AI Engineer
New
G
GitLabDevSecOps
Remote, BangaloreFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- GraphQLPythonJavascriptSalesforceTypeScriptRESTful APIsZendeskPrompt EngineeringLLM
Requirements
- Genuinely invested in technology, the foundational and the cutting-edge in equal measure, reaching for the simplest solution.
- Competent, confident coding skills to build working solutions end-to-end, write clean and maintainable code, and debug effectively.
- Strong proficiency in at least one modern scripting language (Python, JavaScript/TypeScript, or similar).
- Solid understanding of REST APIs, GraphQL, and integration patterns.
- Deep, practical experience with modern AI technologies, specifically prompt engineering as a core discipline.
- Experience with model selection and cost-performance trade-offs in AI.
- Familiarity with agentic architecture patterns: tool use, multi-agent orchestration, human-in-the-loop designs, guardrails, evaluation frameworks, and production-grade reliability patterns.
- Practical fluency across the LLM ecosystem: hands-on experience with models from Anthropic, OpenAI, open-source alternatives.
- Critical thinking about AI Safety & Risk Awareness, including designing appropriate guardrails.
- Systems Thinking & Diagnostic Rigour to identify constraints and trace problems to root causes.
- Familiarity with enterprise business systems: CRM (Salesforce), marketing automation (Marketo), support platforms (Zendesk).
- Familiarity with integration and orchestration tools (Workato), AI platforms (Relevance AI), and enterprise search and knowledge tools (Glean).
- Strong understanding of enterprise data models and workflows.
- Ability to have meaningful conversations with stakeholders across diverse domains and quickly understand their unique needs.
- Track record of owning complex initiatives from discovery through delivery, comfortable with ambiguity.
- Product mindset: ability to scope MVPs, prioritise ruthlessly, and deliver iteratively, considering adoption, user experience, and business outcomes.
Responsibilities
- Diagnose business problems before building solutions. Map workflows, identify constraints, and confirm whether AI is the right intervention.
- Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration.
- Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months, with a focus on practical outcomes and measurable business value.
- Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput.
- Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform.
- Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R&D.
- Partner closely with stakeholders across functions to understand the real constraints. Ask the right questions, bridge technical and non-technical perspectives, and align on outcomes before jumping to solutions.
- Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable.
- Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations that help the team scale its impact.
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