{"id":1191649,"url":"https://alion.io/job/nexaminds-lang-chain-deployment-ai-engineer-2","title":"Lang Chain Deployment AI Engineer","company":{"id":2681241,"name":"Nexaminds","domain":"nexaminds.ai","url":"https://alion.io/company/nexaminds","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["MX"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"IAM","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Milvus","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Reranking","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"Weaviate","optional":false},{"name":"Amazon CloudWatch","optional":true},{"name":"Amazon EKS","optional":true},{"name":"ArgoCD","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Azure AKS","optional":true},{"name":"Datadog","optional":true},{"name":"Function Calling","optional":true},{"name":"GitHub Actions","optional":true},{"name":"GitLab CI","optional":true},{"name":"Google GKE","optional":true},{"name":"Grafana","optional":true},{"name":"Hallucination","optional":true},{"name":"Helm","optional":true},{"name":"Jenkins","optional":true},{"name":"Least Privilege","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"Red Teaming","optional":true},{"name":"Terraform","optional":true},{"name":"Tool Use","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-08-21T19:33:51Z","employer_posted_date":"2026-08-27","last_verified_at":"2026-10-01T07:58:35Z","board_verified":true,"closed_at":null,"days_open":40,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":40},"description":"Unlock Your Future with Nexaminds!\nAt 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.\nJoin 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.\n*]:pointer-events-auto [content-visibility:auto] supports-[content-visibility:auto]:[contain-intrinsic-size:auto_100lvh] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]\" data-turn-id=\"request-WEB:2093ca9d-d6bb-4dac-9795-2b28cd5013d9-1\" data-testid=\"conversation-turn-4\" data-scroll-anchor=\"true\" data-turn=\"assistant\">This position is open exclusively to candidates who are currently residing in Mexico. Before applying, we encourage you to review our open positions and make sure the location requirements match your current location. Candidates who are not currently based in Mexico will not be contacted for this opportunity.\nNexaminds 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.\nThis 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.\nLocation: MEXICO (Remote)\nQualifications weare looking for:\nBachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.\nStrong professional software engineering experience with Python and/or JavaScript/TypeScript, including API development, asynchronous processing, testing, packaging, dependency management, and code review.\nHands-on experience building production-grade AI agents using LangChain and LangGraph, including chains/runnables, tools, structured outputs, stateful workflows, streaming, persistence, and error handling.\nExperience developing and deploying LLM-powered applications using commercial model APIs such as OpenAI, Anthropic, Google, or cloud-hosted equivalents, and/or open-source models.\nStrong understanding of Retrieval-Augmented Generation (RAG), including document ingestion, chunking, embeddings, vector search, metadata filtering, reranking, grounding, and citation patterns.\nExperience 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.\nExperience deploying production-grade AI applications using Docker and Kubernetes.\nExperience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP).\nExperience taking AI applications beyond POCs into production, including CI/CD, environment management, monitoring, troubleshooting, and operational support.\nHands-on experience with LangSmith or comparable LLM tracing, evaluation, and observability tools, including the ability to investigate quality, latency, cost, and tool/retrieval failures.\nFamiliarity with the Agent Development Life Cycle (ADLC) and production deployment of configurable AI agents.\nWorking knowledge of application security, including IAM, secrets management, encryption, API security, auditability, privacy, and secure software development practices.\nStrong customer-facing communication, technical writing, and consulting skills, with the ability to explain technical tradeoffs to both engineering and business stakeholders.\nAbility to work effectively in ambiguous environments and collaborate closely with AI architects, engineering teams, platform teams, security, data, and product stakeholders.\nNice to have:\nExperience with LangChain enterprise products, including LangSmith, Fleet, or Deep Agents.\nExperience designing or implementing multi-agent systems, supervisor patterns, long-running workflows, durable execution, event-driven integrations, or human approval workflows.\nExperience with cloud AI platforms such as Amazon Bedrock, Azure AI Foundry/Azure OpenAI, or Google Vertex AI.\nExperience with managed Kubernetes platforms such as EKS, AKS, or GKE.\nExperience with Infrastructure as Code and delivery tools such as Terraform, Helm, GitHub Actions, GitLab CI, Jenkins, or Argo CD.\nExperience with observability platforms such as OpenTelemetry, Datadog, Grafana, Prometheus, CloudWatch, Azure Monitor, or Google Cloud Operations.\nKnowledge of LLM evaluation, model and prompt versioning, red teaming, adversarial testing, hallucination analysis, retrieval evaluation, and human feedback programs.\nExperience working in regulated or data-sensitive environments.\nRelevant certifications in cloud, Kubernetes, security, data engineering, or AI/ML.\nWillingness to travel to customer locations when required.\nJob duties:\nTranslate approved LangChain and agentic AI architectures into maintainable, secure, scalable, and production-ready applications.\nBuild LLM-powered assistants, copilots, chatbots, document-processing solutions, decision-support tools, and automated workflows.\nDevelop deterministic and agentic workflows using LangGraph, including state management, routing, tool use, retries, checkpoints, memory, streaming, and failure recovery.\nDesign and implement RAG pipelines, including ingestion, chunking, embeddings, indexing, retrieval, reranking, grounding, citations, and access controls.\nIntegrate LLMs, embedding models, APIs, databases, search systems, vector stores, business applications, and custom tools through secure and maintainable interfaces.\nDeploy AI applications using Docker, Kubernetes, serverless, or managed cloud runtimes, supporting environment promotion, rollback, autoscaling, resiliency, and disaster recovery.\nImplement LangSmith tracing, evaluation, monitoring, dashboards, alerts, and feedback workflows to monitor model, tool, retrieval, latency, cost, and quality behavior.\nEstablish automated quality engineering and evaluation processes, including unit, integration, end-to-end, regression, adversarial, and load testing.\nBuild offline and online evaluation frameworks, golden datasets, quality thresholds, and release gates for prompts, models, retrieval systems, tools, and workflows.\nImplement 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.\nOptimize AI applications for response quality, latency, throughput, reliability, context utilization, caching, model selection, and token consumption.\nIntegrate AI solutions into CI/CD pipelines and establish reproducible deployment and release processes.\nCreate operational documentation, architecture updates, troubleshooting guides, runbooks, dashboards, alert thresholds, and incident procedures.\nPartner with AI architects, Nexaminds delivery leaders, and customer stakeholders to communicate progress, risks, dependencies, and technical tradeoffs.\nParticipate in design and code reviews, mentor engineers, and support knowledge transfer to customer engineering and operations teams.\nMonitor production systems, analyze feedback and failures, and continuously improve AI solution quality, reliability, performance, and cost.\nWhat you can expect from us\nHere 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.\nStock options \nRemote work options \nFlexible working hours \nBenefits above the law\nBut it's not just about the work; it's about the people too. You'll be collaborating with some seriously awesome IT pros.\nYou'll have access to mentorship and tons of opportunities to learn and level up.\nReady to embark on this journey with us? If you're feeling the excitement, go ahead and apply!","description_format":"text","description_chars":8684,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Stock options"],"hiring_locations":[{"name":"Mexico","iso":"MX","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Professional Services","AI Consulting & Integration"],"lifecycle":[{"event":"open","at":"2026-09-24T16:59:15Z"}],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":1,"p_active":0.537,"p_room":0.45,"age_days":40,"expected_fill_days":26,"reasons":["conf:7","velocity","win:tail"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nexaminds-lang-chain-deployment-ai-engineer-2","json_url":"https://alion.io/job/nexaminds-lang-chain-deployment-ai-engineer-2.json","meta":{"generated_at":"2026-10-01T18:42:28Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":991,"day_limit":5000,"remaining_today":4009,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}