Lead AI Engineer
Ecolab Inc.3 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect and deliver enterprise-grade GenAI systems using LLM APIs, agent orchestration frameworks, and embedding pipelines.
- Design autonomous and multi-agent workflows with context management, task delegation, tool calling, and distributed agent communication.
- Build RAG and vector-based solutions, reusable SDKs, templates, shared agent logic, and internal AI engineering accelerators.
- Optimize prompt strategies, retrieval layers, caching, latency, accuracy, reliability, and cost across production AI systems.
- Lead solution reviews, enforce prompt safety and governance, and align implementations with security protocols.
- Guide cross-functional engineering pods through technical direction, mentoring, design guidance, code reviews, and reusable engineering patterns.
- Collaborate with platform, product, architecture, and engineering leaders on scalable AI capabilities and enterprise integrations.
- Own the full software lifecycle, including design, development, deployment, support, observability, reliability improvement, and maintainability.
Requirements
- 6 to 8+ years of experience in software, AI, or ML engineering roles, including significant experience with production-grade GenAI or agentic AI applications.
- Proven experience leading the technical delivery of LLM-powered products or agent-based solutions.
- Strong Python and modern backend engineering experience building AI-enabled application services and APIs.
- Hands-on experience with Azure OpenAI, Azure AI Studio, Semantic Kernel, LangChain, AutoGen, or equivalent platforms and orchestration frameworks.
- Strong experience designing and implementing RAG and vector-based patterns using platforms such as Azure AI Search, Pinecone, Weaviate, or FAISS.
- Experience building and deploying cloud-native AI services with Azure Functions, Azure Container Apps, FastAPI, Docker, Azure DevOps, and GitHub or equivalent tools.
- Understanding of CI/CD, containerization, automated testing, and production deployment practices for AI systems.
- Experience with observability and operational tools such as Application Insights, OpenTelemetry, Azure Monitor, Datadog, or New Relic.
- Exposure to Model Context Protocol, agent-to-agent interaction patterns, or similar context-sharing and distributed-agent approaches.
- Ability to provide technical direction, mentor engineers, communicate complex decisions, and collaborate across technical and non-technical teams.
- Preferred experience with multi-step agentic workflows, Microsoft AI Foundry, Azure Machine Learning, Azure AI, Copilot Studio, enterprise integrations, AI governance, safety, evaluation, and cost-management tooling.
- Experience operating in a build-own-operate product environment with strong reliability, supportability, and continuous-improvement expectations.
Benefits
- Bangalore-based hybrid work arrangement.
Categories
About Ecolab Inc.
Ecolab Inc. builds and sells water treatment chemicals and equipment, hygiene and infection-prevention products, and on-site service and digital monitoring for industrial and institutional customers. A NYSE-listed public company founded in 1923 and headquartered in St. Paul, Minnesota, it serves food, healthcare, life sciences, hospitality, manufacturing, and energy markets worldwide; its portfolio includes Nalco Water and, in data centers, CoolIT liquid-cooling solutions.