AI Engineer
WRS Health
CloudPythonTensorflow
Senior Staff AI Architect
Confluent
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $193,800 - $227,700 per year
Job Level
Senior
Tech Stack
AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformKafkaKubernetesMicroservicesNoSQLPyTorchSQLTensorflowTerraform
About the role
- Incorporate AI technologies, such as machine learning models, natural language processing, or predictive analytics, into automation and event-driven workflows & data solutions.
- Contribute to the design, integrations and management of AI/ML solutions across SaaS platforms, systems, and databases, leveraging Confluent, AI-powered tools, and microservices patterns.
- Partner with cross-functional stakeholders to translate business needs into cohesive AI strategies and outcomes.
- Oversee and provide input on the design of microservices that align with modern cloud-native principles, enabling robust and reusable system components.
- Conduct technical design reviews, enforce best practices, and ensure the delivery of high-quality, secure, and maintainable solutions.
- Dedicate time to coach and mentor other team members.
Requirements
- A minimum of 8+ years in enterprise data, software architecture, or related fields, with 5+ years of hands-on experience in Kafka and event-driven systems.
- Proven track record of designing and implementing large-scale, cloud-native solutions leveraging Kafka, Flink, and AI-driven tools.
- Hands-on experience with feature stores, vector databases, or retrieval-augmented generation (RAG) for real-time AI.
- Experience optimizing large-scale, real-time systems for low latency, high throughput, and cost efficiency.
- Demonstrated ability to leverage AI to build and deliver compelling data solutions
- Strong understanding of event-driven architecture, stream processing (Kafka Streams, Flink), and distributed systems.
- Proficiency in microservices architecture, RESTful APIs, and modern DevOps practices (CI/CD pipelines).
- Strong background in cloud platforms (AWS, GCP, or Azure), including infrastructure as code (e.g., Terraform).
- In-depth knowledge of SQL and NoSQL database technologies.
- Familiarity with containerization and orchestration tools (Docker, Kubernetes).
- Familiarity with TensorFlow, PyTorch, Hugging Face, or other ML libraries.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningnatural language processingpredictive analyticsKafkaFlinkfeature storesvector databasesretrieval-augmented generationSQLNoSQL
Soft skills
coachingmentoringcollaborationcommunication
