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, 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 &: 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 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
