Staff Engineer - Agentic AI Platform
| Verified Pay check_circle | Provided by the employer$200000 - $250000 per year |
|---|---|
| Hours | Full-time |
| Location | Redwood City, CA Redwood City, California open_in_new |
About this job
Job Description
We are the Agentic HR platform for enterprise teams and maker of Harper, the world’s first AI HR generalist. We create AI agents that streamline business processes, elevate the employee experience, and free teams to focus on truly strategic work. Backed by top-tier VCs, we've raised $55M in venture funding from Norwest Venture Partners, True Ventures, and Shasta Ventures.
We were recently awarded Top HR Product of 2025 by HR Executive, recognizing how we revolutionize service delivery by combining deep domain expertise with unparalleled functional capabilities.
We’re looking for staff-level engineers who combine strong distributed systems expertise with deep practical understanding of AI workflows and harness engineering – engineers who know how to make GenAI systems work reliably in production.
What You'll Build
Scalable agentic orchestration frameworks that integrate seamlessly with enterprise systems, enabling no-code automation across complex workflows
Pioneering memory architectures and retrieval systems that overcome traditional RAG limits, giving agents persistent context across multi-step processes
AI harnesses that improve the reliability, evaluation, observability, and reasoning quality of LLM-powered systems – including prompt optimisation, hallucination reduction, and LLM context management
Domain-optimised reasoning LLMs that unlock new reasoning capabilities for nuanced business scenarios
Backend infrastructure powering multi-agent workflows, human-in-the-loop systems, and intuitive UIs for seamless human-AI collaboration on documents and processes
Tooling that enables rapid experimentation, evaluation, and deployment of AI workflows at scale
Outdated Industry, Massive Opportunity – HR technology is one of the largest and most entrenched software categories in the world, and most of the infrastructure running it was built for a different era. Every person in a workplace is touched by it, yet the experience has barely improved in decades. Wisq is rebuilding it from the ground up with AI at the centre – not bolted on, but native to every layer of the product. The market is large, the incumbents are slow, and the timing is right.
Founders and Team Who Have Done This Before – The founding team previously built Glint, an HR analytics company acquired by LinkedIn, with strong VC backing throughout. A core group of engineers with ten to fifteen years of experience and two to three companies built together have returned to do it again at Wisq. Series A with a Series B raise planned for this year – early enough for meaningful equity upside, established enough that the thesis is proven, and recognised by Fast Company as the number two most innovative company in HR.
Tier 1 Backing & Real Runway – Wisq has raised $55M from Norwest, True, and Shasta Ventures. The company has the institutional confidence and financial runway to execute on its growth ambitions – this is not a bet-the-farm early stage hire, it is a well-capitalised company moving fast. That stability also reflects the culture: unlike many startups at this stage, the majority of the team includes people with families and real lives, with high standards but without the burnout of other start-ups.
A Great Place to Build – Small guilds of two to three people, two days hybrid in Redwood City, and a culture that values output over face time. No sprawling teams, no layers of process. Wisq has consistently attracted engineers who come back – the repeat team dynamic is one of the clearest signals that people genuinely enjoy working here.
Fully AI-Native Engineering – Most engineers at established companies spend years waiting for permission to work this way. At Wisq, fully agentic engineering is not a future state – it is how the company operates today, from product to infrastructure to internal development. Engineers are expected to move fast, experiment freely, and shape how AI gets used across the organisation.
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