DevSecOps Engineer

Description

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Responsibilities:

Lead the foundational setup of the organization's MLOps and AIOps functions — including architecture, tooling, governance, and workflows — aligned with business and data strategy. Define and implement the MLOps roadmap: identify key use cases, standardize model development lifecycle, and architect scalable pipelines using AWS-native services. Establish the AIOps practice by implementing observability, automated incident response, and intelligent monitoring using Amazon CloudWatch, DevOps Guru, AWS X-Ray, and other tools. Select and integrate appropriate AWS services (e.g., SageMaker, Bedrock, Lambda, Glue, CodePipeline) to build a flexible and secure MLOps and AIOps infrastructure. Collaborate with stakeholders across data science, DevOps, engineering, and security to ensure the smooth operationalization of AI/ML models from development to production. Develop governance, monitoring, and compliance frameworks for AI/ML lifecycle, ensuring data security, lineage, traceability, and auditability. Design and implement model CI/CD workflows from scratch using tools like SageMaker Pipelines, CodeBuild, Terraform, GitHub Actions, and CloudFormation. Build out data pipelines and feature engineering workflows on AWS using services like AWS Glue, S3, Step Functions, Athena, and Redshift. Establish and evangelize best practices for model monitoring, drift detection, and continuous retraining using SageMaker Model Monitor, Clarify, and CloudWatch. Lead the adoption of AI copilots and Agentic AI (e.g., GitHub Copilot, Amazon Q, Bedrock agents) to improve developer productivity, code quality, and automation. Develop a strategy for real-time data observability and health monitoring using open-source and AWS-native tools, integrated into the broader data ecosystem. Provide thought leadership and mentoring to build internal capability in MLOps and AIOps, including training team members and defining reusable standards. Define and implement security-first principles for ML pipelines, ensuring IAM policies, encryption, and secrets management follow AWS best practices. Drive adoption of infrastructure-as-code (IaC) for ML platform provisioning and reproducibility using Terraform or CloudFormation.

Qualifications and Experience:

Bachelor’s degree in Software Engineering, Computer Science, Computer Engineering, or a related engineering discipline; Master’s degree (preferably from IIT/IISc or other premier institutes) is a strong advantage. 5+ years of hands-on experience in designing, implementing, or supporting AI/ML workloads on AWS, with a strong focus on cloud-native architecture, automation, and operationalization.

Skills and Abilities Required:

Expertise in scripting/development using Python, AWS SDKs (boto3), Bash, and infrastructure scripting languages. While following development best practices. Expertise in Terraform & CloudFormation. Experience with AWS Services like STS, IAM, Lambda, S3, CloudWatch, Glue, SageMaker, QuickSight, Athena, Bedrock, EventBridge, etc. Experience integrating Agentic AI systems into software development workflows CI/CD security scanning, compliance enforcement, observability Good Communication and documentation skills. Can-do positive attitude, always looking to accelerate development. Driven commit to high standards of performance and demonstrate personal ownership for getting the job done. Innovative and entrepreneurial attitude, stays up to speed on all the latest technologies and industry trends; healthy curiosity to evaluate, understand and utilize new technologies.
 

Good to have:

Experience with Amazon Q, Bedrock Agents, or similar generative AI agents. Development experience in python. Exposure to open-source observability stacks like Prometheus, Grafana, and ELK. Knowledge of enterprise data governance frameworks and tools (e.g., AWS Lake Formation, Apache Atlas). AWS Certifications such as: AWS Certified Machine Learning – Specialty, AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Associate or Professional

Location:

IN-UP-Noida, India-World Trade Tower (eInfochips)

Time Type:

Full time

Job Category:

Engineering Services

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