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Principal AI Engineer

Trinite Consulting Group LLCSanta Clara, CA🇺🇸United StatesPosted 16 Jul 2026

Why This Role Stands Out

You will lead the design and development of cutting-edge AI-powered enterprise applications, leveraging LLMs, RAG, and multi-agent systems to drive innovation. This hybrid role offers immense growth potential for experienced AI engineers who thrive on building secure, scalable, and production-ready AI architectures within a collaborative environment. Embrace this opportunity to shape the future of AI solutions and advance your career at Trinite Consulting Group LLC.

Quick Overview

Work Type
Hybrid
Level
Leader

Job Description

AI-First Core IT Software Engineer (Software, ML & Data)

  1. Design and develop AI-powered enterprise applications using LLMs, RAG, Multi-Agent Systems, and AI workflows.
  2. Collaborate with business and product teams to translate business requirements into scalable technical solutions.
  3. Build secure, scalable, and production-ready AI architectures for Marketing, Sales, and Lead-to-Cash platforms.
  4. Develop AI gateways and unified APIs to support multiple LLM providers (OpenAI, Llama, Anthropic, etc.).
  5. Design and implement Agentic AI solutions using frameworks such as LangChain and LangGraph.
  6. Build enterprise-grade applications using Python and at least one additional language (Java, Go, or Node.js).
  7. Develop cloud-native microservices and distributed systems on AWS, Azure, or Google Cloud Platform.
  8. Implement AI observability, model evaluation, prompt tracing, and cost/performance optimization.
  9. Ensure AI security through guardrails, prompt injection protection, PII filtering, and governance best practices.
  10. Drive end-to-end delivery from solution architecture and development to deployment and production support.
  11. Mentor engineering teams and communicate technical solutions effectively with business stakeholders.
  12. Follow modern software engineering practices, including API design, CI/CD, Agile/Scrum, and DevOps.
  13. Required experience: 8+ years in software engineering with hands-on experience in enterprise AI application development.
  14. Bachelor''s degree in Computer Science or a related field (or equivalent experience).
  15. Preferred experience includes Quote-to-Cash (Q2C), Revenue Operations, AI evaluation tools (LangSmith, Arize, HoneyHive), and enterprise GTM systems.

Skills

Microservices
Node.js
AWS
Scrum
Agile
Azure
Google Cloud
Java
LLM
Python

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