Role Description
We are looking for a high-performing AI Automation Engineer to join our CS Operations – GTM Automation & AI team. In this role, you will design, build, and continuously evolve the AI-driven applications and tools — chat assistants, workflow automations, and increasingly autonomous agents — that make our post-sales revenue-focused teams (Customer Success, Renewals, Technical Account Management, Managed Services) exponentially more effective and efficient.
You will partner closely with key stakeholders, end users, AI Integration, Data Engineering, and Enablement to turn ideas into high-impact AI capabilities.
This role is ideal for someone who is fiercely passionate about the pace of AI innovation, loves rolling up their sleeves, and is energized by rapidly evolving technologies and a fast-paced environment. You will be part of a fast-moving team that thrives on working with rapidly evolving technologies to deliver value to end-users and our customers.
This is an individual contributor role reporting to the leader of the GTM Systems & Automation pillar, which in addition to AI is responsible for the full CS tech stack.
Your day to day
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AI Chat Assistants & Conversational AI
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Evolve our role-based AI chat assistants — trained to answer questions and take actions tailored to specific personas (e.g., CSM, Renewals).
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Apply advanced prompt engineering techniques to construct the right level of context, ensuring accurate analysis and reliable output.
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Continuously test, monitor, and refine assistant performance based on usage data and user feedback.
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AI-Driven Workflow Automation
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Design and build AI-driven workflow automations using enterprise-grade orchestration platforms (e.g., Amazon Quick Automate, UnifyApps).
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Use AI to process data, apply evaluation and decision logic, generate outputs, and trigger downstream actions.
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Deploy scheduled and trigger-based workflows, and design human-in-the-loop checkpoints where judgment or approval is required.
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AI Architecture & Optimization
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Continuously optimize AI system performance — faster data retrieval and analysis, breaking workflows into modular AI agent building blocks, and determining what belongs in a natural-language prompt versus what should be engineered in code (e.g., Python).
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Assess which AI logic should live at which layer — what should be centralized versus decentralized across different vendors and clouds — and continuously evaluate the ensemble of AI tooling: LLMs (Anthropic, OpenAI, Amazon Bedrock, etc.) and orchestration platforms (Amazon Quick Automate, UnifyApps, open source, and others).
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Stay ahead of the rapidly evolving AI landscape and proactively recommend where new models, frameworks, or techniques should be adopted.
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AI Integration
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Partner closely with the AI Integration and Data teams to expand the AI “brain” — extending data access and connectivity via MCP (Model Context Protocol) and connecting to additional datasets in our data warehouse.
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Integrate and wire together our AI capabilities (chat, headless, workflow) with the broader CS tech stack, including Salesforce, Gainsight/Totango, Clari, Gong, Pendo, Snowflake/Redshift, AWS, and Power BI.
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Help determine what AI processing we build and own ourselves versus what we leverage from point-solution vendors (e.g., Salesforce, Gong, Totango).
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Agentic AI Applications
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Build our first truly agentic CS applications — AI that completes work with minimal to no human intervention — starting with our long-tail and smaller customer segments.
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Define the human-in-the-loop guardrails, evaluation logic, and monitoring needed to operate agentic systems reliably and safely at scale.
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Continuously identify new opportunities across the long-tail customer base where agentic AI can replace manual, repetitive work.
Qualifications
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Bachelor’s degree in Business, Computer Science, Engineering, or related field
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8+ years of professional experience, with at least 2+ years focused on AI technologies
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Proven experience building AI applications with demonstrated results
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Experience in GTM, ideally within post-sales functions such as Customer Success
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Strong command of advanced prompt engineering; understands how to construct context that drives accurate, reliable model output.
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Experience architecting multi-agent systems optimized for performance, reliability, and scale.
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Working knowledge of Python, with the ability to use AI to write code and to determine which components belong in a prompt versus in code.
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Hands-on experience with enterprise orchestration platforms (e.g., Amazon Quick Automate, UnifyApps, or similar), LLM platforms (Anthropic, OpenAI, Amazon Bedrock), and tools such as OpenAI Codex, Claude CoWork, etc.
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Familiarity with the broader CS tech stack — Salesforce, Gainsight/Totango, Clari, Gong, Pendo, Snowflake/Redshift, AWS, Power BI.
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Very comfortable operating with a high degree of ambiguity — moving fast, pivoting as needed, and working in a highly iterative motion.
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Genuine passion for AI innovation and a track record of staying current with new models, frameworks, and tools.
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Strong communication skills, with the ability to translate technical AI concepts for non-technical business stakeholders.
Benefits
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Competitive compensation
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Comprehensive benefits
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Career success on your terms
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Flexible work environment
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Annual wellness and community outreach days
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Always on recognition for your contributions
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Global collaboration and networking opportunities
