Chainguard is the trusted source for open source. We build hardened, minimal, continuously-updated images, libraries, and packages that eliminate vulnerabilities before they ship — used by teams at Anduril, Canva, OpenAI, Snap, and Snowflake, among others.
We're hiring a PM to own the malware and greyware scanning engine inside Chainguard Repository — the system that analyzes source code, build behavior, and maintainer activity across the open source packages flowing through our platform to catch compromised or malicious artifacts before they reach a customer's environment. You'd own the roadmap for detection coverage, scanner accuracy (precision/recall trade-offs are the daily grind), and how findings get surfaced to security teams and translated into policy enforcement. Close partnership with our detection engineering and threat research teams, and with customers who are increasingly asking "how do you know this package is safe?"
Good fit if you've done PM work on a detection, fraud, spam, or security scanning system before, are comfortable being hands-on with data and false-positive/false-negative trade-offs, and want to work on a problem that's getting more urgent as AI agents pull in more open source dependencies automatically.
JD to be posted imminently but email me if interested and I'll route appropriately: patrick@chainguard.dev
We work directly with strategic customers to design, build, deploy, and improve production AI systems on Snowflake. That includes LLM applications, RAG and agentic workflows, evaluation frameworks, guardrails, observability, and production iteration using Snowpark, Cortex, and Snowflake’s native AI capabilities.
For the FDE role, we’re looking for strong engineers who can build and ship customer-facing AI systems end to end, especially if you’ve worked on LLM apps and care deeply about evals and quality. For the Senior role, we’re looking for someone who can lead multi-engineer AI engagements, mentor other engineers, and still be hands-on in architecture and implementation.
Both roles are customer-facing and involve travel, including at least 25% onsite time with strategic customers.
If you like working in ambiguity, building real AI systems instead of demos, and partnering closely with customers to get things into production, these roles are a good fit.
* Forward Deployed Engineer: https://careers.snowflake.com/us/en/job/SNCOUS40EA1BA0045841...
* Senior Forward Deployed Engineer: https://careers.snowflake.com/us/en/job/SNCOUSA253CD7A2E6945...
At SentiLink, we stop identity fraud at scale. Our products protect banks, fintechs, marketplaces, and leading financial institutions from synthetic identity fraud, identity theft, and emerging threats — analyzing millions of applications while keeping real users moving fast.
We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.
SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
We’re a small, high-impact team solving one of the most interesting and adversarial problems in fintech: how do you build systems that reliably determine whether a real human is on the other side of a financial transaction? We’re hiring across Engineering (Full-stack and Infra) and Data Science / ML roles. Hiring at Manager/Director level as well as mid-level/Senior levels. We’re language-agnostic and hire for fundamentals.
Across the team you’ll see: • Python, Go, Rust, Scala • PostgreSQL, Snowflake • Kafka, Redis • Terraform, Kubernetes • ML: XGBoost, PyTorch, Feature stores, real-time scoring pipelines
If you love solving complex distributed systems challenges, building customer-facing ML products, or working on detection systems that must be both high-precision and low-latency, you’ll fit right in.
Roles are here: https://jobs.ashbyhq.com/sentilink?utm_source=hacker_news If you have questions, feel free to reach out directly at liz.woodfield at sentilink dot com.
Atria Health is hiring for Product Engineer roles (across levels) and a Staff SWE, Agentic AI role.
Our team is operating with the special combination of rigor, empathy, and innovation required to fuel a global shift from reactive sick care to preventative, precision healthcare.
Technologies: Express, React, GCP, Terraform, DBT, MySQL, Snowflake
Learn more about our team here: https://share.atria.org/engineering
To apply, please send a resume to hackernewshiring@atria.org. Every resume sent here will be reviewed by a human.
We use web data to identify things like org structure, tech stack, and key projects (e.g., GenAI initiatives, cloud migrations). Our product already has strong product-market fit, early revenue, and happy customers — and now we’re ready to accelerate.
Our long-term vision is to become the world's best data vendor. Try the product at sumble.com.
We are a team of 25 with experience at companies such as Google, Meta, Stack Overflow, Rippling, Snowflake, Confluent and Kaggle.
We raised $38.5MM from Coatue, Canaan, Square Peg Capital https://techcrunch.com/2025/10/22/sumble-emerges-from-stealt...
Palace Cybersecurity secures large organizations from employees abusing cloud access privileges (Google Workspace, Microsoft SharePoint, Snowflake). We are commercializing Facade, a method for deep learning anomaly detection invented and deployed at Google (published at https://arxiv.org/abs/2412.06700).
Looking for a senior/staff level engineer with >5 YoE shipping production machine learning systems, and some experience with deep learning recommendation models. Prior experience in the cybersecurity domain is preferred, but not required. Fluency in an ML framework (e.g. Pytorch, Jax, or Tensorflow) and ETL data orchestration (e.g. Spark, Beam, Dagster) is required. You will work closely with the founder, an author of the above paper, on building and deploying a system for enterprise customers.
Contact at hiring[at]palacecyber.com