AI Architect | Generative AI

Jero Technologies; Indore District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Jero Technologies seeks a senior AI architecture engineer to design end-to-end AI systems, including LLMs, RAG, and multi-agent orchestration. You will build AI asset discovery connectors for models, data, and endpoints, and implement guardrails for data privacy and content moderation.

You will lead cross-functional teams across AI/ML, backend, and data engineering, defining evaluation, observability, and cost standards while ensuring scalable, secure deployments aligned with governance

Qualifications

• Strong programming experience in Python and/or Java.
• Hands-on expertise in GenAI, LLMs, RAG, vector databases, and prompt engineering.
• Experience with LangChain, LangGraph, Semantic Kernel, and familiarity with MCP.
• Experience with AWS Bedrock, SageMaker, Azure OpenAI, or Azure AI Foundry.
• Strong knowledge of APIs, microservices, event-driven architecture, RBAC, SSO, and audit logging.
• Familiarity with LangSmith, Langfuse, Ragas, or Arize.

Responsibilities

• Design AI architecture, including LLMs, RAG, multi-agent orchestration, embeddings, and model routing.
• Architect AI asset discovery connectors for models, datasets, agents, prompts, and endpoints.
• Implement AI guardrails for PII detection, prompt injection, jailbreaks, and content moderation.
• Lead architecture reviews and guide AI/ML, backend, and data engineering teams.
• Define LLM evaluation, observability, performance, latency, and cost optimization standards.
• Ensure enterprise security, scalability, and alignment with AI governance frameworks.

Skills

Python

Java

GenAI

LLMs

RAG

Prompt engineering

LangChain

LangGraph

Semantic Kernel

APIs

RBAC

SSO

Audit logging

Tools

AWS Bedrock

SageMaker

Azure OpenAI

Azure AI Foundry

LangSmith

Langfuse

Arize

Job description

Key Responsibilities

• Design AI architecture, including LLMs, RAG, multi-agent orchestration, embeddings, and model routing.
• Architect AI asset discovery connectors for models, datasets, agents, prompts, and endpoints.
• Implement AI guardrails for PII detection, prompt injection, jailbreaks, and content moderation.
• Lead architecture reviews and guide AI/ML, backend, and data engineering teams.
• Define LLM evaluation, observability, performance, latency, and cost optimization standards.
• Ensure enterprise security, scalability, and alignment with AI governance frameworks.

Required Skills

• Strong programming experience in Python and/or Java.
• Hands-on expertise in GenAI, LLMs, RAG, vector databases, and prompt engineering.
• Experience with LangChain, LangGraph, Semantic Kernel, and familiarity with MCP.
• Experience with AWS Bedrock, SageMaker, Azure OpenAI, or Azure AI Foundry.
• Strong knowledge of APIs, microservices, event-driven architecture, RBAC, SSO, and audit logging.
• Familiarity with LangSmith, Langfuse, Ragas, or Arize.