Senior Software Engineer

Position Overview

Vectra® is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises.

The Vectra AI Platform delivers integrated signal across public cloud, SaaS, identity, and data center networks in a single platform. Powered by patented Attack Signal Intelligence, it empowers security teams to rapidly prioritize, investigate, and respond to advanced cyber-attacks. Organizations worldwide rely on Vectra AI to move at the speed and scale of hybrid attackers. For more information, visit .

Our Engineering organization is a fast-growing team of collaborative, technically strong, and passionate problem solvers. We value ownership, pragmatic technical judgment, and the drive to build meaningful technology that solves real-world security challenges. Engineers make a measurable impact on the product, company, and culture through thoughtful design, strong execution, mentoring, and continuous improvement.

The Application Data Platform team designs, builds, and operates data-intensive services and customer-facing capabilities across APIs, backend systems, and UI experiences. Python is a primary language, and we build end-to-end solutions spanning API design, distributed services, databases, and cloud infrastructure.

As a Senior Software Engineer, you will help evolve our REST API platform to support secure, reliable, and scalable interactions with AI agents and Model Context Protocol (MCP) clients and servers. You will lead the design of API capabilities that make Vectra data safely discoverable and actionable through MCP-based workflows, while ensuring the underlying services meet high standards for security, observability, performance, and operational reliability.

Responsibilities

• Lead the design and implementation of scalable REST APIs and backend services that support customer-facing security workflows and MCP-enabled integrations.
• Define API contracts, data-access patterns, authentication and authorization approaches, and lifecycle/versioning strategies for platform services.
• Design how MCP clients and servers securely interact with REST APIs, tools, and Vectra data sources.
• Build reliable, observable, and high-performance services for AI-assisted and agentic product experiences.
• Work with product managers, security researchers, data scientists, UX, and partner engineering teams to turn ambiguous requirements into durable technical solutions.
• Make sound architecture decisions across APIs, asynchronous workloads, databases, caching, and cloud services.
• Improve platform reliability through instrumentation, monitoring, incident analysis, capacity planning, and performance optimization.
• Establish engineering standards through design reviews, code reviews, documentation, and technical mentorship.
• Guide less-experienced engineers and contribute to a culture of strong ownership, learning, and constructive feedback.
• Partner with security teams to ensure APIs and AI integrations follow secure-by-default practices for identity, access control, data handling, and auditability.

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 using 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 (MCP), including designing MCP servers/tools or integrating MCP clients with REST APIs and data services.
• Experience with AWS cloud services; practical experience with Amazon Bedrock 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 such as 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.
• Comfortable working in Unix/Linux environments.
• Strong written and verbal communication skills, including the ability to explain technical tradeoffs to varied audiences.

Preferred

• Experience deploying and operating workloads on Kubernetes or containerized platforms.
• Experience with FastAPI, Django, Flask, Celery, or other Python web and asynchronous frameworks.
• Experience building production applications using Amazon Bedrock, including model invocation, guardrails, knowledge retrieval, or agent capabilities.
• Experience with backend-heavy full-stack development, including building intuitive UI components and workflows that consume REST APIs and support AI-assisted or agent-driven experiences.
• Familiarity with LLM application frameworks such as LangChain, LangGraph, or similar orchestration/tooling frameworks.
• Familiarity with modern frontend technologies such as React, TypeScript, and component-based UI development.
• Familiarity with retrieval-augmented generation, embeddings, vector search, and secure data-retrieval patterns.
• Experience with event-driven architectures, queues, streams, or workflow orchestration.
• Experience with Infrastructure as Code, such as Terraform or CloudFormation.
• Familiarity with analytical, OLAP, or lakehouse technologies such as Snowflake, Delta Lake, Iceberg, or BigLake.
• Experience in cybersecurity, enterprise SaaS, or other security-sensitive domains.
• Familiarity with LLM-assisted engineering tools such as Codex, Claude, OpenCode, or Cursor.

Education

BS or MS in Computer Science, Engineering, or equivalent practical experience.

Note

Candidates selected for final-round interviews should expect to participate in an onsite interview at a Vectra office. Scheduling and logistics will be coordinated in advance.