Required Skills and Experience
• Engineering Foundation: 7+ years of software engineering experience with a deep understanding of design patterns, clean architecture, and distributed systems.
• AI/ML Expertise:
o Hands-on experience integrating LLMs into production applications.
o Proficiency in orchestration frameworks (LangChain, LangGraph, PydanticAI, etc.).
o Deep understanding of RAG architectures, vector databases (e.g., Pinecone, Milvus), and prompt engineering.
• Backend Mastery: Expert-level proficiency in Python (FastAPI/Flask). Strong experience building RESTful and async, event-driven architectures (message queues/event buses).
• DevOps & Infrastructure:
o IaC: Proven experience with Terraform, AWS CloudFormation, or Pulumi.
o CI/CD: Experience building production-grade deployment pipelines.
o Cloud: Hands-on experience with major cloud platforms (AWS, Azure, or Google Cloud Platform).
• Observability: Practical experience configuring and maintaining monitoring stacks (Datadog, Grafana, Prometheus) to track application performance, errors, and LLM-specific telemetry (cost/latency).
• Security: Strong background in secure API development, including implementing and managing OAuth 2.0 and mTLS.
• Leadership: Demonstrated ability to lead technical initiatives, mentor engineers, and communicate complex trade-offs to non-technical stakeholders.
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