Lead Consultant - AI Application Engineering
Tasks
- Build secure scalable AI applications
- Conduct code reviews and audits
- Define AI application architecture
- Design microservices and containers
- Establish observability and incident response
- Evaluate and monitor model drift
- Implement REST APIs
- Integrate generative AI into workflows
- Lead end-to-end product delivery
- Manage data ingestion and feature stores
- Mentor engineers and build AI engineering culture
- Operationalize machine learning pipelines
- Pilot emerging AI tools and scale best practices
- Set up CI/CD and automated testing
Perks/Benefits
Skills/Tech-stack
AWS | Amazon Bedrock | Angular | Azure | CI/CD | Call Management | Data Warehousing | Django | Docker | Fine Tuning | Flask | Generative AI | Git | Google Cloud | JavaScript | Kubernetes | Microservices | NoSQL | Node.js | On-Call | On-call Management | OpenAI | Prompt engineering | PyTorch | Python | REST | React | Retrieval-Augmented Generation | SLOs | SQL | Scikit-learn | Snowflake | Telemetry | TensorFlow | Transformers | Vue.js
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Application Engineer | Application Engineer | Consultant | Developer | Engineer | Full Stack | Full Stack Developer | Lead | Lead Consultant
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