GenAI Lead Architect for Enterprise AI

Synechron; New York (NY); Híbrido; USD 110.000 - 125.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Global opportunities

Paid time off

Health insurance

Education benefits

Udemy for Business

Descripción de la vacante

Synechron seeks an experienced Generative AI Lead to architect and deliver enterprise-scale GenAI solutions. You will guide AI strategy, define architecture standards, and mentor teams across AI/ML domains, collaborating with stakeholders to translate requirements into scalable products using LLMs, RAG, and cloud-native tech.

You will champion responsible AI, security, and governance while steering projects on AWS/Azure/GCP, LangChain ecosystems, and vector databases, ensuring performance and

Formación

• 8+ years of software engineering experience with 3+ years in Generative AI.
• Strong hands-on experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs (Llama, Mistral).
• Expertise in Python and AI frameworks.

Responsabilidades

• Lead the design and implementation of GenAI solutions using Large Language Models (LLMs).
• Define AI strategy, architecture, governance, and best practices across the organization.
• Build and deploy AI applications leveraging RAG, Vector Databases, and AI Agents.

Conocimientos

Python

AI frameworks

LLMs / GenAI

OpenAI / Azure OpenAI / Claude / Gemin

Prompt engineering

RAG architecture

Vector databases

Multi-Agent Systems

Cloud platforms

MLOps / CI/CD for AI deployments

Herramientas

LangChain

LangGraph

CrewAI

AutoGen

Descripción del empleo

Synechron seeks an experienced Generative AI Lead to architect and deliver enterprise-scale GenAI solutions. You will guide AI strategy, define architecture standards, and mentor teams across AI/ML domains, collaborating with stakeholders to translate requirements into scalable products using LLMs, RAG, and cloud-native tech.

You will champion responsible AI, security, and governance while steering projects on AWS/Azure/GCP, LangChain ecosystems, and vector databases, ensuring performance and