Applied AI Engineer
New
J
JobgetherAI Engineering
Remote opportunities across the United States, Canada, Europe, or AustraliaFull-TimeMiddle
Salary130,000 - 160,000 USD per year
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Job Details
- Required Skills
- GraphQLFull Stack DevelopmentSnowflakeReactRESTful APIsBigQueryLangChain
Requirements
- Demonstrated experience building and deploying production AI applications that real users depend on.
- Strong full-stack engineering capabilities, including frontend development with React.
- Backend experience with REST and/or GraphQL, authentication patterns, and cloud-native architectures.
- Hands-on experience with agentic frameworks or LLM APIs such as LangChain, LlamaIndex, Anthropic, or OpenAI.
- Experience implementing RAG patterns, streaming responses, and intuitive user interfaces.
- Experience designing evaluation harnesses and LLM observability solutions using tools such as Langfuse, LangSmith, or Braintrust.
- Familiarity with multi-model routing and inference cost optimization technologies like LiteLLM or Portkey.
- Experience with data platforms such as Snowflake or BigQuery.
- Practical knowledge of AI application security, including PII handling, secrets management, prompt-injection defense, and API audit logging.
- Strong product intuition and ability to prioritize user needs when selecting models and architectures.
- Ability to write design documentation, conduct postmortems, and explain technical failures to non-technical stakeholders.
Responsibilities
- Lead the architecture and implementation of AI-powered full-stack applications from wireframes to production-quality interfaces.
- Build and integrate applications using agent infrastructure, vector databases, and intelligence-layer capabilities.
- Translate POC blueprints into production applications with measurable evaluation frameworks and observability.
- Develop evaluation harnesses, instrumented traces, and monitoring to ensure AI behavior is trustworthy.
- Integrate applications with core data infrastructure like Snowflake and API gateways.
- Embed application security, PII handling, and data governance into the architecture.
- Perform technical scoping, estimate effort, and identify integration dependencies.
- Own applications through deployment and operational validation before handing off to engineering teams.
- Create documentation and architectural decision records for maintainability.
- Conduct user testing and iterate on solutions based on business partner feedback.
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