Technical Implementation Engineer

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.

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.

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)