AI Engineer (Agent Systems & LLM Platforms)
Tasks
- Build APIs and services for model interaction
- Build evaluation pipelines for AI outputs
- Build multi-agent orchestration
- Contribute to internal AI platforms and developer tooling
- Design AI agents
- Design chunking embedding and retrieval strategies
- Design scalable AI architectures
- Develop RAG pipelines
- Handle latency concurrency and cost optimization
- Implement prompt strategies and guardrails
- Implement scalable embedding pipelines
- Integrate and optimize LLMs
- Monitor system performance and user interactions
- Optimize reliability latency and cost
- Optimize similarity search and ranking
Perks/Benefits
- Development feedback framework
- Family support
- Hybrid work
- Meal allowance
- Onboarding buddy
- Private health insurance
- Unlimited Udemy access
Skills/Tech-stack
API Development | AWS | Azure | Azure OpenAI | CI/CD | Distributed Systems | Docker | Embeddings | Evaluation | Event Driven | Event-driven architecture | GCP | Information Retrieval | Kubeflow | Kubernetes | Language Models | Large Language Models | MLflow | Microservices | OpenAI | Prompt engineering | Python | Ranking | Retrieval-Augmented Generation | Semantic Search | Similarity Search | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer
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