- Architect and implement scalable machine learning models that address specific business challenges and improve process automation for enterprise clients.

- Collaborate with engineering teams to integrate AI-driven features into existing product ecosystems, ensuring seamless performance and reliability.

- Optimize data pipelines and model training processes to improve the accuracy and efficiency of predictive analytics and decision-support systems.

- Conduct rigorous testing and validation of AI models to ensure they meet the highest standards of quality, security, and ethical compliance.

- Mentor junior team members and contribute to the technical roadmap by staying updated on emerging trends in artificial intelligence and machine learning.

Requirements :

- Strong enterprise software engineering experience with Java, Python, C#, or similar programming languages.

- Experience designing enterprise-scale solutions across distributed systems, APIs, microservices, integrations, and cloud-enabled platforms.

- Strong understanding of data architecture, data flows, data models, data products, analytics platforms, and enterprise data governance.

- Nice to have : exposure to platforms such as SAP S/4HANA, Salesforce, Informatica, or comparable enterprise systems.

- Ability to design and govern integration patterns across packaged platforms, custom applications, and enterprise data platforms.

- Working knowledge of AI/LLM agents, Copilot-style enablement, intelligent automation, or practical AI use cases in enterprise environments.

- Strong debugging, performance optimization, testing, deployment, and technical documentation skills.

- Ability to communicate complex technical decisions clearly to engineering teams, architects, product leaders, and business stakeholders.

- Proven ability to influence across teams, build consensus, and drive architecture alignment without relying on direct authority.