Software Engineer, AI Solutions

MNTN

5d•Remote

About The Position

At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2025.) We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social, helping brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/. We’re committed to innovation that empowers, not replaces. At MNTN, AI is a tool for growth, enhancing efficiency while keeping a people-first approach. Our goal is to streamline workflows and drive new solutions—without compromising the human element that makes our company great. So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may be the person we're looking for to join us in our next stage of growth. As a Software Engineer on the AI Efficiency team, you will bridge the gap between emerging AI capabilities and real-world business needs. You’ll design and build AI-powered tools and agents that automate workflows, support business teams, and unlock new opportunities for efficiency across the organization. Your work will directly influence how AI drives impact throughout MNTN.

Requirements

3+ years of software engineering experience, with at least 1 year focused on generative AI or LLM application development.
Experience with Model Context Protocol (MCP) — building MCP servers, integrating MCP clients, or connecting AI agents to external tools and data sources via MCP.
Hands-on experience building with LLM APIs (e.g., OpenAI, Anthropic, Gemini, open-source models), vector databases, and orchestration/agent frameworks (e.g., LangChain, LangGraph, CrewAI, LlamaIndex, ADK).
Experience designing or building AI agents — including tool-using agents, multi-agent systems, or agentic workflows.
Cloud-native development experience — comfortable deploying and operating services in AWS, GCP, or Azure using containers, serverless functions, or managed AI/ML services.
Strong communication skills — able to explain complex generative AI concepts to non-technical stakeholders and get engineers excited about new tools.
A product-minded approach: you think about user problems first, not just the technology.
Self-directed and comfortable operating with ambiguity in a fast-moving space.

Responsibilities

Design and build internal AI-powered tools and integrations — including generative AI applications and autonomous AI agents — that help business teams work smarter and faster.
Architect, develop, and maintain AI agents that automate complex multi-step workflows, make decisions, and interact with internal systems on behalf of users.
Evaluate, prototype, and recommend generative AI solutions (LLM APIs, agent frameworks, code generation tools) tailored to specific business problems.
Act as an AI evangelist within engineering — running workshops, writing internal guides, and mentoring teammates on generative AI development patterns and agent design.
Define and maintain best practices for prompt engineering, agent orchestration, model selection, responsible AI usage, and cost management.
Partner with product and business stakeholders to identify high-impact opportunities for generative AI and agent-driven automation.
Stay on the cutting edge of the generative AI and agentic AI landscape and translate new developments into actionable opportunities for the company.