DevSecOps Senior Engineer/Lead

Sharp Decisions; Torrance (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

Sharp Decisions is seeking a DevSecOps Senior Engineer/Lead in Torrance, CA for onsite work four days per week. You will lead CI/CD, DevSecOps, cloud platform engineering, and environment management across development, QA, staging, and production, ensuring security, reliability, and scalability.

You will partner with development, architecture, security, and operations to accelerate software delivery, improve developer productivity with AI-powered tools, and mentor teams on best practices in

Job description

DevSecOps Senior Engineer/Lead

Location: Torrance, CA

Work Type: Onsite 4 days per week

Employment Type: W2 Only

Position Success Criteria / Minimum Educational Qualifications

• Bachelor’s or Master’s degree (BS/MS).

Position Overview

The DevSecOps Senior Engineer/Lead within the Client’s Digital Services Development organization is responsible for leading CI/CD, DevSecOps, cloud platform engineering, and environment management for digital platforms. This role drives automation, security, observability, reliability, and AI-enabled engineering practices while ensuring development, QA, staging, and production environments remain stable, scalable, and secure.

The individual partners closely with development, architecture, security, and operations teams to support complex enterprise programs, accelerate software delivery, improve developer productivity through AI-powered tools and automation, and maintain highly available cloud-native platforms.

Key Responsibilities (Mandatory Skills)

• Bring 5-10 years of experience in DevOps, DevSecOps, Platform Engineering, Cloud Engineering, or related disciplines supporting enterprise-scale applications and distributed systems.
• Have 3+ years of experience in a senior technical role, such as DevSecOps Lead, Platform Engineer, Senior DevOps Engineer, or Site Reliability Engineer (SRE).
• Demonstrate strong hands‑on experience with AWS cloud services, including EKS/ECS, Lambda, IAM, VPC, CloudWatch, S3, RDS, Kinesis, MQ, Redshift, Secrets Manager, SNS, SQS, EventBridge, ElastiCache, and related services.
• Design, build, and maintain CI/CD pipelines using Jenkins, GitLab CI/CD, GitHub Actions, AWS CodePipeline, Argo CD, or similar technologies.
• Implement Infrastructure as Code (IaC) using Terraform, CloudFormation, Helm, and related automation frameworks.
• Demonstrate strong experience with Docker, Kubernetes, Amazon EKS, and container platform operations.
• Implement DevSecOps practices, including vulnerability management, secrets management, policy enforcement, compliance validation, and software supply chain security.
• Apply strong cloud security knowledge, including IAM, RBAC, encryption, OAuth 2.0/OIDC, JWT, network security, and Zero Trust principles.
• Build and manage observability, monitoring, logging, and alerting solutions using CloudWatch, Prometheus, Grafana, ELK/OpenSearch, Datadog, Splunk, or similar tools.
• Develop automation and scripts using Python, Bash, Go, or similar programming languages.
• Drive platform reliability, resiliency, operational excellence, disaster recovery, and production readiness.
• Leverage AI-assisted engineering tools such as GitHub Copilot, Amazon Q, OpenAI, Claude, Cursor, or similar technologies to improve developer productivity, automation, troubleshooting, and operational efficiency.
• Demonstrate familiarity with enterprise AI/LLM concepts, including Prompt Engineering, RAG, Vector Databases, AI Agents, LLMOps, AI Security Guardrails, and Responsible AI practices.
• Collaborate with development, architecture, security, and infrastructure teams to improve platform scalability, security posture, developer experience, and engineering productivity.
• Lead cloud modernization, automation, platform engineering, and DevSecOps initiatives while mentoring engineering teams on best practices.

Desired Skills (Nice to Have)

• Experience integrating and operating AI/LLM services using AWS Bedrock, Amazon Q, OpenAI, Azure AI, Anthropic Claude, or equivalent enterprise AI platforms.
• Experience supporting LLMOps pipelines, AI model deployment, governance, monitoring, and security.
• AWS, Kubernetes, Terraform, Security, DevOps, AI/ML, or related professional certifications.

LI-JS2