Lang Chain Deployment AI Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Convert approved LangChain and agentic AI architectures into maintainable, secure, scalable, and production-ready applications.

• Create LLM-powered assistants, copilots, chatbots, document-processing solutions, decision-support tools, and automated workflows.

• Develop deterministic and agentic workflows utilizing LangGraph, encompassing state management, routing, tool usage, retries, checkpoints, memory, streaming, and failure recovery.

• Design and execute RAG pipelines, which include ingestion, chunking, embeddings, indexing, retrieval, reranking, grounding, citations, and access controls.

• Integrate LLMs, embedding models, APIs, databases, search systems, vector stores, business applications, and custom tools.

• Deploy AI applications through Docker, Kubernetes, serverless, or managed cloud environments.

• Implement LangSmith tracing, evaluation, monitoring, dashboards, alerts, and feedback workflows.

• Establish automated quality engineering and evaluation processes.

• Create offline and online evaluation frameworks, golden datasets, quality thresholds, and release gates.

• Enforce AI security and responsible AI practices.

• Optimize AI applications for response quality, latency, throughput, reliability, context utilization, caching, model selection, and token consumption.

• Integrate AI solutions into CI/CD pipelines.

• Develop operational documentation, architecture updates, troubleshooting guides, runbooks, dashboards, alert thresholds, and incident processes.

• Collaborate with AI architects, Nexaminds delivery leaders, and customer stakeholders.

• Engage in design and code reviews, mentor engineers, and support knowledge transfer.

• Monitor production systems, analyze feedback and failures, and continuously enhance the quality, reliability, performance, and cost-effectiveness of AI solutions.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent hands-on experience.

• Significant professional software engineering experience with Python and/or JavaScript/TypeScript, focusing on API development, asynchronous processing, testing, packaging, dependency management, and code review.

• Practical experience in constructing production-grade AI agents using LangChain and LangGraph, including chains/runnables, tools, structured outputs, stateful workflows, streaming, persistence, and error handling.

• Experience in developing and deploying LLM-powered applications via commercial model APIs or open-source models.

• Strong comprehension of Retrieval-Augmented Generation (RAG), covering document ingestion, chunking, embeddings, vector search, metadata filtering, reranking, grounding, and citation patterns.

• Familiarity with at least one vector database or search platform.

• Experience in deploying production-grade AI applications utilizing Docker and Kubernetes.

• Proficiency with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP).

• Experience in advancing AI applications from proof of concepts to production, including CI/CD, environment management, monitoring, troubleshooting, and operational support.

• Hands-on experience with LangSmith or similar LLM tracing, evaluation, and observability tools.

• Understanding of the Agent Development Life Cycle (ADLC) and the production deployment of configurable AI agents.

• Working knowledge of application security, including IAM, secrets management, encryption, API security, auditability, privacy, and secure software development practices.

• Excellent customer-facing communication, technical writing, and consulting skills.

• Ability to work collaboratively with AI architects, engineering teams, platform teams, security, data, and product stakeholders.

🏝️ Benefits

• Stock options.

• Remote work opportunities.

• Flexible working hours.

• Enhanced benefits beyond legal requirements.

• Mentorship and opportunities for learning and professional growth.

• A collaborative environment with IT professionals.