about the company.
A high-growth global e-commerce and technology leader that is seeking visionary AI talent to shape the future of smart ecosystem services. Driven by a massive global footprint and an unmatched data repository, we empower top engineers, researchers, and data scientists to build cutting-edge machine learning models that impact millions of users daily.
about the team.
a diverse, highly collaborative group of machine learning engineers, data scientists, and researchers dedicated to transforming massive, real-world data into intelligent, high-impact user experiences. Operating within a global tech powerhouse, our team combines the agile, experimental mindset of a startup with the computing resources and data infrastructure of a worldwide leader.
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about the job.
- Platform Architecture: Design and implement a centralized coding harness that integrates generative AI with internal developer systems (e.g., version control, code search, documentation, ticketing, and deployment pipelines).
- Intelligent Workflows: Build and optimize RAG pipelines over complex codebases and technical documentation to deliver accurate, context-aware code suggestions, reviews, and technical Q&A.
- Agentic Systems: Develop autonomous coding agents capable of performing complex tasks such as refactoring, bug fixing, test generation, and automated pull request reviews, operating securely within existing access-control frameworks.
- Efficiency & Cost Management: Engineer mechanisms for model routing, prompt caching, request throttling, and usage monitoring to ensure sustainable inference costs at an enterprise scale.
- Security & Governance: Enforce comprehensive security standards, including automated secret redaction, granular access scoping, comprehensive audit logging, and policy-as-code guardrails.
- Developer Surface Integration: Embed the harness into daily developer touchpoints—including IDE extensions, CLI tools, and PR bot workflows—to ensure seamless adoption.
- Performance Engineering: Develop benchmarking tools to evaluate accuracy, latency, and developer satisfaction, driving continuous iteration of the platform.
- Research & Innovation: Stay at the forefront of AI engineering by applying cutting-edge techniques such as speculative decoding, specialized tool-use agents, and advanced context compression.
skills and experience required.
- 3+ years of professional experience in software engineering, with a strong focus on LLM application development, platform engineering, or developer tooling.
- Proven expertise in building production-grade AI applications using prompt engineering, RAG, function calling, and agentic workflows.
- Strong proficiency in Python or Go, with a track record of building and scaling backend services and APIs.
- Experience integrating with developer ecosystem tools (Git APIs, IDE extension frameworks, CI/CD pipelines).
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Hands-on experience with LLM frameworks (e.g., LangChain, LlamaIndex, vLLM) and vector search/retrieval systems.
- Experience in inference cost optimization and model routing strategies.
- Knowledge of agentic coding protocols (e.g., Model Context Protocol, function-calling patterns).
- Experience developing IDE integrations (e.g., VS Code extension API, Language Server Protocol).
- Familiarity with observability tools for LLMs (e.g., Langfuse, tracing, prompt regression testing).
- Experience with Kubernetes and cloud-native deployment patterns.
