United States onlyThis position is posted by Jobgether on behalf of [Omada Health]. We are currently looking for a [Staff Software Engineer, AI and Data Technology] in [United States].
This is a high-impact engineering role dedicated to building the foundation that powers analytics, data science, and AI across the organization. As Staff Software Engineer, you will architect scalable, secure, and efficient platforms that enable advanced AI/ML workloads and data-driven decision-making. You will set technical vision, adopt emerging technologies, and optimize performance across cloud-native environments. Working closely with cross-functional teams, you’ll anticipate challenges, align on requirements, and ensure robust enablement of business-critical initiatives. This position offers the opportunity to drive innovation, mentor engineers, and influence the future of data and AI infrastructure at scale.
Accountabilities
- Lead the design, development, and deployment of scalable AI and data platforms, leveraging best practices in MLOps/LLMOps, automation, and cloud-native engineering.
- Architect secure and high-performance systems for ingestion, storage, processing, and model lifecycle management, optimized for scalability and monitoring.
- Collaborate with analytics, data science, and ML teams to enable reliable decision-making through robust platform support.
- Evaluate and integrate cutting-edge frameworks and tools to enhance platform performance, cost-efficiency, and long-term sustainability.
- Provide mentorship and guidance to engineers, fostering innovation and technical excellence across teams.
- Establish and enforce best practices for governance, data privacy, compliance, and deployment standards.
- Drive continuous improvements in automation, observability, and incident response processes.
Requirements
- 8+ years of software engineering experience, with a focus on building platforms for analytics, AI, and data science.
- Proficiency in programming languages such as Python, Java, or Scala.
- Expertise with AI infrastructure including model serving platforms, feature stores, and experimentation frameworks.
- Experience architecting data systems such as lakes, warehouses, and real-time processing solutions.
- Strong knowledge of cloud platforms (AWS, Azure, GCP) and distributed computing technologies (e.g., Kubernetes, Spark).
- Familiarity with machine learning frameworks (TensorFlow, PyTorch) and MLOps/LLMOps practices.
- Demonstrated ability to lead projects end-to-end, from vision to delivery.
- Excellent problem-solving, communication, and collaboration skills with cross-functional stakeholders.
- Bonus points for familiarity with governance and compliance frameworks (HIPAA, GDPR) and BI tool integrations (Looker, Tableau, Power BI).
Benefits
- Competitive salary: $193,600–$253,000 depending on location and experience.
- Annual cash bonus and equity grants.
- Remote-first work environment with flexibility.
- Generous vacation and parental leave policies.
- Health, dental, and vision insurance with above-market contributions.
- 401(k) retirement savings plan.
- Lifestyle Spending Account and mental health support.
- Inclusive culture with a strong commitment to diversity, equity, and belonging.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.
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