Gen AI Architect
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Job Title: Gen AI Architect
Location: Fremont CA (Onsite)
Job Type: C2C
Remote: No
Job Summary
We are seeking an experienced Senior Technical Lead / Gen AI Architect with strong expertise in Langfuse v3 Azure AI services and GenAI lifecycle management. The role will involve architecting implementing and optimizing advanced GenAI evaluation frameworks ensuring enterprise-grade reliability scalability and observability for AI-driven solutions.
Key Responsibilities
- Provide technical leadership to development teams ensuring best practices coding standards and performance optimization in complex GenAI projects.
- Architect and deploy Langfuse v3 in production environments including upgrades from Langfuse v2 with backward compatibility.
- Design and build modular components for prompt management tracing metrics evaluation and playground features using Langfuse v3.
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Leverage Langfuse capabilities for:
- Prompt Management versioning templating optimization
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Tracing end-to-end visibility of GenAI workflows
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Metrics performance latency and usage analytics
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Evaluation automated/manual scoring of outputs
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Playground interactive prompt testing/debugging
- Integrate Azure AI Evaluation SDK into enterprise pipelines for scalable evaluation of GenAI models.
- Build reusable components and templates for evaluation across diverse RAG multi-agent and GenAI lifecycle workflows.
- Ensure scalability observability and traceability of evaluation frameworks in both offline and online environments.
- Collaborate with cross-functional teams (product data science and engineering) to align evaluation metrics with business KPIs.
- Conduct feasibility studies recommend technical alternatives and ensure compliance with architecture best practices.
- Stay current with emerging GenAI evaluation tools and methodologies (e.g. TruLens W&B Helicone).
Required Skills & Qualifications
- Hands-on expertise in Langfuse (including v3 features) and integrations.
- Proficiency with Azure AI Services and Azure AI Evaluation SDK.
- Strong understanding of LLMOps prompt engineering and GenAI lifecycle management.
- Experience with Retrieval-Augmented Generation (RAG) fine-tuning and multi-agent orchestration.
- Proficiency in Python (TypeScript or other GenAI-related languages is a plus).
- Experience with cloud-native architectures (Azure preferred).
- Familiarity with observability tools tracing frameworks and evaluation metrics for GenAI systems.
- Excellent communication documentation and stakeholder collaboration skills.
Nice to Have
- Experience with additional observability tools such as TruLens Weights & Biases (W&B) Helicone.
- Exposure to evaluation standards for enterprise AI adoption.
- Knowledge of multi-cloud and hybrid deployment strategies.
Key Skills
- APIs
- Pegasystems
- Spring
- SOAP
- .NET
- Hybris
- Solution Architecture
- Service-Oriented Architecture
- Adobe Experience Manager
- J2EE
- Java
- Oracle
