Agentic AI Engineer (LLM)
Tasks
- Build evaluation frameworks for AI systems
- Collaborate with cross-functional teams to deliver AI features
- Create technical documentation and reusable components
- Design develop and optimize LLM based AI agents
- Design function calling pipelines
- Design multi agent systems and agent orchestration
- Develop and maintain AI APIs and services
- Develop retrieval-augmented generation pipelines
- Fine-tune and align large language models
- Implement observability for AI agents
- Mentor junior engineers and conduct technical reviews
- Optimize model inference performance
- Research emerging AI technologies and frameworks
- Research evaluate and integrate foundation models
Perks/Benefits
- Annual health check-ups
- Opportunity to collaborate and learn from industry professionals
- Performance bonuses
- Preferential pricing for services
- Premium healthcare package
Skills/Tech-stack
A/B | A/B Testing | API Development | Agent Orchestration | Autogen | B testing | Batching | CI/CD | Caching | CrewAI | DPO | Docker | Embeddings | Function Calling | Generative AI | Git | Hugging Face | Hugging Face Transformers | Inference Optimization | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | LoRA | Logging | Model Distillation | Model Serving | Monitoring | Observability | PEFT | Preference optimization | Prompt engineering | PyTorch | Python | QLoRA | Quantization | Reranking | Retrieval-Augmented Generation | Routing | SFT | Semantic Kernel | Speculative decoding | Structured Output | Testing | Tool integration | Tracing | Transformer | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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