Staff Software Engineer

Overview

On Site
Full Time

Skills

Dependability
Emerging Technologies
Health Care
Innovation
Storage
FOCUS
Scalability
Decision-making
Art
Data Security
Privacy
HIPAA
Continuous Improvement
Incident Management
Operational Excellence
Facilitation
Communication
Conflict Resolution
Problem Solving
Microsoft Excel
Regulatory Compliance
Adaptability
Software Engineering
Analytics
Data Science
Programming Languages
Python
Java
Scala
Real-time
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Machine Learning (ML)
TensorFlow
PyTorch
Lifecycle Management
Distributed Computing
Apache Spark
Kubernetes
Data Engineering
Machine Learning Operations (ML Ops)
Management
Artificial Intelligence
Collaboration
Effective Communication
Mentorship

Job Details

Our client is seeking a Staff Software Engineer in AI and Data Tech to join its remote-first team. This role offers the opportunity to shape the future of healthcare by building scalable platforms that power analytics, data science, and AI. You'll drive data-driven transformation, impacting millions.

Key Responsibilities:
As a Staff Software Engineer - AI and Data Technology within this forward-thinking digital health organization, you will be instrumental in shaping the architecture of next-generation platforms that support analytics and artificial intelligence initiatives. Your day-to-day responsibilities will center around building dependable infrastructure for large-scale data workloads while collaborating with cross-functional teams to ensure alignment on requirements. You will set the technical vision for enterprise-wide data ecosystems by evaluating emerging technologies and integrating them into existing frameworks. By mentoring fellow engineers and establishing best practices in platform engineering, including security compliance, you will foster an environment of shared success. Your efforts will drive continuous improvement in deployment strategies and monitoring processes, ensuring the organization remains at the forefront of healthcare innovation.
  • Drive the design, development, and deployment of scalable AI and data platforms that underpin analytics and machine learning capabilities throughout the organization.
  • Build and maintain reliable infrastructure for analytics and AI/ML workloads using best practices in MLOps/LLMOps, automation, and cloud-native technologies tailored to evolving business needs.
  • Architect robust systems for secure data ingestion, storage, processing, and model lifecycle management with a focus on scalability, reliability, monitoring, and futureproofing through automation.
  • Collaborate closely with analytics, data science, and machine learning teams to anticipate challenges, align requirements, and ensure platforms enable seamless data-driven decision-making.
  • Evaluate, adopt, and integrate state-of-the-art tools, frameworks, and technologies to optimize platform performance while setting the technical vision for enterprise-wide data ecosystems.
  • Provide mentorship to engineers across teams by fostering skill development in AI enablement while promoting a culture of collaboration and engineering excellence.
  • Establish best practices for platform engineering, including data security, privacy compliance standards (such as GDPR or HIPAA), governance protocols, and continuous improvement strategies.
  • Drive enhancements in deployment strategies as well as monitoring and incident response processes to ensure operational excellence across all data platforms.
  • Champion cross-functional enablement by facilitating communication between technical teams to deliver solutions that meet strategic objectives efficiently.
  • Lead technical projects from concept through delivery by guiding teams through complex problem-solving scenarios.
Key Requirements:
To excel as a Staff Software Engineer - AI and Data Technology in this organization, you will bring deep expertise in software engineering gained over several years working on complex analytics or artificial intelligence platforms. Your proficiency with modern programming languages allows you to build scalable solutions tailored for high-volume workloads. Experience architecting robust systems-whether it's designing secure data lakes or integrating real-time processing-will be essential. Familiarity with cloud-based infrastructures ensures you can leverage distributed computing resources effectively while supporting end-to-end model lifecycle management using industry-leading frameworks. Your understanding of MLOps/LLMOps practices means you can manage sophisticated pipelines efficiently. Beyond technical acumen, your collaborative approach enables you to communicate clearly across teams; your mentoring skills help foster growth among peers; your commitment to best practices ensures compliance with regulatory standards; your adaptability allows you to navigate ambiguity gracefully-all contributing towards shared organizational success.
  • Over eight years of experience in software engineering focused on building platforms for analytics, data science, or artificial intelligence applications within complex environments.
  • Proficiency in programming languages such as Python, Java, or Scala with demonstrated ability to develop scalable solutions for high-volume workloads.
  • Hands-on experience with AI-specific infrastructure, including model serving technologies (TensorFlow Serving or NVIDIA Triton), feature stores (Feast or Hopsworks), experimentation platforms (MLflow or Kubeflow).
  • Expertise in designing robust data architectures encompassing lakes, warehouses, as well as real-time processing systems optimized for performance.
  • Practical knowledge of cloud-based data platforms (AWS/Azure/Google Cloud Platform) along with associated tools for managing distributed computing resources.
  • Familiarity with machine learning frameworks (TensorFlow/PyTorch) integrated into production environments supporting end-to-end model lifecycle management.
  • Understanding of distributed computing technologies such as Spark or Kubernetes applied within large-scale data engineering contexts.
  • Experience implementing MLOps/LLMOps practices using modern tools for managing complex AI/data pipelines efficiently.
  • Demonstrated track record leading technical projects from inception through successful delivery while navigating ambiguous challenges collaboratively.
  • Exceptional collaboration skills enabling effective communication with cross-functional teams; proven ability to mentor others within an inclusive environment.
What sets this company apart:
  • This digital health organization stands out for its unwavering commitment to inspiring lifelong wellness through evidence-based care delivered via cutting-edge technology.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.