Senior Applied AI Engineer

KOS International Talent Group; Palo Alto (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

KOS International partners with a leading global fintech to hire a Senior Applied AI Engineer for its U.S. AI team. You will drive AI coding tooling, developer experience, and frontier prototypes across internal scenarios that validate streaming UX and long-context memory.

You will turn Silicon Valley product engineering into multiplicative leverage, producing reference code, onboarding playbooks, and workshops to propagate best practices across the organization.

Qualifications

• 6+ years of software engineering experience.
• 2+ years focused on LLM applications.
• Experience shipping AI applications from 0→1 in production.
• Hands-on with AI coding tooling and related tradeoffs.

Responsibilities

• Introduce AI coding tooling best practices and onboarding playbooks.
• Define Skill design conventions; deliver 5–10 reference Skills.
• Prototype AI-native engineering workflows for reference adoption.
• Build internal AI prototypes in employee-facing scenarios.
• Provide runnable reference architecture code for APAC teams.
• Lead cross-team craft propagation via talks, blogs, and workshops.
• Participate in AI architecture reviews and provide frontier feedback.

Skills

Software engineering

AI application engineering

async collaboration

product sense

public technical influence

Education

CS/EE BS or higher

MS preferred

Tools

Claude Code

Cursor

Devin

Replit Agent

LangGraph

AutoGen

CrewAI

OpenAI Swarm

Job description

KOS International is partnering with a leading global financial technology platform to hire a Senior Applied AI Engineer for its U.S. AI team.

You will lead two primary streams:

• AI Coding tooling and developer experience — bringing the engineering depth of Silicon Valley front-line teams (Claude Code, Cursor, Devin, Replit Agent, etc.) into our client.
• AI application paradigm exploration and dogfooding — building small, frontier prototypes in internal scenarios that validate streaming UX, transparent agent steps, long-context memory, and other emerging patterns, and propagating them across the team through reference code, blog posts, and workshops.

This role is about craft and taste. You are not a platform architect, nor a BU project delivery engineer. You are the person who turns front-line Silicon Valley product engineering experience into multiplicative leverage for the entire AI Team.

Key Responsibilities

• Introduce AI Coding tooling best practices — Bring the engineering depth of Claude Code, Cursor, Devin, Replit Agent, and similar tools (Skills, hooks, subagents, long-context engineering, MCP integration) into our client. Produce engineer onboarding playbooks and advanced-usage standards.
• Set the bar for the Skill Marketplace — Define Skill design conventions; personally deliver 5–10 reference-quality Skills as exemplars; raise team-wide Skill engineering quality through PR review.
• Prototype an AI-native engineering workflow — Reimagine the spec → design → implementation → review → testing → release → operations lifecycle around AI tools, producing a reference workflow APAC teams can adopt.
• Build internal AI application prototypes (employee-facing scenarios) — In OpenClaw, A2UI, role-bound AI assistants, and similar internal contexts, build small frontier prototypes that validate streaming UX, transparent agent steps, long-context memory, multi-agent collaboration, and other emerging patterns.
• Provide reference architecture code — When APAC teams face hard architectural choices in new AI scenarios, deliver runnable "this is how Silicon Valley does it" reference implementations — not documents, but working code.
• Cross-team craft propagation — One internal tech talk per month, one in-depth blog per quarter, and one onsite workshop in APAC per half year. Distill Silicon Valley AI application best practices into durable team assets.
• Architecture review participation — As the AI Team's anchor in the U.S., participate in our client's AI architecture review process and provide frontier perspective and taste-based feedback at the application layer.

Major Requirements

• Education: Top-tier CS / EE BS or above; MS preferred.
• 6+ years of software engineering experience, including at least 2 years focused on LLM applications.
• Senior AI application engineering experience: Has shipped AI applications from 0 → 1 in production (not demos). Must have at least one tour of duty as a core engineer at a top-tier Silicon Valley AI company or a leading AI product team — examples include Anthropic, OpenAI, Meta, and similar.
• Deep AI Coding tooling fluency: Claude Code, Cursor, Devin, or Replit Agent (at least one) is a daily-driver in your workflow, and you can articulate its engineering implementation. Strong understanding of the engineering tradeoffs in Skills, hooks, subagents, MCP, and long-context engineering.
• Agent application engineering depth: Solid grasp of ReAct, Plan-Execute, Reflection, Multi-Agent, and Orchestrator-Worker tradeoffs. Hands-on experience with LangGraph, AutoGen, CrewAI, OpenAI Swarm, or in-house frameworks.
• Strong full-stack engineering: Strong backend (Go / Python / TypeScript). Mid-level or above frontend (React / Next.js). Comfortable with end-to-end streaming rendering and interaction.
• Strong product sense and craft: Comfortable collaborating with PMs and designers; you have considered opinions and taste on AI application UX patterns (streaming, undo, context surfacing, agent-step progress, etc.).
• Public technical influence: A track record of public output — blog, talks, OSS contributions — sufficient to represent the team's craft externally.
• Self-direction and async collaboration: Capable of independently judging value priorities and driving prototype-to-dogfooding loops; effective at collaborating with APAC counterparts via documents, PRs, and asynchronous communication.