Senior AI Engineer (Enterprise GenAI | SAP Environment)

PulseRise Technologies

4d • Remote

About The Position

We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI and Generative AI solutions. As part of a Business AI program, the team is building intelligent agents to streamline core enterprise processes and boost productivity. The goal is to free services professionals from repetitive tasks and accelerate time to value for customers. This role combines strong software engineering fundamentals with hands-on experience deploying LLM-powered systems into secure, production environments. You will drive initiatives from proof-of-concept through scalable enterprise deployment.

Requirements

• 5+ years of professional software engineering experience
• Strong Python expertise (mandatory)
• Experience with Node.js or Java (at least one additional language)
• Backend framework experience (FastAPI, Flask, or Django)
• Microservices architecture experience
• Docker and Kubernetes experience
• Experience with GitHub Actions, MLFlow, or similar orchestration tools
• Hands-on ETL, API integration, and model deployment experience
• Experience implementing CI/CD and MLOps in cloud environments
• Knowledge of distributed systems and big data platforms
• Experience working in Agile frameworks (Scrum, Kanban)
• Fluent English and strong problem-solving mindset

Nice To Haves

• Experience with multi-agent or GenAI frameworks (LangChain, CrewAI)
• Familiarity with SAP AI Core and SAP BTP
• Experience with Jira (Scrum, SAFe)

Responsibilities

• Design, develop, and deploy enterprise AI and GenAI services
• Guide solutions from PoC to secure production rollout
• Build and integrate multi-agent AI systems and LLM-based products
• Work with SAP data products and underlying data architectures
• Manage ingestion, transformation, caching, and indexing workflows
• Support distributed systems and big data processing environments
• Implement CI/CD pipelines and MLOps best practices
• Automate model training, validation, testing, and deployment
• Work with Azure ML, Databricks, or AWS environments
• Implement secure API design, secrets management, and access control
• Contribute to security concept design
• Ensure observability, reliability, and compliance in AI deployments
• Collaborate with AI Product Owners, Data Scientists, and stakeholders
• Create architecture diagrams, ADRs, and technical documentation
• Ensure high-quality, well-documented codebases

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed