15h Left Lead Software Engineer

3 weeks ago

Delhi, India AppZen Full time

Role: Lead Software Engineer : ML Ops & System Engineering

About Us:
AppZen is the leader in autonomous spend-to-pay software. Its patented artificial intelligence accurately and efficiently processes information from thousands of data sources so that organizations can better understand enterprise spend at scale to make smarter business decisions. It seamlessly integrates with existing accounts payable, expense, and card workflows to read, understand, and make real-time decisions based on your unique spend profile, leading to faster processing times and fewer instances of fraud or wasteful spend. Global enterprises, including one-third of the Fortune 500, use AppZen’s invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses. To learn more, visit us at

www.appzen.com

.

About the Role:
We are looking for a

Lead Software Engineer

with strong expertise in

ML Ops, distributed systems, and platform engineering

to design, build, and scale high-performance infrastructure. You will lead initiatives across software engineering, system reliability, and machine learning operations to deliver robust, production-ready solutions.

Key Responsibilities
Design & Develop

scalable, secure, and reliable microservices using

Golang

and

Python .
Build and maintain containerized environments

using

Docker

and orchestrate them with

Kubernetes .
Implement CI/CD pipelines

with

Jenkins

for automated testing, deployment, and monitoring.
Manage ML workflows

with

MLflow , ensuring reproducibility, versioning, and deployment of machine learning models.
Leverage Temporal

for orchestrating complex workflows and ensuring fault-tolerant execution of distributed systems.
Work with AWS cloud services

(EC2, S3, IAM, basics of networking) to deploy and manage scalable infrastructure.
Collaborate with data science and software teams

to bridge the gap between ML research and production systems.
Ensure system reliability and observability

through monitoring, logging, and performance optimization.
Mentor junior engineers and lead best practices for ML Ops, DevOps, and system design.

Required Skills & Experience:

Minimum 5+ years of experience
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Strong programming skills in Golang and Python
Hands-on experience with Kubernetes and Docker in production environments.
Proven experience in microservices architecture and distributed systems design.
Good understanding of AWS fundamentals (EC2, S3, IAM, networking basics).
Experience with MLflow for ML model tracking, management, and deployment.
Proficiency in CI/CD tools (preferably Jenkins).
Knowledge of Temporal or similar workflow orchestration tools.
Strong problem-solving and debugging skills in distributed systems.
Excellent communication and leadership skills with experience mentoring engineers.

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