AI Expert/Architect | Remote | 6+ Months

Genius Business Solutions

• $150K — $180K *
US-AnywhereRemote in United States
Enterprise Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • 15+ years of experience in large-scale distributed systems or enterprise applications.
  • Proven track record in deploying AI/LLM-powered applications including intelligent automation.
  • Expertise in Generative AI technologies such as LLMs, Prompt Engineering, and AI orchestration.
  • Hands-on experience with agent frameworks like LangChain and LangGraph.
  • Strong frontend and backend integration skills for AI solutions.
  • Solid software engineering fundamentals with focus on system design and code quality.
  • Experience leading technical teams and mentoring engineers.

Responsibilities

  • Architect and develop enterprise-grade Generative AI applications using LLMs and automation.
  • Design multi-step reasoning workflows with control over state and memory management.
  • Build robust orchestration for long-running AI workflows using platforms like Temporal.
  • Create reference architectures for model routing and observability in production environments.
  • Establish evaluation frameworks for assessing LLMs and agent performance against business outcomes.
  • Oversee full cycle of feature development from design to production rollout and maintenance.
  • Write and review clean, high-performance code while promoting best practices in AI tooling.

Benefits

  • Opportunity to lead innovative projects in Generative AI.
  • Mentorship and professional development for career growth.
  • Work in a dynamic environment with cutting-edge technology.
  • Culture of continuous learning and technical excellence.
Full Job Description
Job Summary

We are seeking a highly experienced AI Engineering Leader to architect and deliver enterprise-grade Generative AI applications. This role requires deep expertise in LLMs, agentic workflows, and orchestration frameworks, combined with strong software engineering fundamentals and leadership skills. The ideal candidate will drive the design of intelligent automation systems, establish best practices for AI observability and evaluation, and mentor engineering teams to achieve technical excellence. With over 15 years of experience in building large-scale distributed systems, the candidate will own end-to-end feature development, from architecture and implementation to production rollout, ensuring scalable, fault-tolerant, and business-impactful AI solutions.

Key Responsibilities
• Architect and build enterprise-grade Generative AI applications combining LLMs, retrieval, structured data, orchestration, and workflow automation.
• Design agentic systems and multi-step reasoning workflows using LangGraph or equivalent - with clear control over state, memory, tool invocation, and human-in-the-loop checkpoints.
• Build fault-tolerant orchestration for long-running AI workflows using Temporal or similar platforms.
• Drive reference architectures for model routing, prompt versioning, observability, experimentation, and safe production rollout.
• Establish LLM/agent evaluation frameworks - offline evals, regression suites, trace diagnostics, and quality metrics tied to business outcomes.
• Own full feature development across design, implementation, testing, shipping, and servicing.
• Write and review clean, high-quality code with a focus on performance, scalability, and maintainability.
• Set best practices for AI tooling, service observability, alerting, and incident response.
• Mentor engineers across the team and foster a culture of technical excellence and continuous learning.
• Use AI tools in your daily workflow and advocate evolving best practices to the broader team.
Required Qualifications
• 15+ years of experience building large-scale distributed systems, platforms, or enterprise applications.
• Proven track record shipping production AI/LLM-powered applications - agentic workflows, RAG systems, or intelligent automation.
• Deep expertise in Generative AI: LLMs (OpenAI), Prompt Engineering, RAG, vector search, and AI agent orchestration.
• Hands-on experience with agent frameworks: LangChain, LangGraph, AutoGen, or equivalent.
• Frontend and backend background to integrate AI solutions end-to-end into existing applications.
• Strong software engineering fundamentals: system design, algorithms, testing, debugging, and code review.
• Demonstrated ability to lead technical direction and mentor engineers.
• Comfort in ambiguous, fast-moving problem spaces where best practices are still emerging.
• BS, MS, or PhD in Computer Science, Engineering, or equivalent practical experience.

Top Skills Required:
1. UI Architect (ReactJS)
2. Agentic AI (Lang graph , Lang chain)
3. NodeJS

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