11 hours ago
Remote, Americas or Mexico City, MexicoSenior
Responsibilities
- Design, build, deploy, and operate production AI features such as RAG pipelines, LLM-driven recommendations, conversational agents, and agentic workflow automation.
- Build shared AI platform capabilities including retrieval infrastructure, evaluation frameworks, model monitoring, guardrails, and observability.
- Develop LLM applications and integrations for marketing platforms, BI tools, and customer-facing product surfaces.
- Evaluate model and feature quality using structured evaluation frameworks and iterate on prompts, retrieval strategies, and model selection.
- Use AI-assisted software development tools such as Claude Code as part of daily development for AI and non-AI code.
- Coordinate with the Personalization team to align GenAI features with existing ML personalization signals.
- Document system designs, evaluation results, operational lessons, architectural decisions, and RFCs.
- Own system observability for latency, cost, quality drift, and error rates, and participate in on-call and production incident response.
Requirements
- 8+ years of software engineering experience.
- Strong Python proficiency and experience building and operating production LLM applications.
- Hands-on experience with RAG and retrieval systems, LLM evaluation, agentic frameworks, or LLM-based workflow automation.
- Understanding of prompt engineering, context-window management, and LLM output-quality tradeoffs.
- Familiarity with vector databases, embedding models, or semantic search.
- Daily hands-on experience shipping production code with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor.
- Full-stack awareness and willingness to contribute across application layers rather than working exclusively in one layer.
- Experience owning features end-to-end from specification through deployment and operations.
- Preferred experience with MLOps tooling or model deployment pipelines, developer tooling, golden-path standards, SDLC improvements, e-commerce or high-traffic consumer applications, distributed teams, and technical documentation.
Benefits
- Full-time position intended as a long-term engagement.
- Participation in several interview rounds for selected candidates.
- Background check required during onboarding.
Tech Stack
Categories
About Lifted
Lifted builds a global platform for enterprises to source, contract, manage, and pay contingent workers with embedded compliance. The software integrates into existing contingent workforce ecosystems and supports multiple worker types across countries. Lifted operates as an Upwork company, serving organizations that need to centralize contingent programs and streamline cross‑border payments and documentation.