As a Lead AI Engineer, you will architect and deliver enterprise-grade AI solutions, with a strong emphasis on GenAI, agent-based systems, and LLM orchestration. You will own the technical roadmap, guide engineering best practices, and serve as a thought leader in implementing scalable, secure, and efficient AI workflows. You will drive innovation, elevate the engineering bar, and play a pivotal role in shaping Ecolab’s applied AI capabilities.
Core Responsibilities
• Own end-to-end technical design and delivery of GenAI/agentic systems for internal or external applications
• Architect multi-agent workflows using tools like LangChain, A2A protocols, and custom orchestration frameworks
• Guide the design and tuning of prompt architectures, context strategies (e.g., with MCP), and hybrid RAG pipelines
• Integrate AI services into enterprise platforms such as Azure Foundry, Databricks, and core business systems
• Lead engineering pods, mentor engineers across levels, and drive technical alignment across product and platform teams
• Push the boundaries of performance, latency, and accuracy through research-backed optimization
• Define reusable templates, shared components, and internal GenAI SDKs
• Enforce standards around ethical AI use, context control, prompt security, and hallucination mitigation
Required Skills:
• 7+ years of experience in AI/ML/GenAI solutioning, with 3+ years in technical leadership
• Deep proficiency in Python 3 with strong command over openai, pydantic, transformers, faiss, and langchain
• Demonstrated experience in deploying scalable GenAI solutions with cloud-native design
• Strong working knowledge of Azure cloud services, GitHub workflows, and CI/CD best practices
• Experience in vector store optimization, token-level control, and prompt performance management.
Nice-to-have skills:
• Hands-on leadership in projects involving MCP, A2A orchestration, or custom agentic services
• Contributor to open-source GenAI tooling or frameworks
• Familiarity with prompt observability and compliance tooling
• Experience in conducting code reviews, architecture walkthroughs, and internal capability building
• Thought leadership via internal brown-bags, hackathons, or community talks.
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