Mid-Level AI Software Engineer (Python)
Tasks
- Analyze design test develop and maintain software and AI enabled products
- Apply SRE practices and AI evaluation techniques
- Apply compliance risk data privacy and security best practices in software and AI development
- Build and integrate generative AI solutions RAG pipelines and vector database retrieval
- Communicate progress blockers and risks early and collaborate to deliver incremental features
- Create prototypes and proofs of concept for GenAI agentic frameworks and vector search
- Develop and enhance agentic AI systems plan reason retrieve and invoke tools under guardrails
- Develop production ready testable code for components services and AI workflows
- Implement AI enabled solutions using architectural patterns for scalability reliability performance and cost
- Perform code reviews and incorporate feedback to meet engineering security and compliance standards
- Troubleshoot model output quality issues and root cause analysis for software and AI components
Perks/Benefits
Skills/Tech-stack
AI Evaluation | AI Search | Agentic AI | Agile methodology | Azure AI | Azure AI Search | Code review | Data Privacy | DevOps | Faiss | Generative AI | Graph Databases | Knowledge graphs | Langchain | Langgraph | Machine Learning | Neo4j | OpenSearch | Pinecone | Prompt engineering | Python | REST APIs | Reliability Engineering | Retrieval-Augmented Generation | Security Compliance | Semantic Search | Software Reliability Engineering | Software reliability | Software testing | TigerGraph | Tool invocation | Vector Databases | Weaviate | Workflow Orchestration
Education
Roles
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