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$ cat jobs/lead-software-engineer-al-ml-customer-engineer-neuron7-cf23dbe9e036.json

Lead Software Engineer - AL/ML (Customer Engineer)

Neuron7·Worldwide·Bengaluru·senior
pythonllmnlpsalesforcesap
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About Us: Neuron7.ai is a fast-growing AI-first SaaS company — Series B funded and trusted by top Fortune 1000 brands — that transforms service resolution with intelligence. Our Smart Resolution Hub delivers predictive, guided troubleshooting across high-tech, medical, and industrial equipment environments. With 300% ARR growth and deep integrations with Salesforce, ServiceNow, Microsoft, and SAP, Neuron7 is scaling rapidly in India and worldwide. We operate with: Integrity and doing business the right way Continuous innovation in AI and service intelligence Customer obsession with real, measurable impact Collective intelligence through collaboration and knowledge sharing Role Overview As a Lead Software Engineer (Implementation Engineer), you will work at the intersection of engineering, AI, and customer delivery. You’ll build, integrate, and deploy Python-based backend solutions that power Neuron7’s AI-driven resolution platform. This role involves implementing customer-specific workflows, connecting enterprise systems, optimizing data pipelines, and enabling scalable LLM/NLP-powered features in production. You will partner closely with Customer Success, ML, Backend Engineering, and PM teams to ensure smooth onboarding, robust integrations, and high-quality deployments for enterprise clients. Key Responsibilities Python Development & Integrations Develop and maintain Python-based services, APIs, and integration layers for customer implementations. Build data ingestion, transformation, and validation pipelines to support AI/ML workflows. Implement customer-specific logic, connectors, and automations using Python micrservices. AI/ML & NLP (Implementation Focus) Integrate internal ML pipelines, LLM components, and retrieval systems into customer environments. Work with RAG pipelines, embedding workflows, or NLP modules as needed for solution deployment. Collaborate with ML Engineers to productionize models and optimize performance. Deployment & System Reliability Con

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