Senior AI Platform Software Engineer
UL Solutions
- Location
- Bengaluru, Karnataka, India
- Job type
- Full-time
Required skills
- LangChain
- AWS
- Azure
- backend
- data ingestion
- Docker
- FastAPI
- front-end
- GCP
- GraphQL
- incident response
- Kubernetes
- machine learning
- SaaS
- RESTful
About the role
Website:
ul.com
Job details:
Job Description
- Design and implement high-performance RESTful or GraphQL APIs to expose AI model functionality to front-end applications and external services.
- Integrate Large Language Models (LLMs) and custom machine learning models into backend architectures, often using frameworks like LangChain, LangGraph, or FastAPI.
- Build and maintain data ingestion pipelines and vector databases (e.g., Pinecone, Weaviate) to support Retrieval-Augmented Generation for AI agents.
- Deploy and orchestrate containerized services using Docker and Kubernetes on cloud platforms like AWS, GCP, or Azure.
- Implement real-time monitoring and alerting for AI system health, including tracking model performance, latency, and drift.
- Design testing strategies for non-deterministic AI outputs, including the implementation of guardrails and safety constraints.
- Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, and ensuring a fast and effective incident response process
- Works as part of a team.
- Mentor colleagues in AI software engineering best practices
- Performs code reviews of junior software engineers and provides constructive feedback on any findings, both verbal and in writing.
- Read and follow the Underwriters Laboratories Code of Conduct, and follow all physical and digital security practices
- Performs other duties as directed.
Responsibilities
- Design and implement high-performance RESTful or GraphQL APIs to expose AI model functionality to front-end applications and external services.
- Integrate Large Language Models (LLMs) and custom machine learning models into backend architectures, often using frameworks like LangChain, LangGraph, or FastAPI.
- Build and maintain data ingestion pipelines and vector databases (e.g., Pinecone, Weaviate) to support Retrieval-Augmented Generation for AI agents.
- Deploy and orchestrate containerized services using Docker and Kubernetes on cloud platforms like AWS, GCP, or Azure.
- Implement real-time monitoring and alerting for AI system health, including tracking model performance, latency, and drift.
- Design testing strategies for non-deterministic AI outputs, including the implementation of guardrails and safety constraints.
- Own the full development lifecycle for services in a production SaaS environment. This includes establishing automated code coverage goals, rigorous code reviews, defining SLOs, and ensuring a fast and effective incident response process
- Works as part of a team.
- Mentor colleagues in AI software engineering best practices
- Performs code reviews of junior software engineers and provides constructive feedback on any findings, both verbal and in writing.
- Read and follow the Underwriters Laboratories Code of Conduct, and follow all physical and digital security practices
- Performs other duties as directed.
Qualifications
- Advanced technical knowledge and/or software development experience.
- Advanced working knowledge in software application or specific program language requirements of software work.
- University degree in Computer Science or a related discipline.
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