Tech Lead, AI
Leapfrog Technology · Kathmandu, Bagmati, Nepal
What Leapfrog Technology asks for
- Lead technical direction on AI-augmented projects, own architecture decisions and ADRs
- Review and validate AI-generated code; enforce quality, security, and performance standards.
- Mentor engineers on effective use of agentic tools Claude Code, Cursor, Copilot) by ensuring engineers know what these tools are doing for them.
- Assess and benchmark AI tooling for the team - identify what genuinely accelerates delivery vs. what creates noise
- Collaborate with the client and delivery team to scope features where AI can reduce time-to-market
- Identify and mitigate AI-specific risks: prompt injection, hallucinated dependencies, licensing exposure in generated code
- Champion engineering practices such as testing, observability, security all the things that remain non-negotiable in an AI-assisted workflow
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- Employer
- Leapfrog Technology
- Location
- Kathmandu, Bagmati, Nepal
- Type
- Fulltime Permanent
- Team
- Machine Learning
- Posted
- 16 months ago
As Tech Lead, AI the quality is to be a guardian for AI-augmented delivery. This is not a pure management role, they should be shipping code, reviewing AI-generated output, and making architectural decisions. They are the person who knows when to trust the AI and when to override it.
Key Responsibilities:
- Lead technical direction on AI-augmented projects, own architecture decisions and ADRs
- Review and validate AI-generated code; enforce quality, security, and performance standards.
- Mentor engineers on effective use of agentic tools Claude Code, Cursor, Copilot) by ensuring engineers know what these tools are doing for them.
- Assess and benchmark AI tooling for the team - identify what genuinely accelerates delivery vs. what creates noise
- Collaborate with the client and delivery team to scope features where AI can reduce time-to-market
- Identify and mitigate AI-specific risks: prompt injection, hallucinated dependencies, licensing exposure in generated code
- Champion engineering practices such as testing, observability, security all the things that remain non-negotiable in an AI-assisted workflow