Sift

Backend Engineer

• Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry
• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context
• Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails
• Build the distributed systems that let long-running agent work stream in real time, survive disconnects, and resume across restarts
• Design job-based execution systems that schedule, scale, and tear down agent workloads on Kubernetes, both in the cloud and on-prem
• Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly
• Design and implement the APIs that power our agentic capabilities
• Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production
• Integrate and assess frontier models across providers

Software Engineer, Backend

Senior Software Engineer, Backend

• Talk directly to customers and partner with product to turn real review workflows into agent capabilities
• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context
• Build everything around the model that makes agents dependable, including tool interfaces and sandboxed code execution
• Build distributed systems that allow long-running agent work streams in real time
• Design job-based execution systems for Kubernetes in the cloud and on-premises
• Develop and maintain Sift’s MCP server for direct telemetry querying
• Design and implement APIs powering agentic capabilities
• Build evaluation suites to measure agents’ impact on engineers and instrument qualities in production
• Integrate and assess frontier models across providers

Senior Software Engineer, Backend – Agentic AI

AI Engineer

• Collaborate with customers to develop agent capabilities and workflows
• Design, ship, and operate agentic systems for large-scale data
• Build dependable tools and interfaces
• Develop and maintain the MCP server
• Work across the entire stack

Software Engineer, Full Stack – Agentic AI

• Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry
• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context
• Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails
• Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly
• Work across the whole stack
• Build the frontend surfaces where Sift Agents live, and make them feel great
• Design and implement the APIs that power our agentic capabilities
• Run agents reliably at scale, both in the cloud and on-prem
• Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production
• Integrate and assess frontier models across providers

• talk directly to customers and partner with product to turn real review workflows into agent capabilities
• design, ship, and operate agentic systems that reason over large-scale time-series data
• build everything around the model that makes agents dependable
• develop and maintain Sift’s MCP server
• work across the whole stack
• build the frontend surfaces where Sift Agents live
• design and implement the APIs that power our agentic capabilities
• run agents reliably at scale
• build evaluation suites that measure whether agents actually help engineers

Senior Software Engineer, Full Stack – Agentic AI

Full-stack Engineer

• Build and deliver customer-facing features end to end, across both the frontend and the backend. Some features are primarily one or the other; many involve both.
• Work closely with Customer Success and Product to turn customer requests and bug reports into delivered features.
• Work across different areas of our various product and technology areas, including Payments, Account Takeover, Dispute Management, Console, Workflows, and the API. You are not expected to know every area from the start; getting up to speed quickly is part of the role.
• Contribute to backend services in our stack (Ruby on Rails, Java, and others), building your familiarity with it over time.
• Help maintain our tooling and engineering practices so the team can continue to deliver reliably.

Full-Stack Engineer

Machine Learning Engineer

• Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real time.
• Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognition.
• Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
• Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databases.
• Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions.

• Architect and implement engineering solutions to address complex customer needs at scale
• Develop, build, and maintain both internal and external facing API platforms and endpoints to enable customer integration, automation, and powering our customer-facing Console web application
• Partner with product management to help scope and shape project requirements
• Collaborate with other engineers within the team as well as across other engineering teams
• Help evolve and improve our engineering practices

Staff Engineer

Product Manager

• Own the Product Vision Across Initiatives: Partner with engineering and leadership to define and articulate the “why” and “what” across multiple product areas and strategic initiatives. Use data, market research, and customer insight to set direction and prioritize ruthlessly.
• Drive the Roadmap with Business and Technical Clarity: Own product roadmaps that reflect both customer needs and business objectives. Communicate the rationale behind prioritization decisions clearly to engineering, executives, and go-to-market partners alike.
• Be the Voice of the Customer: Engage regularly and deeply with customers — from discovery conversations to beta programs. Validate hypotheses, surface unmet needs, and ensure the customer perspective is embedded in every product decision.
• Execute with Precision: Write clear, detailed specifications. Create tickets, draft copy, define acceptance criteria, and partner closely with engineering to ship high-quality product on time.
• Partner Across the Business: Work hand-in-hand with Sales, Marketing, and Customer Success to ensure new features and products are positioned and launched effectively. Support deal cycles, create GTM materials, and drive adoption of what you ship.
• Inspire Cross-Functional Teams: Rally engineering, design, data science, and business stakeholders around a shared vision. Be a clear communicator and a collaborative leader who helps teams do their best work.
• Contribute to Company Strategy: Help identify new market opportunities, inform product strategy at the portfolio level, and contribute to Sift’s long-term product direction.

Security Engineer

• Design and implement security controls and tooling across Sift’s infrastructure and applications (e.g., IAM policies, network controls, secrets management, endpoint protections, container and workload security).
• Embed with product and platform teams to perform security design reviews, threat modeling, and code or configuration reviews for new features and services.
• Improve the secure SDLC by integrating AI-powered scanning tools, security scanning (SAST/DAST, dependency and container scanning) into CI/CD, and by developing guardrails, templates, and best practices for engineers.
• Own or co-own vulnerability management workflows, from discovery and triage through remediation, including defining SLAs, coordinating with service owners, and tracking closure.
• Develop automation (scripts, services, integrations) to detect misconfigurations, anomalous activity, or policy violations, and to reduce manual operational work for the security team.
• Participate in security incident response (on-call rotation or escalation), including investigation, containment, root cause analysis, and long-term fixes.
• Contribute to security documentation and standards, ensuring we have clear, actionable guidance for engineers on topics like authentication, authorization, data encryption, and key management.
• Support audits and assessments (e.g., SOC 2, customer security questionnaires) by providing technical details and evidence of control design and effectiveness.
• Mentor other engineers on secure design and implementation practices through pairing, reviews, training sessions, and written guidance.

Senior Security Engineer

Data Scientist

• Architect and own advanced modeling strategies across fraud and abuse problem domains.
• Establish and defend model quality standards that account for adversarial dynamics.
• Lead statistical innovation on highest-leverage fraud problems.
• Partner with ML engineering and information security on adversarial robustness.
• Build automated workflows that scale human expertise while respecting fraud complexity.

Staff Data Scientist

Customer Success Manager

• Lead and develop a high-performing CSM team.
• Manage, coach, and develop a team of Customer Success Managers.
• Raise the bar on customer strategy, account planning, executive engagement, and execution quality.
• Build clear team expectations, operating rhythms, and accountability mechanisms.
• Support hiring, onboarding, performance management, and career development.
• Foster a strong, collaborative, commercially minded, and customer-first team culture.
• Help CSMs connect day-to-day customer activity to broader business outcomes.
• Drive customer outcomes and retention performance.
• Lead team execution against customer health, product adoption, renewal readiness, and risk mitigation goals.
• Partner with CSMs on strategy for high-priority, complex, or at-risk accounts.
• Identify trends across the customer portfolio and translate them into team priorities, playbooks, and cross-functional recommendations.
• Improve how the team surfaces, manages, and communicates customer risk.
• Collaborate closely with Sales on account strategy, renewal planning, expansion opportunities, and risk mitigation.

Software Engineer, Backend

Software Engineer, Backend

Senior Software Engineer, Backend

Senior Software Engineer, Backend – Agentic AI

Software Engineer, Full Stack – Agentic AI

Software Engineer, Full Stack – Agentic AI

Senior Software Engineer, Full Stack – Agentic AI

Senior Software Engineer, Full Stack – Agentic AI

Full-Stack Engineer

Machine Learning Engineer

Staff Engineer

Product Manager

Senior Security Engineer

Staff Data Scientist

Senior Manager, Customer Success