AI Automation Engineer

Lookout Inc

1d•Remote

About The Position

Lookout, Inc. is the endpoint to cloud security company purpose-built for the intersection of enterprise and personal data. We safeguard data across devices, apps, networks and clouds through our unified, cloud-native security platform — a solution that's as fluid and flexible as the modern digital world. By giving organizations and individuals greater control over their data, we enable them to unleash its value and thrive. Lookout is trusted by enterprises of all sizes, government agencies and millions of consumers to protect sensitive data, enabling them to live, work and connect — freely and safely. To learn more about the Lookout Cloud Security Platform, visit www.lookout.com and follow Lookout on our blog, LinkedIn and Twitter. As part of Lookout's R&D organization, you will have a unique opportunity to spearhead the internal Agentic AI revolution. While our core engineering teams focus on product capabilities, you will be the primary architect responsible for operationalizing AI across the rest of the business. You will work directly with high-impact functions—Sales, Marketing, Finance, HR, Legal, and Recruiting—to design and build autonomous agents that fundamentally change how Lookout operates. To tackle these challenges, you must be part builder, part business analyst, and part evangelist. You need to be open-minded enough to experiment with emerging tools (like Gemini Enterprise and N8N) and persistent enough to solve complex integration puzzles across a diverse SaaS ecosystem. If you enjoy bridging the gap between cutting-edge LLM technology and real-world business strategy, and want to see your work immediately accelerate an entire organization, come check us out.

Requirements

Proven experience building AI Agents: Hands-on experience with orchestration tools (N8N, LangChain, Flowise, or similar) and direct usage of LLM APIs (Gemini, OpenAI, Anthropic).
Strong Scripting/Technical Skills: While this is a low-code friendly role, you must be proficient in Python or JavaScript to write custom logic, handle complex API authentication, and transform data payloads.
Business Systems Fluency: Demonstrated ability to quickly learn the data structures and logic of complex enterprise SaaS platforms (CRM, ERP, HRIS). You don’t need to be an expert in NetSuite today, but you must know how to read API documentation and figure it out fast.
Process Engineering Mindset: Experience mapping business workflows and spotting inefficiencies. You need the ability to say "No" to automating a bad process, and instead redesign it for an AI-first approach.
Resilience in Debugging: A high tolerance for the "trial and error" nature of agent development—debugging hallucinating models, fixing broken API connectors, and handling unstructured data.
Communication Skills: The ability to explain prompt engineering and context windows to a VP of Sales or a General Counsel in plain English.
3+ years of technical experience: Ideally a mix of software engineering, technical product management, or business systems analysis.

Nice To Haves

Experience specifically with Google Cloud Platform, Gemini and N8N workflow automation.
Familiarity with enterprise automation platforms
Background in cybersecurity or experience working within a security-conscious environment (handling PII/sensitive internal data).
Experience with Vector Databases and RAG (Retrieval-Augmented Generation) patterns for searching internal documentation.

Responsibilities

Design, Build and Maintain Agentic Workflows: Responsible for architecting and deploying autonomous AI agents using low-code/no-code orchestration platforms (e.g., N8N) and enterprise LLMs (e.g., Gemini Enterprise).
Translate Business Needs to AI Logic: Act as the bridge between non-technical stakeholders and AI capabilities. You will dissect requests from departments like Finance or Legal, understand the "why," and re-engineer their processes to be compatible with how LLMs and agents actually work.
Systems Integration & Orchestration: Figure out how to make the AI "talk" to our business stack. You will handle the trial-and-error work of integrating agents with Salesforce, NetSuite, Workday, Marketo, Vena, and other enterprise platforms via APIs and webhooks.
Data Strategy for Agents: Determine how to extract, clean, and contextually feed data from siloed systems into AI models to ensure accurate, hallucination-free outputs.
Influence Internal AI Strategy: Move beyond simple "chatbots" by identifying high-value use cases for multi-step agentic automation that stakeholders haven't even thought of yet.
Governance & Maintenance: Own the lifecycle of internal agents, ensuring they remain secure, cost-effective, and functional as underlying APIs and business rules evolve.

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