Lead Software Engineer - Cloud DevOps & AI

Fairygodboss; Hyderabad; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

JPMorgan Chase in Hyderabad is seeking a Lead Software Engineer to guide AI/ML-driven DevOps, architect cloud infrastructure, and drive automation across on-premises and AWS environments.

You will design and implement CI/CD pipelines, IaC, and container orchestration strategies while leveraging AI-enabled tooling to boost deployment velocity, reliability, and cost efficiency. Collaboration with cross-functional teams is essential to deliver scalable, secure solutions.

Qualifications

• 5+ years in AI/ML engineering with automation
• Automation of IAC using Terraform, Ansible or CloudFormation
• Experience with observability tools and AI/ML integration
• Proficiency in Python or Java; ML framework familiarity
• Knowledge of AWS/Azure/GCP and containerization (Docker, Kubernetes)

Responsibilities

• Design and implement CI/CD pipelines and IaC frameworks
• Lead architecture and management of cloud infrastructure in AWS
• Drive AI/ML adoption within DevOps workflows and automation
• Lead integration of intelligent agents for workflow automation
• Develop AI-powered observability and automated incident response
• Collaborate with engineering, product and operations teams to identify automation opportunities
• Stay updated with AI/ML tooling and industry trends
• Provide hands-on guidance and conduct design reviews to ensure engineering excellence

Skills

AI/ML engineering

Agent-based systems

CI/CD automation

Python

Java

Kubernetes

Docker

Cloud platforms

Observability

Tools

Terraform

Ansible

CloudFormation

Docker

Kubernetes

Prometheus

Grafana

ELK stack

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking organization, we have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

Job Responsibilities:

• Design and implement CI/CD pipelines, infrastructure-as-code (IaC) frameworks, and container orchestration strategies leveraging tools such as Kubernetes, Docker, Terraform, and Spinnaker, while utilizing AI-driven automation to streamline deployment and management across cloud and on-premises environments.
• Lead the architecture, deployment, and management of cloud infrastructure in AWS, establishing and enforcing best practices for reliability, scalability, security, and cost optimization across all cloud environments.
• Drive the adoption of AI and machine learning capabilities within DevOps workflows, including intelligent monitoring, predictive analytics, and automated remediation, while evaluating and integrating AI-powered tools to continuously improve development velocity, system reliability, and operational efficiency.
• Lead the integration of intelligent agents for workflow automation, decision-making, and process optimization.
• Develop AI-powered observability solutions to monitor, analyze, and proactively manage application and infrastructure health, automating alerting, root cause analysis, and incident response using advanced ML techniques.
• Work closely with cross-functional teams including engineering, product, and operations to identify automation opportunities and deliver impactful solutions.
• Stay abreast of emerging AI/ML technologies, frameworks, and industry trends, driving continuous improvement by evaluating and implementing new tools, methodologies, and approaches.
• Provide hands-on technical guidance to a team of software and DevOps engineers, fostering a culture of innovation, accountability, and continuous learning.
• Conduct code reviews, architectural assessments, and design discussions to uphold engineering excellence.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years in AI/ML engineering, with proven expertise in agent-based systems and automation.
• Strong experience in automating IAC development (e.g., Terraform, Ansible, CloudFormation) using AI/ML.
• Deep understanding of observability tools (e.g., Prometheus, Grafana, ELK stack) and automation using AI/ML.
• Proficiency in Python, Java, or similar programming languages; experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Excellent problem-solving, communication, and collaboration skills.