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Design and build Python-based integrations, data pipelines, APIs, and AI-enabled workflows; deploy and maintain LLM/NLP/RAG capabilities in cloud environments; troubleshoot production issues; lead customer-facing implementations and mentor engineers to deliver scalable, reliable solutions.

Lead implementation of Python-based backend integrations and data pipelines to deploy LLM/NLP/RAG solutions for enterprise clients. Configure cloud deployments, ensure reliability and observability, troubleshoot production issues, and collaborate with Customer Success, ML, and engineering teams. Mentor juniors and document implementation playbooks.

Design, implement, and manage CI/CD pipelines and cloud infrastructure (AWS/Azure/GCP); automate provisioning with Terraform/Ansible; containerize apps with Docker/Kubernetes; monitor performance (Prometheus/Grafana/ELK); ensure security/compliance; troubleshoot availability issues; mentor junior engineers and document processes.

The role involves guiding the implementation and optimization of AI solutions for enterprise clients, focusing on customer onboarding, technical deployments, and service transformation initiatives.

The Product Management Apprentice supports product teams in building AI-powered products by assisting in documenting requirements, analyzing use cases, and collaborating across teams, offering hands-on training for early-career talent.

Lead and manage CI/CD pipelines, collaborate with teams on deployment processes, monitor system performance, automate infrastructure, and mentor junior engineers.

The Product Manager will lead the strategy and execution of agent product experiences, collaborating with teams to enhance AI diagnostics and optimize service workflows.

The Release Manager will oversee the complete release lifecycle, emphasizing QA processes, CI/CD pipeline optimization, and effective communication with stakeholders to ensure high-quality software releases.

Implement and deploy Python-based backend services and integrations for enterprise customers, build data pipelines for AI/ML workflows, integrate LLM/NLP and RAG components, ensure reliable cloud deployments, troubleshoot production issues, and collaborate with Customer Success, ML, and engineering teams to deliver scalable, productionized solutions.

The Solution Architect at Neuron7.ai will design AI-powered enterprise solutions, optimize business processes, engage customers, and lead architectural discussions to transform operations through intelligent automation.