Applied AI Engineer

Must have :- Python + Data Science/ML + GenAI/LLMs + Agentic AI + RAG + Azure/Azure OpenAI + Enterprise APIs/Integration + PostgreSQL/SQL + AI Evaluation/Observability + Production/MLOps experience, preferably within manufacturing/consumer goods/supply chain.

We are looking for an Applied AI Engineer who can design, develop, evaluate, and deploy production-ready AI/ML solutions for enterprise applications in a consumer goods/manufacturing environment.

Must-Have Skills:

• Strong Python development experience for AI/ML, data science, and applications.
• Strong Data Science & Machine Learning knowledge: data preparation, feature engineering, statistics, experimentation, model selection/validation, classification, regression, clustering, ranking, model evaluation, drift monitoring, and MLOps.
• Hands-on experience with PyTorch, TensorFlow, scikit-learn, pandas, and NumPy.
• Strong experience building Generative AI / LLM applications.
• Hands-on Agentic AI development: AI agents, tool/function calling, multi-step workflows, orchestration, state/memory, human-in-the-loop, approvals, retries, and guardrails.
• Strong experience with RAG, embeddings, semantic search, vector databases, and enterprise knowledge retrieval.
• Strong prompt engineering, context engineering, structured outputs, AI evaluation, observability, tracing, and debugging.
• Ability to evaluate AI solutions for accuracy, reliability, hallucination, latency, cost, safety, and business impact.
• Strong understanding of traditional ML vs. LLM-based solutions and when to use each.

Enterprise & Integration:

• Experience integrating AI with enterprise APIs, databases, messaging systems, and business applications.
• Strong REST API, SQL, relational database, PostgreSQL, and application data-model knowledge.
• Understanding of synchronoasynchronous integrations, event-driven architecture, messaging, caching, state management, microservices, and distributed systems.
• Experience securely connecting AI agents to enterprise systems using authentication, authorization, IAM, APIs, and controlled tool access.

Azure / Cloud:

• Hands-on experience deploying AI solutions in Microsoft Azure.
• Strong exposure to Azure OpenAI, Azure AI Services, API Management, Service Bus, Event Hubs, Azure Database for PostgreSQL, Entra ID, Key Vault, Azure Monitor, and Application Insights.
• Experience with containers, cloud-native applications, CI/CD, automated deployments, and production monitoring.
• Ability to move AI solutions from POC/experimentation to secure, scalable production.

AI Engineering:

• Experience with AI orchestration frameworks/SDKs and single-agent/multi-agent architectures.
• Understanding of deterministic vs. probabilistic systems.
• Experience implementing guardrails, validation, retries, approval workflows, human oversight, AI observability, and cost/token optimization.
• Knowledge of model latency, model selection, token usage, AI cost optimization, MLOps/LLMOps.

Industry Experience:

• Experience in consumer goods, manufacturing, supply chain, distribution, or similar industries.
• Ability to translate business/operational problems into practical AI solutions.
• Experience working with product, order, customer, manufacturing, supply-chain, and master data.
• Familiarity with ERP, MES, WMS, order management, or shop-floor systems.

Preferred:

• SAP / S4HANA / SAP BTP / SAP CPI / SAP MDG experience.
• AI/ML experience in manufacturing, product configuration, order management, forecasting, quality, or supply chain.
• Redis/distributed caching, vector search, AI evaluation/observability platforms.
• AI-assisted development tools such as OpenAI Codex, Claude Code, or GitHub Copilot.
• Experience taking AI solutions from POC → production → operational support.
• Strong English communication skills for documentation, technical discussions, and stakeholder interaction.