Senior Software Engineer I - AI/ML

New

Based in the United StatesFull-TimeSenior

Salary not disclosed

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Job Details

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, preferably including generative AI or LLM-based applications.
Strong understanding of machine learning infrastructure, data pipelines, and model deployment practices.
Experience designing and implementing scalable backend systems and APIs.
Familiarity with prompt engineering techniques and applied AI optimization strategies.
Strong problem-solving skills with the ability to balance short-term delivery and long-term architectural vision.
Ability to collaborate effectively across product, engineering, and business teams in a fast-paced environment.
Strong communication skills with the ability to translate complex technical concepts into clear, actionable insights.
Commitment to security, compliance, and responsible handling of sensitive or regulated data.

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.

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