Own backend engineering work from problem definition through production, shaping the technical direction of a platform handling sensitive financial data
Locations (2)
New York, New York, United States
San Francisco, California, United States
Compensation
Base salary: USD 175,000 to 225,000 per year
Responsibilities
Take ambiguous initiatives, break them into workable pieces and carry them to production with minimal oversight
Make architecture and design decisions for the backend infrastructure
Partner with product and non-technical colleagues to define features and set direction
Build automation for transaction, billing and reimbursement workflows
Improve engineering tooling and processes as one of the first members of a small team
Requirements
Bachelor's or master's degree in computer science or a related engineering field, or an adjacent degree from a strong school
The role involves designing and building a core classification engine that powers multiple security solutions across the platform, working at the intersection of large-scale systems and applied AI.
Responsibilities
Build and scale AI-driven data classification and detection capabilities for next-generation data security products
Design systems that identify, classify, and protect sensitive data in real time across cloud and endpoint environments
Lead technical design discussions and influence architecture for large-scale data processing systems
Partner with product, infrastructure, and other engineering teams to deliver tightly integrated solutions
Raise the technical and collaborative bar by mentoring and sharing knowledge
Lead the technical strategy and modernization of iHerb’s product catalog platform, driving AI-native engineering practices and cross-team architectural standards.
Compensation
The expected salary range for this role is $204,000.00 - $260,000.00 USD.
Responsibilities
Define and own catalog platform architecture
Lead technical scoping and execution of modernization effort
Write production code and build proofs of concept
Set and enforce technical standards
Resolve cross-cutting technical dependencies
Requirements
Bachelor’s Degree in Computer Science or related field
As a Software Engineer supporting agents, you'll design how Nominal's agents work: you'll architect the one platform our agents, the Nominal MCP, and our internal agent all run on, and set technical direction for the team that builds on it.
Responsibilities
Build agent tools and workflows that ship to every customer, from turning test plans into automated checks to running investigations across tests.
Grow the Nominal MCP so external agents can do more of the work our users do, safely and with the user's own permissions.
Build the integrations our internal company agent needs to work across Nominal's own tools and teams.
Turn the patterns forward-deployed engineers find in the field into capabilities every customer gets.
Instrument what you ship, read the traces, and fix what the evals and users tell you.
Build and maintain the technical platform for a Series B education technology company, focusing on Flutter mobile app, AI and agent infrastructure, developer experience, and backend services.
Compensation
Base salary: €80,000 to €110,000 annually. Visa sponsorship is not available.
Responsibilities
Own core parts of the Flutter app, including shared components, design systems, state management, performance, and tooling
Build AI and agent infrastructure, including MCP servers, background agent capabilities, evaluations, and feedback loops
Integrate agentic coding tools into everyday engineering workflows
Improve CI/CD, release tooling, and the feedback loop from code changes to production
Ship user-facing features alongside platform work and keep shared foundations dependable for other engineers
The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth.
Responsibilities
Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency.
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Software Engineer, Agents - UKNewNominal · London, United Kingdom