DTEX Systems - Infrastructure Engineer (SRE) - Recruiter Screen Prep

Job URL: https://www.linkedin.com/jobs/view/4395937049Role: Infrastructure Engineer (SRE focus) Employment Type: Full-time Seniority: Mid-Senior level Location: Fremont, CA (hybrid/remote, US-based candidates only) Salary Range: $160k–$220k (SF Bay Area) Focus: Infrastructure modernization, IaC automation, Python-driven SRE, legacy-to-modern migration

⚠️ Note: This role requires US-based candidates and may require US citizenship for federal contract screening. Confirm eligibility before proceeding.

1) Quick Role Read

DTEX Systems is the global leader in Workforce Cyber Intelligence and insider threat detection. Their platform (DTEX InTERCEPT) monitors user behavior and data activity to detect and mitigate insider risks — serving enterprise and government customers in financial services, critical infrastructure, defense, and healthcare.

This role is an SRE position with a heavy software engineering and automation focus. DTEX is explicitly looking for someone to drive the transition from legacy manual operations to modern, automated Infrastructure as Code. This is not a "keep the lights on" role — it is a transformation role.

Top signals from the posting:

• Write and maintain Python software to automate provisioning, deployment, and configuration management.
• Establish Terraform best practices: state management, modularization, version control.
• Use Ansible/Saltstack for consistency and standardization across environments.
• Build CI/CD pipelines for infrastructure and application deployments, replacing manual processes.
• Implement and mature monitoring, logging, and alerting (Prometheus, Grafana, Zabbix, OpenSearch).
• Participate in follow-the-sun on-call with blameless postmortems.
• Champion SRE principles and automation culture across the organization.
• Work in enterprise and government-focused environments with strong security and reliability requirements.
• AI tools for SRE and agentic workflows are a valued plus.

2) Core Positioning

Your strongest pitch for this role is that you have done exactly this kind of transformation — multiple times, at multiple companies — and you bring software engineering discipline to infrastructure work:

• Legacy-to-modern migration specialist: At illion, you migrated from EC2 to ECS, reducing change lead time by 92%. At Domain, you drove the migration from ECS to Kubernetes for 100+ microservices. At Avinet, you migrated an entire AWS environment to IaC. This pattern of modernization is the core of what DTEX needs.
• Python and automation-first mindset: You write Python and Bash to solve infrastructure problems, not just click through consoles. Your AI Slack bot at Viator and K8sGPT custom prompts demonstrate software engineering applied to operational challenges.
• Terraform at scale: You have built 50+ reusable Terraform modules at Domain, consolidated ad-hoc resources into versioned modules across 30+ AWS accounts at Envato, and achieved audit compliance through IaC at Avinet.
• Monitoring and observability depth: Prometheus, Grafana, ELK/OpenSearch, Datadog, New Relic, PagerDuty, OpenTelemetry — you have worked across the full spectrum and understand how to implement monitoring that actually improves reliability.
• Incident response and on-call maturity: You have established incident management processes (Avinet), integrated PagerDuty workflows (Envato), and reduced MTTR by 70% (Avinet) and incident resolution by 40% (Envato).
• AI for SRE: At Viator, you introduced K8sGPT with 20+ custom prompts for evidence gathering and troubleshooting, and built an AI Slack bot that reduced first-response time by 50%. At Future Secure AI, you are delivering AI Co-Workers in production.

3) Your Fit Story

Strongest alignment

• Proven legacy-to-modern migration track record: This is the single most important requirement in the posting, and it is the defining pattern of your career. From bare-metal to VMs, EC2 to ECS, ECS to Kubernetes, manual ops to GitOps — you have repeatedly taken organizations from where they are to where they need to be.
• Strong Python proficiency: You use Python as a primary language for automation, tooling, and infrastructure management. Combined with Bash, you cover the two scripting pillars DTEX needs.
• Deep Terraform expertise: 50+ reusable modules at Domain, 30+ AWS accounts consolidated at Envato, modularization and state management across complex multi-account environments. This directly maps to DTEX's need to establish Terraform best practices.
• Ansible experience: Your early career as a Linux Engineer managing 1,200+ VMs with Ansible gives you configuration management depth that many SREs lack.
• Linux internals knowledge: Starting as a Linux Engineer managing bare-metal servers and 250-host VMware environments, through to Kubernetes platform engineering — your Linux foundation is deep and practical.
• CI/CD pipeline builder: Jenkins, GitHub Actions, GitLab, Buildkite, Argo CD — you have built and improved pipelines across every role, including reducing change lead time from 2 hours to 10 minutes at illion.
• Monitoring and observability across tools: Direct experience with Prometheus, Grafana, ELK (OpenSearch), Datadog, New Relic, and PagerDuty. You have both implemented and migrated monitoring systems.
• AI-driven SRE workflows: K8sGPT, AI Slack bots, agentic tooling rollout at Viator, and production AI systems at Future Secure AI. This maps directly to their "highly desirable" AI tools requirement.
• Compliance and security environments: SOC 2 Type 2 and ISO 27001 audit experience at illion, security tooling integration (Orca, CrowdStrike) at Domain. This aligns with DTEX's enterprise and government customer base.
• Incident management and on-call culture: Established incident management processes, blameless postmortems, PagerDuty integration, and measurable MTTR improvements.

Potential recruiter concerns and how to frame them

• Location / US citizenship: This is the biggest potential blocker. The role states US-based candidates only and may require federal contract screening. If you have US eligibility (you studied at UT Arlington), clarify this early. If not, this may be a non-starter unless DTEX is open to exceptions.
• Saltstack is not in your background: You have deep Ansible experience, which is the closer analogue. Saltstack and Ansible solve the same category of problems, and your configuration management fundamentals transfer directly.
• GCP is not your primary cloud: Your experience is heavily AWS-focused. Frame this as depth in one major cloud with transferable patterns — networking, IAM, compute abstractions, and IaC principles apply across providers.
• This is a cybersecurity company: You have not worked in cybersecurity product companies before. Frame it as: the infrastructure and SRE challenges are universal, and your compliance experience (SOC 2, ISO 27001) shows you understand security-sensitive environments.

4) Main Recruiter Narrative

90-second intro

I am a Senior Platform and SRE engineer with 13 years of experience, and the thread that runs through my career is taking organizations from legacy, manual infrastructure to modern, automated systems. I have done that migration multiple times — from bare-metal to VMs, EC2 to ECS, ECS to Kubernetes, manual deployments to GitOps — and each time I have brought software engineering discipline to the problem rather than just replacing one set of tools with another.

At Domain, I helped migrate 100+ microservices to Kubernetes, built a library of 50+ reusable Terraform modules, and enabled 20+ teams to deploy independently. At Envato, I consolidated ad-hoc infrastructure across 30+ AWS accounts into versioned Terraform modules, reducing drift by 80%. At illion, I took a fully manual deployment process and automated it down from 2 hours to 10 minutes while leading the team through SOC 2 and ISO 27001 audits.

More recently at Viator, I have been applying AI to SRE workflows — rolling out agentic tooling, building an AI Slack bot that cut first-response time by 50%, and introducing K8sGPT with custom prompts for faster troubleshooting.

What drew me to this role at DTEX is that it is exactly the kind of transformation I have built my career around — moving from legacy operations to modern, automated infrastructure — and doing it in a high-stakes environment where reliability and security genuinely matter.

5) Recruiter Questions — Suggested Answers

Tell me about yourself

Use the 90-second version above. Key theme: legacy-to-modern transformation, Python and Terraform at scale, AI-augmented SRE.

Why DTEX?

• The role is a greenfield modernization challenge, which is where I do my best work.
• DTEX operates in a space where infrastructure reliability directly impacts customer trust and national security outcomes — that level of consequence is motivating.
• The emphasis on software engineering principles applied to infrastructure aligns with how I approach SRE work: writing clean, testable automation, not just scripting one-off fixes.
• I am interested in cybersecurity as a domain and want to contribute to a product that protects organizations from insider threats.

Why are you exploring now?

Viator consolidated Australian engineering roles as part of a broader restructure. Keep it factual and positive, then pivot to wanting a role where you can drive a meaningful infrastructure transformation and apply your full range of skills — Python, Terraform, monitoring, and automation — at a company where SRE is a first-class investment.

Tell me about your Terraform experience

At Domain, I built 50+ reusable Terraform modules covering networking, IAM, compute, and Kubernetes resources, and used Atlantis for automated plan/apply workflows. At Envato, I consolidated ad-hoc resources across 30+ AWS accounts into versioned modules, reducing infrastructure drift by 80%. At Avinet, I migrated an entire AWS environment to IaC for audit compliance. I understand state management, module design, provider versioning, and how to structure Terraform for teams, not just individuals.

How strong is your Python?

Python is one of my primary languages for infrastructure automation. I use it for tooling, integrations, and automation scripts. At Viator, I built an AI-powered Slack bot in Python that integrated with our internal knowledge base. I write clean, testable code — not throwaway scripts — because infrastructure tooling needs to be maintained and extended by the team.

Do you have experience with legacy-to-modern migrations?

This is the defining pattern of my career. At illion, EC2 to ECS with a 92% reduction in change lead time. At Domain, ECS to Kubernetes for 100+ microservices. At Avinet, manual operations to full IaC. At Envato, scattered ad-hoc resources to consolidated Terraform modules. Each migration required understanding the existing system deeply, building confidence with the team, and delivering incrementally.

What is your monitoring and observability experience?

I have hands-on experience with Prometheus, Grafana, ELK/OpenSearch, Datadog, New Relic, PagerDuty, and OpenTelemetry. At Envato, I led a migration from New Relic to Datadog that cut observability costs by 45% and improved incident resolution by 40%. At Viator, I automated observability coverage for 80% of services with standardized Grafana dashboards via Terraform. At Domain, I rolled out SLO patterns and shifted observability left into platform pipelines.

Have you worked with Ansible?

Yes. My early career as a Linux Engineer involved managing 1,200+ VMs across a 250-host VMware environment with Ansible for configuration management. I understand playbook design, inventory management, and idempotent configuration patterns. While Saltstack is not in my direct background, the configuration management principles and patterns are transferable.

How do you approach on-call and incident response?

I have both participated in and established on-call rotations. At Avinet, I set up incident management processes and disaster recovery procedures from scratch, reducing MTTR by 70%. At Envato, I integrated PagerDuty with Datadog and improved incident resolution by 40%. I believe strongly in blameless postmortems and using incidents as data to drive systemic improvements, not just patches.

What is your experience with AI tools in SRE?

At Viator, I introduced K8sGPT with 20+ custom prompts to reduce evidence gathering and troubleshooting time for the SRE team. I also built an AI Slack bot that used our internal knowledge base to handle common support issues, cutting first-response time by 50%. I rolled out agentic coding tools across the organization and captured metrics to measure impact. At Future Secure AI, I am currently building and operating production infrastructure for AI Co-Workers.

Are you comfortable in enterprise/government security environments?

Yes. At illion, I led SOC 2 Type 2 and ISO 27001 audit preparation, providing comprehensive evidence and driving the team through successful audits. At Domain, I integrated Orca and CrowdStrike into platform pipelines for security posture management. I understand the compliance rigor and operational discipline that enterprise and government customers require.

6) Stories to Keep Ready

Story A — Legacy-to-modern infrastructure transformation (illion)

• Problem: Fully manual EC2-based deployment process taking 2 hours per release, with no IaC and limited automation.
• Action: Architected and led the migration from EC2 to AWS ECS, containerized the entire ASP.NET environment, and designed an automated CI/CD pipeline.
• Result: Reduced change lead time by 92% (2 hours to 10 minutes). Also led SOC 2 Type 2 and ISO 27001 audit preparation through this modernized environment.

Story B — Terraform at scale with team enablement (Domain)

• Problem: 100+ microservices needed a reliable, self-service platform, but infrastructure was fragmented and teams could not deploy independently.
• Action: Built 50+ reusable Terraform modules, implemented Atlantis for automated plan/apply, migrated from ECS to Kubernetes, and enabled GitOps workflows.
• Result: 20+ product teams deploying independently, 60% reduction in new service onboarding time, and 40% SLO adoption in 3 months.

Story C — AI-augmented SRE workflows (Viator)

• Problem: SRE team spending too much time on evidence gathering, troubleshooting, and repetitive support queries.
• Action: Introduced K8sGPT with 20+ custom prompts for faster troubleshooting. Built an AI Slack bot integrated with the internal knowledge base for first-line support. Rolled out agentic coding tools and measured adoption.
• Result: 50% reduction in first-response time for internal support. Measurable improvement in developer efficiency and SRE troubleshooting speed.

Story D — Monitoring migration with business impact (Envato)

• Problem: Observability costs were high, alert quality was poor, and incident response was slow.
• Action: Led migration from New Relic to Datadog, redesigned alerting strategy, integrated PagerDuty workflows, and added OpenTelemetry instrumentation to critical paths.
• Result: 45% reduction in observability costs, 40% improvement in incident resolution time.

7) What to Emphasize in the Call

• You are a transformation engineer — your career is defined by taking legacy environments and modernizing them with IaC, automation, and software engineering discipline.
• You bring Python and Terraform depth that goes beyond scripting — you write maintainable, modular code and build reusable infrastructure libraries.
• You have real AI-for-SRE experience, not just familiarity — K8sGPT, AI bots, agentic tooling with measured outcomes.
• You understand monitoring from implementation to migration — Prometheus, Grafana, ELK, Datadog, New Relic, PagerDuty, OpenTelemetry.
• You have compliance and security environment experience (SOC 2, ISO 27001, CrowdStrike, Orca) relevant to DTEX's enterprise and government customer base.
• You have deep Linux foundations from your early career managing bare-metal servers and VMware environments with Ansible.
• You approach on-call with engineering discipline — blameless postmortems, systematic MTTR reduction, and data-driven improvements.

8) Questions to Ask the Recruiter

1. What does the current infrastructure look like, and how far along is the modernization journey?
2. What is the primary cloud provider today — AWS, GCP, or a mix?
3. How large is the SRE/infrastructure team, and what is the team structure?
4. What does the follow-the-sun on-call rotation look like in practice?
5. How much greenfield automation work versus maintaining existing systems does this role involve?
6. What security clearance or personnel screening is required for this role, and what is the timeline for that process?
7. Is the team open to candidates currently based outside the US who may be willing to relocate, or is US residency a hard requirement from day one?

9) 30-second close

What excites me about this role is that it maps directly to the kind of work I have built my career around — taking legacy infrastructure and transforming it into modern, automated, code-driven systems. I bring deep experience in Python, Terraform, Ansible, monitoring, and CI/CD, and more recently I have been applying AI to SRE workflows in ways that deliver measurable improvements. I think that combination would have a meaningful impact at DTEX.

10) Prep Checklist

• Rehearse the 90-second intro out loud.
• Memorize these proof points: 92% change lead time reduction, 50+ Terraform modules, 100+ microservices Kubernetes migration, 80% infrastructure drift reduction, 50% first-response time reduction with AI bot, 45% observability cost reduction.
• Clarify your US work eligibility status before the call.
• Be ready to explain how you approach a legacy-to-modern migration step by step.
• Be ready to talk about Python as a tool for infrastructure, not just scripting.
• Research DTEX InTERCEPT platform and insider threat detection basics.
• Understand the enterprise/government security context and how your SOC 2/ISO 27001 experience applies.
• Keep your tone practical, confident, and transformation-focused.