technical roadmaps
Full Job Description
## Accountabilities Design, develop, and implement scalable and high-performance AI/ML-enabled systems supporting web applications, data pipelines, and production environments. Improve and evolve AI/ML infrastructure for model development, training, deployment, and monitoring, with a focus on generative AI and large language models. Architect systems that enhance model capabilities, ensuring data is structured, accessible, and optimized for machine learning and AI applications. Develop and refine prompt engineering strategies to improve the effectiveness, reliability, and accuracy of generative AI outputs. Collaborate with product managers, engineering leaders, and cross-functional stakeholders to define and execute technical roadmaps using Agile methodologies. Contribute to API design and system integration efforts that embed generative AI capabilities into healthcare platforms and applications. Analyze usage data, system performance, and product trends to inform AI strategy and prioritize high-impact use cases. Maintain strong observability practices, including monitoring, alerting, testing, and incremental release strategies to ensure system reliability and performance. Mentor and coach junior engineers through code reviews, technical guidance, and collaborative problem-solving. Ensure compliance with healthcare data security standards, including the protection of sensitive patient information within AI systems. Requirements: Bachelor’s degree (or higher) in Computer Science, Engineering, or a related technical field. 4+ years of experience in full-stack software engineering within cross-functional teams. Strong experience working with SQL or similar query languages on large, complex datasets. 2+ years of experience contributing to technical decision-making in engineering teams with a focus on business value delivery. 2+ years of experience mentoring, coaching, or supporting the growth of other engineers. Hands-on experience building or supporting AI/ML systems,
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