About the Organization-
Impetus Technologies is a digital engineering company focused on delivering expert services and products to help enterprises achieve their transformation goals. We solve the analytics, AI, and cloud puzzle, enabling businesses to drive unmatched innovation and growth.
Founded in 1991, we are cloud and data engineering leaders providing solutions to fortune 100 enterprises, headquartered in Los Gatos, California, with development centers in NOIDA, Indore, Gurugram, Bengaluru, Pune, and Hyderabad with over 3000 global team members. We also have offices in Canada and Australia and collaborate with a number of established companies, including American Express, Bank of America, Capital One, Toyota, United Airlines, and Verizon.
Locations- Gurgaon, Bengaluru, Pune, Chennai, Noida, Gurgaon
Job Summary
We are seeking an experienced AI Engineer to drive the design, development, and operation of the infrastructure, data pipelines, and platform capabilities that power our AI and LLM-based solutions.
This is a hands-on engineering role for professionals passionate about building scalable, secure, and production-ready AI platforms rather than developing AI models themselves.
You will collaborate with application engineers, data scientists, architects, and product teams to deliver reliable, observable, and cost-efficient AI infrastructure that supports enterprise-scale AI workloads.
Must-Have Skills
8–12 years of hands-on experience in software engineering and platform engineering.
Robust proficiency in Python, including asynchronous programming, API development, and microservices architecture.
Extensive experience with AWS, including ECS/EKS, Lambda, API Gateway, S3, SQS, and RDS.
Strong background in data engineering, including ETL/ELT pipelines, document processing, and vector databases such as Pinecone, Weaviate, and pgvector.
Proven experience building and operating production-grade AI/LLM platforms, including embedding pipelines, API gateways, Retri
📌 Lead Software Engineer (Noida)
🏢 Impetus
📍 Noida