Software Engineer – AI Automation (Internal Tools)

Voyager Technologies•Los Angeles, WA

19h•$100,000 - $160,000

About The Position

Voyager is seeking Software Engineers – AI Automation (Internal Tools) to join its Internal Tools Team. This role involves designing and building AI-driven automations, bots, and internal applications to streamline business operations across various departments like finance, HR, supply chain, and manufacturing. The engineer will collaborate with the Internal AI Tools Lead and business stakeholders to identify pain points and develop practical systems, including integrations, services, and LLM/agent-based tools. This position is well-suited for early-career engineers, including new graduates, who are passionate about building, enjoy user interaction, and are eager to utilize AI in their engineering work. The Internal AI Tools Team focuses on creating AI-powered systems to enhance Voyager's internal operations, transforming manual workflows into efficient, integrated systems. The team collaborates across departments such as Finance & Accounting, Internal Communications, Performance Management, Human Resources, IT & Infrastructure, Cyber Security & Systems Assurance, Mergers & Acquisitions, R&D and Technology Roadmapping, Strategic Planning, Enterprise Risk Management, Quality Assurance, Supply Chain & Procurement, Manufacturing & Assembly, and Sales / New Business Capture. The ultimate goal is to significantly boost the effectiveness of every Voyager team by replacing manual, spreadsheet- and email-driven processes with secure, AI-driven workflows, decision-support tools, and intelligent assistants that reduce cycle times and improve execution quality.

Requirements

0–3 years of professional software engineering experience (internships, research, or substantial personal projects all count; exceptional new graduates are encouraged to apply).
Proficiency in at least one general-purpose programming language such as Python, TypeScript/JavaScript, or similar.
Experience building scripts, APIs, small web apps, or workflow automations—whether in a professional setting, research lab, or serious side projects.
Familiarity with RESTful APIs, webhooks, and basic data modeling using SQL or modern data stores.
Hands-on experience using LLMs or automation platforms (e.g., OpenAI tools, LangChain, Zapier, n8n, or similar) to automate or accelerate real tasks.
Strong ownership mindset and willingness to talk directly with non-technical users to understand problems and ship solutions quickly.

Nice To Haves

Bachelor’s degree in Computer Science, Software Engineering, or a related STEM field; or equivalent experience.
Experience with one or more of: internal tools development, low-code/no-code automation, or back-office systems (ERP, CRM, HRIS, ticketing, finance tools).
Exposure to enterprise or security-conscious environments (e.g., defense, aerospace, healthcare, finance) where data protection and auditability are important.
Portfolio or examples of personal projects—automations, bots, dashboards, or tools you built to make your own life or your team’s work easier.
Interest in business operations and process improvement, not just writing code in isolation.
Passion for writing and shipping code rapidly that has a measurable impact on business efficiency.

Responsibilities

Build and maintain AI-powered automations and workflows that streamline recurring business processes (e.g., report generation, approval flows, policy Q&A, data reconciliation).
Implement internal tools and microservices that integrate with systems across Finance & Accounting, HR, IT, Cyber Security, Supply Chain, Manufacturing, and Sales / New Business Capture.
Develop and maintain Slack/Teams bots, web frontends, and small internal apps that serve as “copilots” for business users.
Use LLMs and agent frameworks to design task-specific assistants—such as a contract summarization agent, a supplier risk analysis agent, or an internal policy advisor bot.
Work with the Internal AI Tools Lead and business stakeholders to map manual workflows into clear technical requirements and automation designs.
Leverage agentic to rapidly write clean, tested code and contribute to shared libraries, templates, and best practices for internal automations.
Monitor and debug automations in production; improve reliability and performance based on real-world usage and feedback.