benlm

Hiring for a full-time, 100% remote role (entire company is remote) for a Staff Software Engineer, working on the ShiftUp platform stack (Python, Pydantic AI, GCP, Temporal Workflows, Turbopuffer, Postgres). You will be one of the first five engineering hires, and you will have the ability to grow and shape your own role.

We need someone with solid experience designing and implementing systems with many moving parts, who can easily shift between systems design, writing and reviewing code (or, let's face it, supervising Codex/Cursor/Claude Code), working with the team to design features, and talking to customers to gain feedback and insights.

You'll be working to build all kinds of agents, workflows, and other components to support our features. Our research agents are truly deep, sometimes spending upwards of an hour searching and analyzing information for a single prospect or strategy. Our RAG pipeline is focused on quality, leveraging LLM chunking, metadata and graph generation, and contextual embeddings.

If this sounds like fun, let's chat: you won't be asked to regurgitate leetcode solutions, we'll simply have a conversation and see if there's a mutual fit. Our interview process is lightweight, respectful and moves fast. Competitive salary, equity and full benefits.

You can email me directly: ben@shiftupai.com

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About the company: ShiftUp is a new kind of intelligence-driven sales platform that identifies emerging demand and drives revenue. Built from scratch to leverage LLM-driven agentic workflows, ShiftUp deeply researches prospects, identifies the highest-value opportunities, and provides targeted sales strategies to execute on them.

ShiftUp is delivered as a native app on Salesforce AppExchange, providing our platform to sellers where they already are. Our Salesforce app talks to a cloud-native stack that uses Python services, durable workflows, and SQL + vector databases.

We're well-funded, having recently closed a $3M seed round. We're building out a small team of highly talented, well-rounded engineers to deliver on our vision. Our company is 100% remote, and we use SoWork to help build our culture. As a small startup, everyone is highly motivated and focused on moving quickly, but we also place importance on a sustainable work-life balance so that you can continue to do your best work.

We built it in Kotlin with Ktor server, htmx and tailwind. It uses a mixture of models, including gpt4-turbo, gpt4-vision and gemini-pro-vision. It's deployed using Kamal on bare metal.

Example canvas that provides a roundup of Apple Vision Pro reviews: https://jumprun.ai/share/canvas/01HNXB2K3GM7KPRP45Y2CVVJSC

Our learn more page with some screenshots to show creating a canvas: https://jumprun.ai/learn-more

It's a free closed beta at the moment to control costs, but let me know if you'd like an invite.

The source material doesn't need to provide a comparative analysis itself: as long as it finds data detailing Vision Pro specs (which it already found) and Oculus specs it'll be able to do the analysis.

Canvases also have memory and auto-refresh, so once it finds the specs it can remember them across refreshes/updates, but also incorporate any new information it finds.

We support rich components like tables, timeseries, charts and maps. We're working on automations at the moment so that you can provide natural language conditions that trigger actions (like sending you an email or changing updating a page in Notion).

Our long-term vision is that canvases become more interactive and interconnected, so that you end up building mini applications without it feeling like you're using a low-code app builder.

"Homelessness then, in Australia, is more than lacking a roof over your head, it is also the absence of those features associated with “home”: permanence, security, and the freedom to come and go."

"If the world were to accept Australia’s definition and include everyone with inadequate shelter, the number would exceed 1.6 billion – roughly 20 percent of the population. Also excluded from official figures are the world’s 65 million displaced refugees in temporary accommodation."

Place for all scientific studies to be elucidated with plain english explanations, analysis, information on shortcomings, links to related studies, open questions, links to further information. Would be community created content, but needs some sort of community voting/moderation system to surface the best content and empower the most knowledgable/trusted contributors.

Ideally this would be where you go when you see sensationalist headlines in popular science magazines -- here you can find out what the study actually means.

Anything like this out there?

Congrats on the 13 jumps! Where do you jump at?