GenAI Solutions Engineer

Overview

Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
No Travel Required
Able to Provide Sponsorship

Skills

GenAI
System Integration
RAG Architectures

Job Details

GenAI Solutions Engineer

Location: Remote/ Candidate should be in Pacific Timezone

JD:

Skills: Full-Stack Development, API Design, System Integration, RAG Architectures, Agent Orchestration, Chain-of-Thought Reasoning, AI UX Design, Rapid Prototyping

Translating AI capabilities into business value requires a technically versatile engineer who can bridge the gap between complex AI models and practical applications. This implementation-oriented full-stack role combines software engineering expertise with specialized knowledge of how to efficiently leverage data sources, LLMs, and AI agents in production environments to deliver tangible business value.

  • Accelerates user adoptionthrough intuitive interfaces and seamless system integrations
  • Creates efficient data pipelinesconnecting LLMs to relevant utility information sources
  • Enables intelligent automationthrough multi-agent systems for complex workflows
  • Develops sustainable solutionsthat can evolve with business needs and technology advances

Key Responsibilities:

  • Build proof-of-concept applications and production-ready interfaces for GenAI capabilities
  • Connect AI services with enterprise systems (SAP, internal databases) for data exchange
  • Design and implement multi-agent architectures to solve complex business processes
  • Develop tool integration frameworks allowing AI to interact with utility systems
  • Create robust memory and reasoning systems for contextual, multi-step AI interactions
  • Implement appropriate guardrails and safety measures for AI agent systems
  • Gather requirements and translate business needs into technical implementation
  • Produce documentation and knowledge transfer materials for sustainable solutions

Expected Skillset:

  • Full-Stack Development: Modern front-end frameworks, back-end technologies, API design
  • System Integration: Experience connecting disparate systems, data orchestration, authentication
  • AI Application Patterns: RAG architectures, prompt engineering, agent orchestration frameworks
  • Agent Architecture: Knowledge of multi-agent systems, collaboration protocols, tool integration
  • Reasoning & Memory: Understanding of chain-of-thought reasoning, context management, planning algorithms
  • User Experience: Ability to design intuitive AI interfaces with appropriate feedback mechanisms
  • Rapid Prototyping: Demonstrated ability to quickly build working demos and iterate based on feedback

Thanks,

Vinutha

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