Senior AI Software Engineer
Tasks
- Define GenAI governance for safety security and responsible use
- Define LLM observability and evaluation standards
- Develop scalable reliable and secure code
- Estimate and assess feasibility for complex cross functional initiatives
- Evaluate prototype and document emerging AI tools and techniques
- Lead design and development of enterprise GenAI solutions
- Provide secure coding design patterns and performance optimization
- Serve as technical authority on LLMs and agentic systems
Perks/Benefits
- Career growth
- Comprehensive benefits
- Continuous learning
- Generous paid time off
- Healthcare
- Hybrid work
- Retirement plan
- Work-life balance
Skills/Tech-stack
Agent Orchestration | Agent systems | Arize | Azure SQL | Context engineering | Embeddings | Integration Testing | LLM Evaluation | LLM Observability | Langchain | Langgraph | Langsmith | Language Models | Large Language Models | Multi-Agent | Multi-Agent Systems | OWASP Top | OWASP Top 10 | PostgreSQL | Prompt engineering | PromptFlow | PyTorch | Pytest | Python | RAG | REST APIs | Ragas | Retrieval-Augmented Generation | SOLID | SQL Server | Scikit-learn | Semantic Kernel | Semantic similarity | Structured outputs | TensorFlow | Top 10 | Unit Testing | Vector Databases
Education
N/A
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