About the job
About Flow Engineering
Flow Engineering is at the forefront of innovation, providing an AI-native requirements platform tailored for forward-thinking engineering organizations. Our mission is to empower hardware teams to seamlessly collaborate with AI agents, optimizing the design, validation, and evolution of intricate systems with unmatched efficiency and precision.
Role Overview
We are on the lookout for talented Software Engineers to engineer AI-driven features that enhance the way teams create, review, and oversee requirements. You will be instrumental in developing workflows for agentic systems and domain engineers, placing AI at the core of systems reasoning.
This position merges the realms of AI, product management, and full-stack engineering, allowing you to transform concepts from initial prototypes into robust, observable features deployed in production.
Your Responsibilities
Design and implement AI-enhanced features, including assisted requirement drafting, consistency checks, impact analysis, and intelligent suggestions tailored for systems and domain engineers.
Develop agentic workflows that enable systems and domain engineers to explore designs, simulate alterations, and validate requirements effectively.
Evaluate and integrate advanced language models and related tools, focusing on reliability, latency, cost-effectiveness, and debuggability in live environments.
Build and maintain essential infrastructure, including data pipelines, evaluation frameworks, and observability measures with appropriate safety protocols.
Engage across the technology stack, from backend APIs to user interface integrations, ensuring the delivery of comprehensive AI solutions rather than isolated model endpoints.
Collaborate with product teams and clients to pinpoint high-impact workflows, conduct experiments, and iterate swiftly based on user feedback.
Your Profile
Minimum 3 years of experience in software development, with a strong focus on designing, testing, and operating scalable services within cloud environments.
Hands-on experience with leading language model providers and technologies (e.g., OpenAI, Anthropic, Hugging Face, vector databases, retrieval-augmented generation patterns).
Familiarity with prompt engineering, retrieval-augmented systems, evaluation techniques, and safety/guardrail methods.
Proficient in evaluating trade-offs among various models, architectures, and deployment strategies, making informed decisions.
Thrives in a dynamic, ownership-driven environment where experimentation and rapid iteration are commonplace.
