Lang Chain Deployment Engineer

🔥 13 minutes ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 15%

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Nexaminds

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2023

🤖 Artificial Intelligence

💼 Consulting

🤝 B2B

Artificial Intelligence • Consulting • B2B

Nexaminds is an AI consulting and technology services company that helps businesses leverage artificial intelligence and machine learning to increase efficiency, reduce costs, and unlock new revenue streams. The firm offers AI/ML development, data engineering, application modernization, cloud transformation, agile development, and site reliability engineering (SRE) services. Nexaminds positions itself as a B2B partner, with case studies in personalized retail/subscription platforms and logistics/transportation modernization where it applies AI to improve engineering practices, QA, and operational efficiency.

📋 Description

• Translate approved LangChain and agentic AI architectures into maintainable, secure, scalable, production-ready applications • Build LLM-powered assistants, copilots, chatbots, document-processing solutions, decision-support tools, and automated workflows • Develop deterministic and agentic workflows using LangGraph, including state management, routing, tool use, retries, checkpoints, memory, streaming, and failure recovery • Design and implement RAG pipelines, including 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 using Docker, Kubernetes, serverless, or managed cloud runtimes • Implement LangSmith tracing, evaluation, monitoring, dashboards, alerts, and feedback workflows • Establish automated quality engineering and evaluation processes • Build offline and online evaluation frameworks, golden datasets, quality thresholds, and release gates • Implement 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 • Create operational documentation, architecture updates, troubleshooting guides, runbooks, dashboards, alert thresholds, and incident procedures • Partner with AI architects, Nexaminds delivery leaders, and customer stakeholders • Participate in design and code reviews, mentor engineers, and support knowledge transfer • Monitor production systems, analyze feedback and failures, and continuously improve AI solution quality, reliability, performance, and cost

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience • Strong professional software engineering experience with Python and/or JavaScript/TypeScript, including API development, asynchronous processing, testing, packaging, dependency management, and code review • Hands-on experience building production-grade AI agents using LangChain and LangGraph, including chains/runnables, tools, structured outputs, stateful workflows, streaming, persistence, and error handling • Experience developing and deploying LLM-powered applications using commercial model APIs or open-source models • Strong understanding of Retrieval-Augmented Generation (RAG), including document ingestion, chunking, embeddings, vector search, metadata filtering, reranking, grounding, and citation patterns • Experience with at least one vector database or search platform • Experience deploying production-grade AI applications using Docker and Kubernetes • Experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP) • Experience taking AI applications beyond POCs into production, including CI/CD, environment management, monitoring, troubleshooting, and operational support • Hands-on experience with LangSmith or comparable LLM tracing, evaluation, and observability tools • Familiarity with the Agent Development Life Cycle (ADLC) and 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 • Strong customer-facing communication, technical writing, and consulting skills • Ability to work effectively in ambiguous environments and collaborate with AI architects, engineering, platform, security, data, and product stakeholders

🏖️ Benefits

• Stock options • Remote work options • Flexible working hours • Benefits above the law • Mentorship and opportunities to learn and develop professionally • Collaboration with experienced IT professionals

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