software engineers

We’re a small, seed-stage company that just opened an office in San Francisco. We’re looking to hire two Product Engineers to collaborate closely with each other and with the AI agents and coworkers that will support them.

This is a technical role for software engineers excited to use the leverage that AI allows in producing code to allow focus on higher order technical architecture, product requirements, and user needs. Your job as Product Engineer is to see around the corners in the market, our product, and its technical implementation. You should have immense software wisdom, the kind not yet encoded in the weights of an LLM. You communicate well, exercise ownership over your responsibilities and your decisions, and move fast in the most competitive market that has ever existed.

Your job is not to sit in isolation, as an artisan meticulously crafting lines of code to satisfy a JIRA ticket. It’s to have impact through software creation, participating in engineering, technical, and architecture implementation and review, while working closely with your human and AI coworkers to ship software products that satisfy real user needs.

We are looking for generalist polymaths who have seen the failings of traditional technologies, ways of working, and organizational bureaucracy.

On a given day or week, you might:

• Prototype a new multimodal agent interaction
• Review a pile of PRs that your coworkers, both human and AI, have produced, checking for gotchas, product direction, alignment, and architectural concerns. You don’t trust AI code outright. You internalize it, think about it, and understand its implications and tradeoffs.
• Develop a new synthetic data generation mechanism to support evals of Kinelo’s memory and inference system
• Debate whether visual UI is even needed in software anymore
• Diagnose scaling problems with a Kinelo data ingestion system
• Prepare a presentation for a conference where you’ll discuss Kinelo’s temporal inference system and its benchmarks

We’re looking for candidates who are:

• Aware of the current state of the art in agentic coding and the principles and techniques that underlie it, as well as where the problems and opportunities lie
• Experienced and can tell battle stories of failings in system design and software architecture, so that they can keep an eye out and prevent such problems in the future
• All about getting the job done, wearing many hats and abandoning convention where necessary
• Extraordinarily comfortable with ambiguity and uncertainty. We are an early-stage startup still navigating product-market fit. It’s your job to have input and embrace that uncertainty as opportunity.

• At least six years in a professional software development capacity
• Knowledge of several programming languages, including at least one that is statically typed
• Knowledge of fundamental computer science principles
• Experience with databases, data ingestion, containerization, and other basics of scalable and reliable software
• Our tech stack currently includes TypeScript running in a managed container service backed by Postgres, Redis, and some other systems. But we’re adaptive and flexible, and you should be too.

Kinelo is for you if:

• You maintain high standards while being collaborative and compassionate
• You enjoy tackling ambiguous, high-leverage problems
• You think in terms of leverage and impact (“80% value with 20% effort”)
• You’re excited about redefining how teams and AI work together
• You view failures as learning accelerants

You won’t be happy at Kinelo if:

• You want slow pace or highly defined problems
• You bring ego instead of curiosity and ownership
• You’re uncomfortable competing in a fast-moving, high-expectation environment

• Competitive salary with meaningful early-stage equity
• Full benefits (health, vision, dental, 401k, parental leave)
• This position is in person in San Francisco at our office at 2nd and Mission. Some WHF and remote are okay.

At Kinelo, we are rethinking organizational structure, corporate hierarchy, and how people work together with machines. Today, we’re building the context layer that connects the tools teams already use into persistent memory that AI agents can reason over and act on. We’re heading toward a world where AI coworkers work alongside humans at every level of a new kind of fast-moving, hyperefficient organization, with purpose and responsibilities, not just tasks.