Generative AI Engineer

Generative AI Engineer - Nextiva

Redefine the future of customer experiences. One conversation at a time.

We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans.

Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication.

If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place.

Build Amazing - Deliver Amazing - Live Amazing - Be Amazing

We’re looking for a highly skilled and hands-on RAG (Retrieval-Augmented Generation) & Prompt Engineer to join our applied AI team. You’ll work with cutting-edge open-source and proprietary LLMs (like LLaMA, Mistral, Claude, GPT-4o, etc.) to build, prompt, and orchestrate intelligent agents that are capable, reliable, and production-ready.

This role is perfect for someone who has experience developing prompt chains, implementing tool-calling workflows, and debugging AI agents at scale.

Key Responsibilities

Design, develop, and iterate on prompt strategies tailored to downloadable models and major APIs (LLaMA, Mistral, Claude, GPT-4o, etc.).

Architect and implement RAG pipelines with a deep understanding of embedding models, retrievers, and context optimization techniques.

Create prompt chains and tool-calling workflows for dynamic agent behavior using Responses API and similar frameworks.

Design, test, and deploy foolproof agent architectures using OpenAI tool calling and agent protocol layers.

Write robust Guardrails and control flows for agents to prevent unintended behaviors and ensure task compliance.

Debug and maintain agent codebases, ensuring reliability and scalability of deployed services.

Apply basic knowledge of OpenAI Operator and related orchestration tools to manage agent lifecycle.

Collaborate with researchers and infra teams to optimize prompt efficiency and latency.

Must-Have Qualifications

3 - 5 years of experience in AI engineering, prompt engineering, or applied ML roles.

Proven experience working with both downloadable open-source models and hosted APIs.

Strong knowledge of LLM prompt design patterns, prompt chaining, and failure handling.

Ability to build agent systems that are secure, auditable, and self-healing.

Good coding and debugging skills in Python (or relevant stack) with focus on AI orchestration.

Familiarity with agent deployment pipelines, containerized environments, and CI/CD flows.

Tech Stack We Use

Python, FastAPI, LangChain / LlamaIndex.

OpenAI, Anthropic, HuggingFace.

Vector DBs (Weaviate, Pinecone, Qdrant).

Responses API, OpenAI Operator, A2A SDK.

Docker, GitHub Actions, GCP/AWS.

Bonus (Nice-to-Have Skills)

Experience building agents from scratch, especially with agent transfer logic and persistent memory.

Understanding of Model Context Protocols and how to integrate them into multi-agent LLM stacks.

Familiarity with A2A SDK for agent-to-agent communication and delegation.

Hands-on experience with LoRA / QLoRA techniques for fine-tuning GPT-style models on downstream or domain-specific tasks.

Experience with vector DBs, context compression, or multi-turn reasoning at scale.

#LI-SC1 #LI-Hybrid

Last updated: 18 hours ago