Lead AI Engineer - RAG & Enterprise AI Architect

Namely

Mountain View (CA)

On-site

USD 19,000 - 35,000

Full time

5 days ago
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Job summary

Namely is seeking a Lead AI Engineer in Hyderabad to architect, develop, and scale enterprise AI infrastructure. You will lead design for RAG frameworks, LLM gateways, and agentic workflows, ensuring robust data pipelines integrated with AWS cloud.

Responsibilities include guiding system design, enforcing JSON-based validation, and mentoring teams while advancing scalable, enterprise-grade AI platforms.

Qualifications

  • 5-8 years of professional software engineering experience.
  • Deep, hands-on expertise in Java and Spring/Spring Boot; Python for AI/ML integrations.
  • Strong knowledge of relational databases (PostgreSQL/MySQL) and MongoDB.
  • Extensive knowledge of object-oriented design and enterprise integration patterns.
  • Hands-on experience with AWS and containerized applications.

Responsibilities

  • Design, deploy, and optimize RAG frameworks and centralized LLM gateways.
  • Lead architectural oversight for content ingestion and enrichment pipelines.
  • Build and orchestrate multi-agent workflows for enterprise AI integrations.
  • Implement Model Context Protocol to standardize interactions with foundation models.
  • Architect highly reliable LLM generation pipelines with strict JSON outputs for schema validation.
  • Provide technical leadership across cloud deployments and infrastructure planning.

Skills

Java & Spring Boot
Python
AWS cloud services
RAG
LLM orchestration
JSON-based data validation
PostgreSQL
MySQL
MongoDB
Distributed systems

Tools

Docker
Kubernetes
AWS

Job description

Namely is seeking a Lead AI Engineer in Hyderabad to architect, develop, and scale enterprise AI infrastructure. You will lead design for RAG frameworks, LLM gateways, and agentic workflows, ensuring robust data pipelines integrated with AWS cloud.

Responsibilities include guiding system design, enforcing JSON-based validation, and mentoring teams while advancing scalable, enterprise-grade AI platforms.

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