About this role
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
Technical Implementation Engineer — Customer Solutions & Integrations
Role summary: Sits between Technical Implementation and Engineering — owns technical onboarding, data ingestion, and custom integration work for customers on the platform (ETM/VMDR context), with enough coding and AI-tooling fluency to automate repetitive implementation work rather than doing it manually each time. Note - Relocation to Pune is required for this role, Role may involve Night shifts. We work 3 days from Office in a week.
• Core Responsibilities • Data ingestion & onboarding: Build and validate CSV/bulk data ingestion pipelines into ETM (asset data, business context, criticality tags, third-party vulnerability feeds) • API-based integrations: Build custom solutions using Qualys APIs and third-party APIs (ServiceNow, Jira, Tenable, Rapid7, Defender, SIEM/SOAR platforms, ticketing systems) • Customer-facing technical work: Join customer calls to scope integration requirements, troubleshoot live issues, and walk technical stakeholders (network/security/IT teams) through implementation steps • Automation of implementation work itself: Use AI agents/scripting to templatize and speed up recurring implementation tasks (data mapping, connector setup, validation checks) rather than repeating manual work per customer • Documentation & handoff: Produce clean runbooks/config docs so Support and the customer's own team can maintain the integration post-go-live
• AI & Agentic Automation - The engineer will be expected to use modern AI tooling as an engineering productivity layer. The role should be capable of evaluating and building workflows where AI/agents can assist with implementation activities such as: • Understanding customer integration requirements. • Mapping customer schemas to Qualys schemas. • Generating transformation logic. • Creating API integration code. • Analysing integration errors and logs. • Generating configuration templates. • Validating implementation prerequisites. • Generating customer-specific implementation documentation. • Performing repetitive implementation checks. • Building internal agents that execute controlled implementation workflows.
• Experience with tools such as GPT-based agents, Claude-based workflows, RAG, function/tool calling, MCP-style integrations, RPA, or similar automation frameworks is valuable. • The expectation is not that the engineer is an AI researcher. • The expectation is that they understand how to apply AI safely and practically to reduce implementation effort and increase implementation consistency.
• Required Qualifications: • Programming proficiency (Python strongly preferred — scripting, API clients, data transformation) • Solid REST API experience (auth flows, pagination, rate limits, webhook handling) • Comfortable with CSV/structured data manipulation and data validation at scale • Working knowledge of at least one ticketing/ITSM platform integration (ServiceNow, Jira, Remedy) • Experience or strong aptitude with AI agent tooling (e.g., building/using agents for workflow automation — could be internal tooling, Claude/GPT-based agents, or RPA-adjacent tools) • Strong verbal communication — able to run technical discussions directly with customer engineering/network teams, not just write code
• Preferred Qualifications: • Prior exposure to Qualys VMDR/ETM, or a comparable VM platform (Tenable, Rapid7, Qualys competitors) • Experience with SOAR platforms or security automation • Familiarity with cloud platform APIs (AWS/Azure/GCP) for asset ingestion • Basic understanding of vulnerability management workflows (so they understand why the data matters, not just how to move it)