Senior Software Engineer, Conversation Infrastructure at Moveworks (Peninsula)

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Does this sound like an interesting challenge to you - scaling and optimizing a best-in-class conversational AI product to provide instant help to all enterprise users? Do you wonder how to apply abstraction, scalability, and optimization, to a dynamic, probabilistic, and ML-driven conversational product?

If so, join us at the Conversation Engine team, where you have the opportunity to work on the heart of the Moveworks AI product, to make it scalable and optimized for the ever growing enterprise solution space. Check out our recent blog postings (part1, part2) on Moveworks’s groundbreaking solutions for enterprise AI. 

As the pioneer for enterprise AI products, there’s no established formula for building out the next solution. You will be working closely with ML experts and cross-functional teams, iterating fast over innovative ideas, and making informed decisions empowered by timely user behavior data. You are challenged to scale and optimize the conversation engine to support hundreds of millions of users, omni chat channels, a large variety of ML models, and a rich set of enterprise skills, with the highest engineering quality and robustness.

Who we are:

Moveworks is revolutionizing how companies support their employees — with the first AI platform that makes getting help at work effortless. Using advanced conversational AI built for the enterprise, Moveworks gives employees exactly what they need, from IT support to HR help to policy information. Our platform allows customers like DocuSign, Twitter, Snowflake, Instacart, Coca Cola, and Hearst to move forward on what matters.

Founded in 2016, Moveworks has raised $315 million in funding, at a valuation of $2.1 billion. We’ve been named to the Forbes AI 50 list for three consecutive years, while earning recognition as the Best Chatbot Solution at the 2021 AI Breakthrough Awards. Above all, we’ve built an AI company that puts people first, which is why Built In named Moveworks the #1 Best Place to Work in the Bay Area.

What you’ll do:

  • Design clean API abstractions for the conversation platform, which supports all popular chat clients (for example, MSTeams and Slack) and offers a neutral chat client interface to other parts of the system.
  • Optimize the dialog engine to support all conversational features, private domain knowledge of each enterprise customer in the cloud, and multilingual translation on the fly, with the least memory footprint, the lowest latency, and the most efficient development process for application engineers.
  • Educate and mentor fellow engineers on best practices for coding pattern, API design, scalability, robustness, and optimization.
  • Provide deep insight and visibility into the performance of the Moveworks conversational API product, with comprehensive logging and tracing framework, easy to use debugging and triaging tools, and automatic metrics.
  • Collaborate closely with ML engineers, application engineers, and cross functional teams, on new features and productivity and quality initiatives.
What you bring to the table:

Strong foundation in CS and software engineering and expertise in building scalable systems.

  • Deep understanding of clean, modular and scalable API design. Ability to promote best coding practices and influence other engineers on code quality and craftsmanship.
  • Passionate about optimization of the systems. Experienced in tracing, logging and metrics frameworks. Systematic approach to quickly diagnose and fix latency bottlenecks, race conditions, and throughput limitations.
  • Independent in research for new requirements and solutions. Fast iterations in coding and execution.
  • Effective communicator for articulating rationales and design approaches, cross functional awareness, and mentoring others.
  • BS or higher degree in computer science or a related field, or equivalent relevant experience 
  • 3+ years of professional development experience building systems at scale
Nice to have:
  • Experience with scaling ML systems
  • Experience with defining metrics to measure conversational AI product

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