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 an 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 microservices.
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 deploy services on cloud platforms (Azure/AWS/GCP).
- Ensure reliability, observability, and performance of implementation-specific services.
- Troubleshoot production issues, analyze logs, and perform root-cause analysis.
Customer Delivery & Collaboration
- Work closely with Customer Success & Solutions teams to translate requirements into technical specifications.
- Own end-to-end technical implementation for enterprise accounts.
- Provide guidance on best practices, architecture choices, and scalable patterns.
Team Excellence
- Participate in code reviews and maintain high-quality coding standards.
- Document implementation workflows, integration steps, and troubleshooting playbooks.
- Work closely with the team and contribute to internal tooling and automation.
Required Qualifications
- 3–5 years of professional experience in Python development.
- Strong understanding of backend fundamentals, microservices, and distributed systems.
- Experience working with APIs, web frameworks (FastAPI, Flask, Django), and RESTful architectures.
- Hands-on experience with relational & NoSQL databases (PostgreSQL, MongoDB, or similar).
- Familiarity with cloud platforms (Azure, AWS, or GCP).
- Strong problem-solving, debugging, and communication skills.
- Ability to work cross-functionally with engineering, ML, and customer-facing teams.
Desired (Nice-to-Have)
- Experience with AI/ML/NLP pipelines, LLMs, or RAG-based applications.
- Good knowledge in Java, NLP or text processing or agentic implementation experience.
- Knowledge of Docker, Kubernetes, and container orchestration.
- Exposure to message queues (Kafka, RabbitMQ).
- Experience with CI/CD tools and automation frameworks.
- Prior startup or scale-up experience.
- Open-source contributions or technical writing experience.