Member of Technical Staff, Core Product

At Enterpret, we are building the platform that unlocks the most impactful dataset for any business — customer feedback. We solve complex problems across natural language processing, serverless computing, and analytics on the frontend, pushing the envelope of what's possible by applying first-principle thinking.
Investors like Kleiner Perkins and Sequoia Capital share our conviction, and respected product development teams at companies like Canva, Notion, Samsung, and Loom rely on us to understand and act on the voice of their customers.
We love working with folks who are resourceful, thrive in ambiguity, and display a strong sense of ownership.
Our engineering culture is built around leveraging and contributing to open-source tools. We aim to build upon and improve state-of-the-art systems in our field of work.
Read more about our team, core values, and operating principles - here.

• →Build and scale the core backend and infrastructure that powers our customer feedback intelligence platform — owning systems from data ingestion through real-time analytics.
• →Harden the ML and NLP infrastructure — pipelines, model-serving, and data flows — so features stay reliable in real customer environments at scale.
• →Own critical infrastructure decisions around data models, event flows, and service boundaries, with strong correctness and data-integrity guarantees.
• →Instrument systems deeply for observability, so failures surface early and production behavior becomes something the team learns from.
• →Balance speed, cost, and long-term system health, making pragmatic cost-effective and scalable trade-offs while shipping continuously.
• →Partner with Product, Design, and the founding team to turn ambiguous problem statements into clear infrastructure, and contribute directly to product direction.
• →Raise the bar on the systems you own through clean code, thorough design reviews, and mentorship — and propose platform-level improvements where you spot leverage.

• 6–8 years in software engineering, with a proven record of building and shipping reliable systems in production.
• 3+ years at one organization where you've built infrastructure from scratch and owned complex projects end to end, from problem framing to production impact.
• Deep expertise in infrastructure — not just distributed systems: data pipelines, event-driven/microservices architectures, and the operational backbone (observability, reliability, cost) that keeps them healthy in production.
• Hands-on depth in at least one of Golang, serverless computing, SQL/NoSQL, ElasticSearch, or GraphQL, and the range to go deep when things break. Bonus: experience building or operating ML/NLP infrastructure such as pipelines, model-serving, or feature stores.
• Strong systems thinking and engineering judgment: you reason clearly about data models, boundaries, and failure modes, and you know when to move fast and when to slow down.
• A track record of mentoring and collaborating — raising the bar through code, reviews, and cross-functional partnership with Product and Design.
• Comfort operating in ambiguity, making sound decisions with incomplete information, with a bias toward action and continuous learning.

• High Impact: Build the foundational backend and infrastructure at an early-stage startup where every line of code matters.
• Ownership: End-to-end responsibility for features and systems.
• Complex Challenges: Work on state-of-the-art ML/NLP infrastructure, distributed systems, and real-time analytics at production scale.
• Growth: Learn and grow with a high-caliber team and expand into deep technical expertise or a tech-lead path.
• Culture: Open, collaborative, and values-driven environment with autonomy.
• Benefits: Competitive salary, equity, hybrid work setup, premium healthcare, and more.

We are an equal opportunity employer. We ensure that none of our employees or prospective employees receives less favourable treatment as a result of age, sex, disability, marital status, colour, race, religion or ethnic origin. Equally we aim to ensure that no such employee is disadvantaged by terms and conditions of employment which cannot be justified.