Lead AI Engineer
At a glance
Senior AI Engineering role at Ecolab. Bangalore · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Set the technical direction and governance rules for GenAI systems built for enterprise use
- Design LLM applications with agent workflows and vector retrieval, balancing security, speed and reuse
- Turn business scenarios into detailed technical plans with enterprise and platform architects
- Build reusable SDKs, prompt libraries and orchestration templates to speed up delivery
- Connect backend services to front-end applications and support scalable cloud-native deployments
What you bring
- Deep experience delivering production systems with LLMs, embedding pipelines and agent workflows
- Strong Azure cloud and Azure SQL skills, including API design, tuning and performance optimization
- Experience with enterprise-scale work, microservices and micro front-end architecture
- Knowledge of GenAI prompt tuning, vector search, context handling, model safety and observability
Who this fits
This senior technical leadership role suits someone who can shape architecture while staying hands-on with production AI systems. You’ll work across business use cases, enterprise and platform architecture, and front-end integration. The role is based in Bangalore, India.
From the employer
As a Principal AI Engineer, you will define the architectural vision and governance standards for GenAI solutions at scale. You will lead the design of intelligent systems leveraging LLMs, agentic workflows, and vector-based retrieval strategies, while ensuring alignment with enterprise-level goals around security, performance, and reusability. This role operates at the intersection of deep technical expertise and cross-functional leadership.
Key Responsibilities & Skills
- Expert knowledge of Azure cloud services for designing, optimizing, and maintaining APIs
- Strong expertise in Azure SQL, including performance tuning and optimization
- Strong proficiency in API design principles and performance optimization techniques
- Solid understanding of, and experience with, enterprise-scale initiatives
- Effective collaboration with Enterprise Architects and Platform Architects
- Ability to understand business use cases and translate them into detailed technical designs
- Strong sense of accountability and ownership
- Strong proficiency in micro-services and micro front-end architecture
- Excellent problem-solving skills with a large-scale, strategic mindset
- Strong knowledge of security across application and data layers
- Strong exposure to Visual Studio and modern development environments
- Good knowledge of CI/CD processes and DevOps practices
- Demonstrated expertise in building LLM-integrated systems, embedding pipelines, and agentic workflows in production environments
- Deep understanding of prompt optimization, vector search, context management, and multi-step task orchestration
- Experience with cloud-native delivery (Azure preferred), containerized workloads, and scalable microservices
- Strong grasp of model safety, cost optimization, and observability in GenAI applications
- Build reusable components (SDKs, prompt libraries, orchestration templates) to accelerate solution delivery
- Experience integrating backend services with front-end applications; familiarity with UI functionality is a plus