Engineering Leader
As an Engineering Leader at Ema, you will build and lead a high-performance engineering organization by recruiting, hiring, and developing senior engineers across multiple sub-teams such as cloud infrastructure, data platform, ML operations, and developer experience. You will establish engineering standards, code review culture, on-call expectations, and a bias-toward-shipping mentality balanced with production rigor. You will coach and grow senior/staff engineers into technical leaders and manage engineering managers as the organization scales. Additionally, you will set the 6–18 month platform roadmap in partnership with engineering teams, make high-stakes architectural decisions regarding build vs. buy, migration strategies, and technology bets, and own the outcomes. You will drive cross-functional alignment with product, ML/AI research, and go-to-market teams ensuring the platform evolves with customer and product needs. Moreover, you will own production health for all platform services including incident response, postmortems, SLO tracking, and capacity planning. You will establish and iterate on engineering practices that enable fast shipping without compromising reliability and participate in executive-level reviews on infrastructure spend, system health, and engineering velocity.
Senior Python Systems Developer - Functional Testing Project
Create functional black box tests for large codebases in various source languages, create and manage Docker environments to ensure 100% reproducible builds and test execution across different platforms, monitor code coverage and configure automated scoring criteria to meet industry benchmark-level standards, and leverage LLMs such as Roo Code and Claude to accelerate development cycles, automate repetitive tasks, and improve overall code quality.
Engineering Manager, Go - Assist & Chat
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts, including development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.
Compliance Program Manager
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts including development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.
Enterprise Account Executive (New York City)
Debug and fix issues in the platform and ship pull requests with the fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.
Senior Engineer, Internal tools
The Senior Engineer on the internal tools team is responsible for building and maintaining internal platforms and tools used by various departments such as People, Finance, Ops, Sales, and Engineering. The role involves owning features end-to-end, including requirements gathering, architecture, implementation, testing, deployment, and monitoring. The engineer is expected to write clean, well-tested, production-grade code and build API-first integrations to connect multiple business systems like HRIS, CRM, finance platforms, and developer tools. Responsibilities include designing for reliability, performance, and scalability, eliminating data silos by creating clean data pipelines, and owning services in production with monitoring, alerting, incident response, and post-mortems. The role also involves building AI/LLM-powered features to automate internal workflows, moving prototypes to production, and staying updated on emerging AI technologies. Collaboration includes working directly with business stakeholders to translate pain points into technical solutions, mentoring junior engineers, conducting code and design reviews, influencing technical direction, proposing architectural improvements, and driving best practices across the team.
Senior Brand Events Manager
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage, including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts, including development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.
Intern, Software Engineer - Platform
As a Platform Engineering Intern at Hayden AI, you will take ownership of a real project and see it through to completion, build and ship features with support from senior engineers, write clean and scalable code, test your work and iterate quickly, be involved in design discussions, deployment, collaborate with engineers in code reviews and team discussions, participate in standups, sprint planning, and retrospectives, support the team on ad hoc engineering tasks, help improve performance, reliability, or usability where needed, and ask questions, seek feedback, and apply it quickly. The work spans building foundational systems that power the product, including infrastructure, services, and data pipelines to ensure Perception algorithms run reliably across edge devices and cloud environments. Projects may include GPS data analysis, training deep learning models, creating AI datasets, lidar/camera data tooling, test cases for end-to-end system performance, developing cloud services in the event processing pipeline, and adding pages or user flows to the Portal web application.
Offensive Security Engineer
Lead advanced "whitebox" penetration testing engagements with full access to source code, identifying systemic weaknesses, logic flaws, and architectural gaps. Simulate adversarial attacks across web applications, APIs, and containerized infrastructure including Kubernetes and Docker. Perform offensive testing on AI-enabled systems focusing on prompt injection, data leakage, and abuse of AI-driven components. Research and chain vulnerabilities to demonstrate realistic business risks. Build internal offensive tooling, including AI-assisted testing tools, to automate discovery of common bugs while maintaining manual testing depth. Collaborate with engineering product teams and security architects to explain root causes, influence design guardrails, and triage findings from the Bug Bounty program.
Full-stack Developer (Full-Time/Intern) - SH 全栈工程师 (全职/实习) - 上海
As a Full-Stack Engineer at Flowith, responsibilities include crossing front-end and back-end boundaries to independently or collaboratively lead the full-stack development of core modules, delivering highly available and scalable system code. The role requires deep integration of advanced AI algorithms and complex models into the product flow to create intelligent interactive experiences. The engineer will work closely with product managers, designers, and AI engineers in a creative environment to implement AI concepts. Additional responsibilities include automating deployments and managing continuous integration on mainstream cloud infrastructure, monitoring and optimizing system performance and resource bottlenecks. The role also involves participating in the evolutionary design of core architecture, conducting in-depth code reviews, and accumulating technical components and best practices to elevate the team's overall engineering standards.
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