Principal Engineer
Tasks
- Architect scalable secure highly available cloud systems
- Conduct cross team architectural reviews and define trade offs
- Define DevOps SRE and MLOps practices
- Define and evolve AI ML platform vision
- Develop LLM based applications RAG pipelines and agentic workflows
- Drive adoption of AI assisted coding practices
- Evaluate select and integrate open source frameworks
- Implement CI/CD and Infrastructure as Code
- Implement observability and model monitoring for AI systems
- Lead end to end AI solution design and delivery
- Manage ML model lifecycle and deployment
- Mentor engineers through coaching design reviews and technical deep dives
- Review pull requests and guide key technical design decisions
- Set engineering excellence standards for security performance scalability observability
- Stay current with generative AI LLMs and applied ML trends
- Write production grade backend code and build prototypes
Perks/Benefits
- N/A
Skills/Tech-stack
AKS | AWS | AWS Bedrock | Access Management | Accessibility | Agile | Airflow | Angular | Anthropic APIs | Azure | Azure OpenAI | CI/CD | Caching | Camunda | CloudFormation | Data Pipelines | Data Privacy | DevOps | Distributed Computing | Docker | ECS | Event Driven | Event-driven architecture | Fine Tuning | GCP | GDPR | Go | Grafana | High Throughput | High-throughput data | High-throughput data pipelines | Hugging Face | ISO 27001 | Identity and Access Management | Identity and access | Infrastructure as Code | Java | Kubernetes | Langchain | Llamaindex | MLOps | Microservices | Model Monitoring | Node.js | Open Source | OpenAI APIs | OpenTelemetry | Prometheus | Prompt engineering | PyTorch | Python | Queueing | React | Retrieval-Augmented Generation | SOC 2 | SRE | SageMaker | Scikit-learn | Secure Coding | Temporal | TensorFlow | Terraform | Vector Databases | Vertex AI | Vue | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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