AI Lead Developer / Architect
Tasks
- Add guardrails
- Architect enterprise generative AI solutions
- Build RAG-architectures
- Deploy AI systems on Azure
- Design agentic AI workflows
- Design modular microservices
- Develop asynchronous distributed AI applications
- Develop backend AI services APIs and data pipelines
- Develop prompting techniques
- Implement AI governance and model lifecycle management
- Implement AI monitoring and observability
- Implement CI/CD pipelines
- Implement Model Context Protocol
- Implement evaluation pipelines
- Lead client and vendor AI engagements
- Mentor and manage AI/ML engineering teams
- Orchestrate multi-agent systems
- Productionize AI solutions with Docker
Perks/Benefits
Skills/Tech-stack
AI Services | API first | API-first design | Agent Orchestration | Agentic AI | Asynchronous programming | Azure AI | Azure AI Services | Azure ML | Azure OpenAI | CI/CD | Chain-of-Thought | Cloud Native | Containerization | Cost analysis | Distributed Systems | Docker | Embeddings | Evaluation Pipelines | Feature Engineering | Few-Shot Learning | Few-shot | Generative AI | Guardrails | Hallucination Tracking | Hyperparameter Optimization | Keras | Langchain | Langfuse | Langgraph | Language Models | Large Language Models | MCP | Microservices | Model Context Protocol | Model Evaluation | Multi-Agent | Multi-agent orchestration | Observability | OpenAI API | Prompt engineering | PyTorch | Python | RAG | ReAct agents | Retrieval-Augmented Generation | SQL | Scikit-learn | Self-reflection | Semantic Search | Structured outputs | Structured prompting | Telemetry | TensorFlow | Tool-Calling | Vector Databases | XGBoost | Zero-Shot | Zero-shot Learning
Education
N/A
Roles
AI | AI Architect | AI Lead | AI Lead Developer | Architect | Developer | Lead Developer
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