SRE / Observability Engineer (Middle+ / Senior) (Python)

About the Role 

As a Senior Forward Deployed Engineer, you will be the technical owner for some of the most complex and strategic customer accounts. You will lead the technical approach, make clear decisions in ambiguous situations, and help customers get real value from the platform in complex enterprise environments. 

You will work across deployment, integration, automation, and solution design. You will also handle deep technical escalations and build reusable patterns, tools, and playbooks that help the wider Forward Deployed Engineering team move faster and deliver more consistently. 

This is a hands-on senior engineering role. You will work directly with customer executives, security and privacy leaders, business stakeholders, and technical teams. You will turn complex data, security, privacy, and AI needs into practical solutions that can scale. 

What You'll Do 

• Own technical delivery for the most complex customer accounts, from deployment through scaled, everyday use 

• Lead deployments across hybrid environments, including cloud, on-premises, Kubernetes, containers, Linux, and related infrastructure 

• Define solution architecture for customers with complex data estates, security needs, and business requirements 

• Adapt platform behavior when standard configuration does not fully match the customer’s data, workflows, or risk model 

• Build and operate integrations across customer systems, including identity, SIEM, ITSM, data platforms, APIs, and downstream tools 

• Diagnose and resolve deep technical issues across data, deployment, infrastructure, and integration layers 

• Build reusable agents, automations, tools, and playbooks that help the broader FDE team deliver faster and with higher quality 

• Turn manual customer outcomes into repeatable workflows for remediation, alerting, reporting, and operational follow-up 

• Lead architecture and design sessions with customer executives, security and privacy leaders, business teams, and engineers 

• Mentor other FDEs by reviewing solutions, sharing patterns, and helping unblock complex technical work 

• Partner with Sales Engineering, Product, and Engineering on strategic POCs, customer escalations, and product feedback from the field 

 

What You'll Bring 

• 8–12+ years of experience in deeply technical, customer-facing roles, such as forward-deployed engineering, solutions engineering, platform engineering, or technical consulting 

• Strong software engineering skills in at least one language, such as Python, Go, or TypeScript, with the ability to read unfamiliar code and understand complex systems quickly 

• Hands-on experience with Kubernetes, containers, Linux, and cloud platforms such as AWS, Azure, or Google Cloud 

• Experience deploying and operating solutions across complex cloud, hybrid, and on-premises enterprise environments 

• Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data 

• Experience building practical technical solutions, such as data pipelines, custom classifiers, integrations, automations, agents, or internal tools 

• Strong fluency with AI-native developer tools, agents, and automation, including creating reusable workflows that help others move faster 

• Strong customer presence, with the ability to build trust with executives, business leaders, and engineering teams 

• Working knowledge of data security, privacy, and regulatory topics across industries and geographies 

• High ownership, strong critical thinking, and the ability to bring structure to complex problems without a clear playbook 

 

Bonus Skills 

• Experience with DSPM, CSPM, DLP, data governance, privacy platforms, or related security domains 

• Experience building or heavily using AI agents, agentic coding assistants, MCP, or RAG systems 

• Familiarity with regulatory frameworks such as GDPR, SOC 2, or ISO 27001, especially across multiple geographies 

• Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery 

• Knowledge of access control, encryption, masking, or other data protection controls in enterprise data systems 

• Experience mentoring senior technical contributors or setting delivery standards in fast-paced, distributed teams 

 

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About the Role

Securiti's platform processes billions of data events per day across hundreds of enterprise clouds. As a DevSecOps Engineer, you will build and maintain the invisible infrastructure that makes this scale possible—ensuring developers can ship features daily while maintaining fortress-level security.

You will be responsible for designing self-healing deployment pipelines that turn infrastructure into code, security into automation, and complexity into reliability. Your work ensures that when a customer onboards petabytes of data, our platform scales transparently—without manual intervention.

Responsibilities

• Security-First Infrastructure: Architect and implement infrastructure-as-code using Terraform and CloudFormation, ensuring every deployment follows zero-trust principles and least-privilege access models.

• Kubernetes at Scale: Design and optimize our Kubernetes clusters to handle massive workloads, implementing intelligent autoscaling, pod security policies, and network segmentation that protects sensitive customer data.

• Zero-Downtime Deployments: Build sophisticated CI/CD pipelines using ArgoCD, Spinnaker, and GitOps patterns that enable blue/green and canary deployments—allowing us to ship multiple times per day with zero customer impact.

• Observability Engineering: Implement comprehensive monitoring and alerting using Prometheus, Grafana, and ELK, creating dashboards that surface anomalies before they become incidents.

• Multi-Cloud Orchestration: Manage infrastructure across AWS, Azure, and GCP, building abstraction layers that allow our platform to run anywhere while maintaining consistent security postures.

• Performance Under Fire: Be on-call to diagnose and resolve production issues in real-time, using your deep systems knowledge to troubleshoot complex distributed systems problems across the stack.

• Automation-First Mindset: Write Python and Go tooling that automates repetitive operational tasks, turning hours of manual work into seconds of automated execution.

Requirements

• Experience: 5+ years of software development with deep operational experience in cloud-native environments (AWS, Azure, GCP).

•  Infrastructure as Code Mastery: Expert-level proficiency with Terraform or AWS CloudFormation, with a portfolio of reusable modules and patterns.

• Container Orchestration: Production experience running Kubernetes at scale, including deep knowledge of networking, security contexts, and stateful workloads.

• CI/CD Architecture: Hands-on experience designing GitOps-based deployment pipelines using tools like ArgoCD, Spinnaker, Jenkins, or GitHub Actions.

• Development Skills: Professional coding ability in Python or Golang—you're not just configuring tools, you're building them.

• Database Operations: Working knowledge of SQL (Postgres), NoSQL (MongoDB/Elasticsearch), and Graph databases (Neo4j, Neptune) for operational troubleshooting and performance tuning.

• Linux & Networking Fundamentals: Deep understanding of Linux systems administration, bash scripting, network routing, load balancing, and service mesh architectures.

• Monitoring & Observability: Experience implementing full-stack observability with metrics, logs, and traces using Prometheus, Grafana, ELK, or similar tooling.

Bonus Points

• Security Certifications: AWS Security Specialty, CKS (Certified Kubernetes Security Specialist), or equivalent security-focused credentials.

• Service Mesh Experience: Hands-on work with Istio, Linkerd, or Consul for advanced traffic management and zero-trust networking.

• Chaos Engineering: Experience with fault injection frameworks (Chaos Monkey, Litmus) to build resilient systems.

• GitOps Evangelism: You've championed GitOps practices and trained teams on declarative infrastructure patterns.

• Cost Optimization: Track record of reducing cloud spend through intelligent resource management and architectural improvements.

 

About the Role

As a Forward Deployed Engineer, you will be the technical owner for strategic customer deployments of the Securiti AI platform within Veeam. You will work directly with customers to deploy, integrate, and scale the platform across complex cloud, hybrid, and on-premises environments.

• ✨ This role will be 3 days in office at our San Jose, CA location! ✨

You will help customers turn complex data and AI environments into clear security, privacy, governance, and AI readiness outcomes. This is a hands-on engineering role where you will build integrations, automate workflows, troubleshoot issues, and adapt the platform to fit real customer needs.

What You'll Do

• Own the technical outcome for customer accounts, from first deployment through scaled, everyday use
• Deploy and configure the platform across hybrid environments, including AWS, Azure, Google Cloud, private cloud, and on-premises systems
• Connect the platform to customer data systems, identity providers, reporting tools, and business workflows
• Configure, tune, and troubleshoot core deployment components, including Kubernetes, containers, Linux, and cloud infrastructure
• Build and operate integrations using APIs, including SSO/SAML/OIDC, SIEM, ITSM, data platforms, and downstream reporting or remediation systems
• Translate customer goals into technical plans that support data discovery, classification, governance, privacy, and AI security outcomes
• Adapt platform behavior when standard configuration does not fully match the customer’s data, risk model, or operating process
• Build production-grade solutions, including data pipelines, custom classifiers, automations, integrations, and agent-based workflows
• Use AI-native tools and agents to automate repeatable work, improve delivery quality, and increase your impact
• Diagnose complex issues across data, deployment, and integration layers using observability tools and structured problem-solving
• Lead technical sessions with customer teams; partner with Sales Engineering, Product, and Engineering to support POCs, resolve issues, and share field learnings
• This role will be 3 days in office at our San Jose, CA location! 

What You'll Bring

• 4–7+ years of experience in technical, customer-facing roles, such as forward-deployed engineering, solutions engineering, platform engineering, or technical consulting
• Strong software engineering skills, with fluency in at least one programming language such as Python, Go, or TypeScript
• Experience building and shipping practical technical solutions, such as scripts, integrations, data pipelines, classifiers, automations, or internal tools
• Ability to read unfamiliar code, understand running systems quickly, and guide targeted changes when needed
• Hands-on experience with Kubernetes, containers, Linux, and cloud platforms such as AWS, Azure, or Google Cloud
• Experience working across hybrid environments, including cloud, private cloud, and on-premises systems
• Strong understanding of APIs, system integration, SQL/NoSQL data stores, and structured or unstructured data
• Experience using AI-native developer tools, agents, and automation to work faster and improve quality
• Strong customer presence, with the ability to build trust with executives, business stakeholders, and technical teams
• Ability to translate unclear security, privacy, compliance, or business needs into a clear technical plan
• Working knowledge of data security, privacy, and regulatory topics across industries and geographies
• High ownership, strong critical thinking, and the ability to bring structure to complex problems without a clear playbook

Bonus Skills

• Experience with DSPM, CSPM, DLP, data governance, privacy platforms, or related security domains
• Experience building or heavily using AI agents, agentic coding assistants, MCP, or RAG systems
• Familiarity with regulatory frameworks such as GDPR, SOC 2, or ISO 27001
• Experience with enterprise data platforms such as Snowflake, Databricks, or BigQuery
• Knowledge of access control, encryption, masking, or data protection controls in enterprise data systems