Senior Software Engineer- AI Platform(US)

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.