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Net2Source (N2S) · 3 hours ago

GEN AI Architect

Plano, TX

Contract

Hybrid

Senior Level

Net2Source (N2S) is seeking a GEN AI Architect to join their team. The role involves designing and maintaining LLM-powered workflows and building scalable automation systems while collaborating with various teams to ensure engineering standards are met.

B2BDeliveryHuman ResourcesInformation Technology

Growth Opportunities

H1B Sponsor Likely

Responsibilities

Design, develop, and maintain LLM-powered multi-agent workflows for code analysis, remediation proposals, and safe patch generation

Implement agentic patterns including planning/execution loops, dynamic tool orchestration, sandboxing, guardrails, and failure recovery

Build scalable automation systems for technical debt remediation: language/runtime upgrades, vulnerability patching, dependency modernization, and config drift correction

Partner with Dev Experience and Platform teams to define engineering guidelines and reusable standards across the organization

Architect and optimize Retrieval-Augmented Generation (RAG) pipelines, managing chunking, embeddings, hybrid search, reranking, and retrieval policies

Develop robust evaluation frameworks for LLMs, RAG, and agent workflows, including offline datasets, validation metrics, statistical testing, and A/B tests

Contribute to backend systems using Python, distributed systems, microservices, PostgreSQL, DBT, vector databases, caching, streaming, and queueing

Build CI/CD pipelines, observability dashboards, and perform performance analysis on model, retrieval, and network layers

Collaborate cross-functionally with product, platform, and security to move prototypes to production-grade services

Communicate clearly with stakeholders, write technical documentation, and mentor junior engineers

Qualification

Multi-agent architecturesRAG systemsAWS proficiencyLLM evaluationObservability toolsPostgreSQLAI tool adoptionTechnical documentationMentoringCommunication skills

Required

Deep knowledge of multi-agent architectures including planners, executors, and tool routing

Strong understanding of RAG systems: chunking, embeddings, vector/hybrid search, and retrieval policies

Experience evaluating LLMs and agent workflows incorporating statistical reasoning and validation

Proficiency with AWS (Lambda, ECS/EKS, S3, API Gateway, EC2, IAM) and Infrastructure-as-Code for cloud resource automation and deployment

Experience with observability tools (Datadog, logging, tracing, metrics)

Familiarity with PostgreSQL, DBT, data modeling, schema evolution, and performance tuning

Hands on experience on AI

AI Engineer who has extensive knowledge on LLM creation, AI tool adoption and also defining the frameworks

Should be strongly vocal enough to communicate with the customers