Lang Chain Deployment AI Engineer

Nexaminds; United States; Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Stock options

Remote work options

Flexible working hours

Benefits above the law

Job summary

Nexaminds is seeking a LangChain Deployment AI Engineer to deliver production-grade generative AI solutions. The role focuses on turning approved architectures into secure, scalable systems, deploying LLM-powered applications, and building agentic workflows with strong quality and security.

You’ll work closely with AI architects, engineering teams, and customers. The position emphasizes production readiness, observability, and operational excellence, with remote work options and a collaborative,

Qualifications

• Bachelor's degree or equivalent practical experience in CS/Engineering/IS.
• Strong software engineering experience with Python and/or JavaScript/TypeScript, including API development and testing.
• Hands-on production-grade AI agent development with LangChain and LangGraph.
• Experience deploying LLM-powered applications via cloud providers and CI/CD.

Responsibilities

• Translate LangChain and agentic AI architectures into production-ready applications.
• Build LLM-powered assistants, copilots, chatbots, and automation workflows.
• Develop deterministic workflows with LangGraph, including state management and error handling.
• Design and implement RAG pipelines with ingestion, embeddings, indexing, and grounding.
• Deploy using Docker, Kubernetes, and cloud runtimes with scalable environments.
• Implement LangSmith tracing, monitoring, and quality gates for deployments.
• Create operational docs, runbooks, and support production incident response.
• Collaborate with AI architects, delivery leads, and customer teams.

Skills

Python

JavaScript/TypeScript

LangChain

LangGraph

RAG

LLM applications

Cloud deployment

CI/CD

LangSmith

ADLC

IAM & security

Collaboration

Education

Bachelor's degree in CS/Engineering/IS or equivalent

Tools

Docker

Kubernetes

AWS/Azure/GCP

GitHub Actions

Terraform

OpenTelemetry

Datadog

Grafana

Job description

Unlock Your Future with Nexaminds!

At Nexaminds, we’re on a mission to redefine industries with AI. We’re passionate about the limitless potential of artificial intelligence to transform businesses, streamline processes, and drive growth.

Join us on our visionary journey. We’re leading the way in AI solutions, and we’re committed to innovation, collaboration, and ethical practices. Become a part of our team and shape the future powered by intelligent machines. If you’re driven by ambition, success, fun, and learning, Nexaminds is where you belong.

Eligibility Notice This position is only open to candidates who are Mexican citizens currently residing in Mexico. Applications from candidates who do not meet this legal and operational requirement will not be considered. We appreciate your interest and encourage you to apply to roles that match your location.

Nexaminds is looking for a LangChain Deployment AI Engineer to join our team and deliver production-grade generative and agentic AI solutions. The ideal candidate has strong hands‑on experience with Python and/or JavaScript/TypeScript, LangChain, LangGraph, RAG, LLM applications, and cloud deployment , with proven experience taking AI solutions beyond proof‑of‑concept into reliable production environments.

This role focuses on translating approved AI architectures into secure, scalable, observable, and maintainable production systems , while working closely with AI architects, engineering teams, and customer stakeholders. The successful candidate will build and deploy LLM‑powered applications, agentic workflows, RAG solutions, evaluation pipelines, and integrations, while ensuring strong quality, security, performance, and operational readiness.

Location: MEXICO (Remote

Qualifications we are looking for:

• 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 such as OpenAI, Anthropic, Google, or cloud‑hosted equivalents, and/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 working with at least one vector database or search platform , such as Pinecone, Weaviate, Milvus, pgvector/PostgreSQL, Elasticsearch/OpenSearch, Redis, Azure AI Search, or equivalent.
• 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 , including the ability to investigate quality, latency, cost, and tool/retrieval failures.
• 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, with the ability to explain technical tradeoffs to both engineering and business stakeholders.
• Ability to work effectively in ambiguous environments and collaborate closely with AI architects, engineering teams, platform teams, security, data, and product stakeholders.

Nice to have:

• Experience with LangChain enterprise products , including LangSmith, Fleet, or Deep Agents.
• Experience designing or implementing multi‑agent systems , supervisor patterns, long‑running workflows, durable execution, event‑driven integrations, or human approval workflows.
• Experience with cloud AI platforms such as Amazon Bedrock, Azure AI Foundry/Azure OpenAI, or Google Vertex AI.
• Experience with managed Kubernetes platforms such as EKS, AKS, or GKE.
• Experience with Infrastructure as Code and delivery tools such as Terraform, Helm, GitHub Actions, GitLab CI, Jenkins, or Argo CD.
• Experience with observability platforms such as OpenTelemetry, Datadog, Grafana, Prometheus, CloudWatch, Azure Monitor, or Google Cloud Operations.
• Knowledge of LLM evaluation, model and prompt versioning, red teaming, adversarial testing, hallucination analysis, retrieval evaluation, and human feedback programs.
• Experience working in regulated or data‑sensitive environments.
• Relevant certifications in cloud, Kubernetes, security, data engineering, or AI/ML.
• Willingness to travel to customer locations when required.

Job duties:

• Translate approved LangChain and agentic AI architectures into maintainable, secure, scalable, and 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 through secure and maintainable interfaces.
• Deploy AI applications using Docker, Kubernetes, serverless, or managed cloud runtimes , supporting environment promotion, rollback, autoscaling, resiliency, and disaster recovery.
• Implement LangSmith tracing, evaluation, monitoring, dashboards, alerts, and feedback workflows to monitor model, tool, retrieval, latency, cost, and quality behavior.
• Establish automated quality engineering and evaluation processes , including unit, integration, end‑to‑end, regression, adversarial, and load testing.
• Build offline and online evaluation frameworks , golden datasets, quality thresholds, and release gates for prompts, models, retrieval systems, tools, and workflows.
• Implement AI security and responsible AI practices, including least privilege, IAM, encryption, secrets management, audit logging, PII safeguards, prompt‑injection defenses, output controls, and human escalation.
• Optimize AI applications for response quality, latency, throughput, reliability, context utilization, caching, model selection, and token consumption.
• Integrate AI solutions into CI/CD pipelines and establish reproducible deployment and release processes.
• Create operational documentation, architecture updates, troubleshooting guides, runbooks, dashboards, alert thresholds, and incident procedures.
• Partner with AI architects, Nexaminds delivery leaders, and customer stakeholders to communicate progress, risks, dependencies, and technical tradeoffs.
• Participate in design and code reviews , mentor engineers, and support knowledge transfer to customer engineering and operations teams.
• Monitor production systems, analyze feedback and failures, and continuously improve AI solution quality, reliability, performance, and cost.

What you can expect from us

Here at Nexaminds, we’re not your typical workplace. We’re all about creating a friendly and trusting environment where you can thrive. Why does this matter? Well, trust and openness lead to better quality, innovation, commitment to getting the job done, efficiency, and cost‑effectiveness.

• Stock options
• Remote work options
• Flexible working hours
• Benefits above the law
• But it’s not just about the work; it’s about the people too. You’ll be collaborating with some seriously awesome IT pros.
• You’ll have access to mentorship and tons of opportunities to learn and level up.