Lead Engineer

Lead AI Engineer

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 Ecolabs 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:

6+ 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