Overview

We are looking for an experienced Lead AI Engineer to lead the design, development, and deployment of enterprise-grade Agentic AI solutions, with a strong focus on SAP Joule integration.

The ideal candidate will have hands-on experience building intelligent AI agents capable of reasoning, planning, decision-making, tool execution, and workflow automation, along with strong expertise in LLMs, RAG, multi-agent architectures, and modern AI frameworks.

This role combines deep technical expertise with technical leadership, architecture ownership, team mentoring, and stakeholder management.

Key Responsibilities

• Lead the architecture, development, and deployment of Agentic AI systems capable of autonomous reasoning, planning, decision-making, and execution.
• Design and implement scalable AI solutions integrating SAP Joule with enterprise applications and business workflows.
• Develop and orchestrate single-agent and multi-agent AI systems using frameworks such as LangChain, AutoGen, CrewAI, or equivalent technologies.
• Design robust LLM orchestration, tool-calling, agent memory, workflow execution, and agent-to-agent communication patterns.
• Build and optimize RAG pipelines using appropriate embedding models, retrieval strategies, reranking, and vector databases.
• Integrate LLMs from providers such as OpenAI, Anthropic, and open-source models into enterprise AI applications.
• Translate complex business requirements into scalable and production-ready AI/ML solutions.
• Establish best practices for prompt engineering, model evaluation, AI observability, guardrails, and responsible AI.
• Lead the deployment and optimization of AI applications across AWS, Azure, or GCP environments.
• Work closely with product, engineering, SAP, and business stakeholders to identify and deliver AI-driven automation opportunities.
• Mentor and provide technical guidance to AI engineers and developers.
• Review architecture, code, performance, scalability, and security of AI solutions.
• Ensure AI systems meet enterprise requirements for security, compliance, reliability, scalability, and data privacy.
• Monitor production AI systems and optimize latency, cost, model performance, and reliability.

Required Skills

• 7–10+ years of experience in AI/ML Engineering, Generative AI, Data Science, or a closely related field.
• Hands-on SAP Joule AI experience – Mandatory.
• Strong practical experience in Agentic AI architecture and development.
• Experience with one or more Agentic AI frameworks:
  • LangChain
  • LangGraph
  • AutoGen
  • CrewAI
  • Semantic Kernel
  • Equivalent agent orchestration frameworks
• Strong programming skills in Python.
• Hands-on experience with LLMs / Generative AI, including OpenAI, Anthropic, or open-source models.
• Strong understanding of:
  • Prompt Engineering
  • RAG
  • Embeddings
  • Vector Databases
  • Tool Calling / Function Calling
  • AI Agents
  • Agent Memory
  • Multi-Agent Systems
  • LLM Orchestration
• Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus, Chroma, or equivalent.
• Experience deploying AI solutions on AWS, Azure, or GCP.
• Strong understanding of AI application architecture, APIs, microservices, and integration patterns.
• Experience with production deployment, monitoring, performance optimization, and troubleshooting of AI systems.
• Strong technical leadership and stakeholder management capabilities.
• SAP / Enterprise AI Experience

Preferred Skills

• Experience leading AI transformation or Generative AI initiatives.
• Experience implementing enterprise AI governance, security, and compliance.
• Knowledge of AI evaluation frameworks and LLM observability platforms.
• Experience with CI/CD and MLOps/LLMOps practices.
• Experience integrating AI agents with enterprise applications and workflow platforms.
• Exposure to MCP (Model Context Protocol) and modern AI tool-integration patterns.
• Experience managing or mentoring a team of AI/ML engineers.
• Strong understanding of enterprise architecture and solution design.

Leadership Expectations

The successful candidate will be expected to:

• Own the technical architecture of Agentic AI initiatives.
• Guide engineering teams on AI architecture and implementation.
• Conduct technical reviews and establish development standards.
• Collaborate directly with senior stakeholders.
• Identify opportunities for AI-driven automation and process improvement.
• Drive solutions from POC/prototype through production deployment.
• Ensure solutions are scalable, secure, maintainable, and business-aligned.