Neuron7. ai
SaaS
CustomerImplementationEngineer(Python|AI/ML)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Customer Implementation Engineer ( Python | AI/ML) at Neuron7. ai. Skills: Python, AI/ML, Backend Development, Cloud Deployment. Develop Python-based services. Maintain Python-based services”
Industry & Context.
Problem-solving; Debugging; Troubleshoot production issues; Root-cause analysis
What They're Looking For.
Must Have
3+ years of professional experience, 2+ years of Python coding experience, Backend fundamentals understanding, Microservices understanding, Distributed systems understanding, Experience with APIs, Experience with web frameworks, Experience with RESTful architectures, Hands-on experience with relational databases, Hands-on experience with NoSQL databases, Familiarity with cloud platforms, Problem-solving skills, Debugging skills, Communication skills, Ability to work cross-functionally, Scope work, Sequence delivery, Remove blockers early, Make trade-offs, Adjust plans, Contribute in code, Codify working patterns, Keep teams moving
Nice to Have
AI/ML/NLP pipelines experience, LLM experience, RAG-based applications experience, Java knowledge, NLP knowledge, Text processing knowledge, Agentic implementation experience, Docker knowledge, Kubernetes knowledge, Message queues knowledge, CI/CD tools experience, Automation frameworks experience, Startup experience, Scale-up experience, Open-source contributions experience, Technical writing experience
What You'll Do.
Develop Python-based services
Maintain Python-based services
Develop integration layers
Maintain integration layers
Build data ingestion pipelines
Build data transformation pipelines
Build data validation pipelines
Implement customer-specific logic
Implement automations
Integrate internal ML pipelines
Integrate LLM components
Integrate retrieval systems
Work with RAG pipelines
Work with embedding workflows
Work with NLP modules
Optimize model performance
Ensure service reliability
Ensure service observability
Ensure service performance
Troubleshoot production issues
Perform root-cause analysis
Translate requirements
Own technical implementation
Provide guidance on best practices
Provide guidance on architecture choices
Provide guidance on scalable patterns
Participate in code reviews
Maintain coding standards
Document implementation workflows
Document integration steps
Document troubleshooting playbooks
Mentor junior team members
Contribute to internal tooling
Contribute to internal automation
How You'll Work.
Team & Collaboration
Customer Success teams; Solutions teams; ML teams; Backend Engineering teams; PM teams; Cross-functionally
Communication Scope
Problem-solving; Debugging; Communication
Process & Methodology
Scope work, Sequence delivery, Remove blockers, Make trade-offs, Adjust plans
Full Job Description
## Description 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 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 Configure and
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