Senior Software Engineer- AI Platform(US)
- Point Click Care
- Remote USA
Job Description
What your day-to-day will look like:
· Identify, prioritize and execute tasks in the software development life cycle
· Work with business to iterate over software requirements
· Develop tools and applications by producing clean, efficient code
· Automate tasks through appropriate tools and scripting
· Analyze and debug systems
· Perform validation and verification testing in a test-driven manner
· Review the work of others, and invite others to review your work
· Collaborate with internal teams and vendors to fix and improve products
· Ensure software is up-to-date with latest technologies
What qualifications we’re looking for:
· Experience writing clean code that performs well at scale using Java (or other functional or object-oriented languages).
· Experience with Azure cloud services or equivalent
· Experience with cloud native streaming using Azure Event Hub/Service Bus (or others, such as AWS Kinesis, Google Pub/Sub)
· In-depth knowledge of relational databases (e.g. Microsoft SQL Server, PostgreSQL)
· Experience with GitHub Actions, Jenkins CI/CD pipeline
· Experience with Spring Boot
· Solid experience writing RESTful API endpoints
Absolutely love TDD and have working knowledge of it
· Proficient in GIT
· Experience using system and performance monitoring tools (e.g. Azure Log Analytics, Grafana, DataDog)
· Experience with automated testing frameworks (e.g. Selenium, Cypress,Jest, Playwright)
· Excellent organization, critical-thinking and personal leadership skills
· Self-starter with the ability to deliver with minimal supervision
· Being okay with the uncomfortable feeling that comes from learning new things
· Team player
· Analytical mind with problem-solving aptitude
· BSc/BA in Computer Science or a related degree
Generative AI Code Assistants
- Use of Generative AI Code Assistants (e.g. GitHub Copilot) is a must and working knowledge of spec-driven development. Daily application of the latest Generative AI Model capabilities is a must.
- Extensive experience building and maintain AI platform infrastructure, Kubernetes, and container security.
- Demonstrated expertise in observability, and monitoring frameworks, with a focus on real-time performance (i.e: experience with OpenTelemetry, NLPFlow).
- Experience with AI infrastructure components such as vector databases, prompt/versioning stores, and AI IDEs.
Bonus points for:
· Experience with Kafka, or Kafka compatible platforms (e.g. Redpanda, WarpStream, or others)
· Experience with integration engines such as Rhapsody, Mirth, or others
· Experience with message brokers such as RabbitMQ·
· Experience with Docker, Kubernetes and Istio
· Experience with Ansible
· Experience with SAML, OAuth and OpenID Connect
· Experience working on a SaaS product
· Experience with Service Oriented Architecture
· Knowledge of scripting languages such as Python, Bash
- Familiarity with vLLM, SGLang or similar framework to host LLM inference workloads.
- Experience with CI/CD pipelines and automation for AI model deployment and platform operations
- Strong knowledge of authentication and authorization frameworks integrated into AI platforms.
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