AI Engineer

About Viral Pitch

Viral Pitch is an AI-driven influencer marketing SaaS platform that assists brands and agencies in discovering influencers, automating campaign workflows, managing content, contracts, and payments, along with measuring campaign performance efficiently at scale.

Role Overview

We are searching for a proactive AI Engineer to construct and evolve the AI intelligence layer within our platform. This role involves hands-on involvement in taking AI projects from the experimental phase to robust, production-grade solutions.

Key Responsibilities

• Architect, develop, and deploy AI and machine learning features throughout the Viral Pitch platform.
• Create AI agents and orchestrate workflows for influencer identification, matching, outreach, negotiations, content analysis, campaign strategy formulation, and reporting.
• Utilize Large Language Models (LLMs), multimodal models, embeddings, Retrieval-Augmented Generation (RAG), vector databases, and various AI APIs.
• Construct dependable AI data pipelines processing text, images, videos, social media inputs, and campaign-related data.
• Design prompt engineering techniques, generate structured outputs, implement tool calling, and build agent-like workflows.
• Integrate AI models from providers including OpenAI, Google Gemini, Anthropic, and other emerging AI platforms.
• Assess and select AI models balancing quality, latency, and cost for production deployment.
• Develop scalable AI systems that maintain high levels of accuracy, consistency, and reliability.
• Create frameworks for evaluating and monitoring AI outputs and perform model fine-tuning or adaptation as necessary.
• Collaborate closely with Product and Engineering teams to translate business needs into effective AI solutions. Rapidly prototype and transition successful new AI capabilities to production.
• Keep up-to-date with the latest advancements in Generative AI, AI Agents, multimodal AI, and LLM infrastructure.

Candidate Profile

• A minimum of 2 years and up to 6 years' experience in AI/ML engineering, Generative AI, or a related domain.
• Proven hands-on expertise in developing applications using LLMs and Generative AI APIs.
• Solid understanding of embeddings, vector search technologies, Retrieval-Augmented Generation (RAG), and prompt engineering.
• Experience in delivering AI solutions into production environments, beyond experimental notebooks or prototypes.
• Strong grasp of API usage, databases, and backend engineering systems.
• Competence in systematically evaluating AI outputs and enhancing model performance.
• Excellent problem-solving capabilities coupled with a readiness to experiment quickly and iteratively.
• Ability to independently manage tasks from initial concept through prototyping to full production deployment.