Job Responsibilities:
- Develop innovative AI/ML solutions and agentic systems for the LLM Suite platform using Azure, AWS, and AI Agentic frameworks.
- Integrate with AWS Cloud Services for compute, storage, databases, and security, as well as the Azure ecosystem.
- Create solutions or tools to provision and monitor infrastructure for LLM and agentic systems.
- Utilize operational skills to provide impactful recommendations for product, process, or policy improvements.
- Collaborate with the Product team to design, build, and deliver capabilities in agile sprints.
- Work with cross-functional teams, including data scientists, software engineers, and designers.
- Develop and implement state-of-the-art GenAI services leveraging Azure OpenAI models and AWS Bedrock service.
Required Qualifications, Capabilities, and Skills:
- Formal training or certification on software engineering concepts and proficient applied experience
- Strong hands-on experience with at least one programming language (Python/Java/Rust)
- Experience in developing microservices using Python with FastAPI.
- Commercial experience in both backend and frontend engineering
- Hands-on experience with AWS Cloud-based applications development, including EC2, ECS, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, EMR, and Kinesis.
- Strong engineering background in machine learning, deep learning, and neural networks.
- Experience with containerized stack using Kubernetes or ECS for development, deployment, and configuration.
- Experience with Single Sign-On/OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS.
- Solid understanding of backend performance optimization and debugging.
- Knowledge of AWS SageMaker and data analytics tools.
- Proficiency in frameworks TensorFlow, PyTorch, or similar.
Preferred Qualifications, Capabilities, and Skills:
- Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus.
- Python engineering experience
- React