3 days ago
Base Salary
$150k - $190k/yr
Responsibilities
- Lead the design and implementation of scalable REST APIs and backend services for customer-facing security workflows and MCP integrations.
- Define API contracts, data-access patterns, authentication and authorization approaches, and service lifecycle and versioning strategies.
- Design secure interactions between MCP clients and servers, REST APIs, tools, and Vectra data sources.
- Build reliable, observable, performant services for AI-assisted and agentic product experiences.
- Make architecture decisions across APIs, asynchronous workloads, databases, caching, and cloud services.
- Improve reliability through instrumentation, monitoring, incident analysis, capacity planning, and performance optimization.
- Collaborate with product managers, security researchers, data scientists, UX, and partner engineering teams to turn ambiguous requirements into durable solutions.
- Establish engineering standards through design reviews, code reviews, documentation, and technical mentorship.
- Guide less-experienced engineers and promote strong ownership, learning, and constructive feedback.
- Partner with security teams on secure-by-default identity, access control, data handling, and auditability practices.
Requirements
- 6+ years of professional software engineering experience with substantial backend or platform engineering experience.
- Strong Python experience or deep experience in another backend language with the ability to work effectively in Python.
- Proven experience designing, building, and operating production REST APIs at scale.
- Experience designing API contracts with OpenAPI/Swagger or comparable specification-driven approaches.
- Experience integrating AI applications, agents, or tools with REST APIs and enterprise data sources.
- Hands-on familiarity with the Model Context Protocol, including designing MCP servers or tools or integrating MCP clients with REST APIs and data services.
- Experience with AWS cloud services; Amazon Bedrock experience is strongly preferred.
- Experience with relational databases such as PostgreSQL, MySQL, or MariaDB, including schema design and query-performance considerations.
- Experience with distributed-systems concerns including asynchronous processing, retries, idempotency, rate limiting, caching, and graceful failure handling.
- Experience with automated testing, CI/CD, production debugging, and service observability.
- Strong understanding of authentication, authorization, and secure API design, including OAuth, OIDC, IAM, token handling, and least-privilege access.
- Comfort working in Unix/Linux environments.
- Strong written and verbal communication skills and the ability to explain technical tradeoffs to varied audiences.
- Preferred experience deploying workloads on Kubernetes or containerized platforms.
- Preferred experience with FastAPI, Django, Flask, Celery, or other Python web and asynchronous frameworks.
- Preferred experience building production applications with Amazon Bedrock, including model invocation, guardrails, knowledge retrieval, or agent capabilities.
- Preferred backend-heavy full-stack experience, including UI components and workflows consuming REST APIs and supporting AI-assisted experiences.
- Preferred familiarity with LangChain, LangGraph, retrieval-augmented generation, embeddings, vector search, event-driven architectures, queues, streams, workflow orchestration, Infrastructure as Code, analytical or lakehouse technologies, and LLM-assisted engineering tools.
- Experience in cybersecurity, enterprise SaaS, or other security-sensitive domains is preferred.
- BS or MS in Computer Science, Engineering, or equivalent practical experience.
Benefits
- Comprehensive total rewards package including health care insurance, income protection and life insurance, retirement savings plans, behavioral and emotional wellness services, generous time away from work, and an employee recognition program.
- Eligibility for an incentive plan and participation in the employee equity plan; compensation details are excluded here.
- Final-round candidates should expect an onsite interview at a Vectra office, with scheduling and logistics coordinated in advance.
Tech Stack
Categories
About Vectra
Vectra AI is the cybersecurity AI leader in protecting modern networks from modern attacks. The Vectra AI Platform delivers real-time visibility into network activity, clear insight into which behaviors matter most, and the ability to act before risk becomes impact. By connecting and analyzing activity across on-premises, multi-cloud, identity, SaaS, edge, and IoT/OT environments, Vectra AI helps organizations reduce exposure, accelerate detection and response, and automate security operations with AI. Backed by more than a decade of AI and machine learning innovation and a portfolio of 39 cybersecurity AI patents, Vectra AI empowers security teams to stay ahead of emerging AI-powered attacks, improve operational efficiency, and demonstrate resilience in an increasingly complex, AI-driven world. Recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Network Detection and Response (NDR) for the second consecutive year. Learn more at vectra.ai.