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We are looking for a hands-on AI Architect to deliver technical designs and implementations of internal AI tools. This is a hybrid role where you will act as a software architect, a lead engineer, and a technical partner to the business. You will be responsible for taking vague business problems and turning them into reliable, secure AI software solutions. You will be instrumental in defining the architecture and writing the code that runs in production.
Job Responsibility:
Design AI integrations that can securely read from and write back to core platforms
Architect the integration layer between external LLM providers and internal data
Design a model-agnostic inference layer
Write production-ready code using modern agent frameworks
Implement robust RAG pipelines to ground AI responses in company data
Set up the CI/CD pipelines and infrastructure
Implement automated testing frameworks to measure response accuracy, latency, and costs
Ensure strict handling of PII and adherence to enterprise security standards
Partner with leaders in Sales, Marketing, and Support to identify high-impact automation opportunities
Requirements:
8+ years of experience in software development with strong proficiency in Python and API design (REST)
2+ years of experience building LLM-powered applications or agents (using libraries like LangChain or ADK)
Experience with Vector Databases (e.g., Pinecone, pgvector) and building pipelines to process unstructured text
Hands-on experience deploying services on AWS, Azure, or GCP
Proven experience integrating custom applications with SaaS platforms like Salesforce, NetSuite, or Zendesk
Ability to explain technical concepts to non-technical stakeholders and collaborate effectively with product managers and business analysts
Nice to have:
Hands-on experience with GCP Vertex AI features and technologies (Agent Engine, RAG Engine etc)