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Open nowPosted 62 days ago

Tech Lead

Workable (global search)108,016 open roles

Where
Melbourne, VIC, Australia
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Your applicationOpen nowTech LeadWorkable (global search) · Melbourne, VIC, Australia
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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
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  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 62 days ago

Workable (global search) median: 7 days open

The posting

At Squiz, we are building a cloud-based Digital Experience Platform (DXP) designed to power complex content management, optimization tooling, and platform services. Within this ecosystem, our Discovery team is fundamentally redefining how enterprise customers interact with data. We are moving past traditional keyword matching to build next-generation Conversational Search and Content Intelligence products.

We are looking for an Engineering Tech Lead to serve as the technical overseer for this domain. This role requires a pragmatic, battle-tested software engineer. While you will help steer our journey into generative AI and conversational capabilities, your primary responsibility is building the resilient, secure, and cost-efficient cloud systems that make those capabilities possible. We need a systems thinker who values engineering rigor, robust architecture, and operational excellence just as much as cutting-edge technology.

The Team Dynamics

We believe great technical leaders should be free to focus on architecture and engineering excellence. Because of this, this role has zero direct reports. You will focus purely on technical steering, working in close lockstep with the team’s Engineering Manager, who handles people management, professional growth, and day-to-day sprint logistics.

This is a permanent position open to anyone living on the east coast of Australia. We operate on a flexible, hybrid model, meaning you can balance working from home and collaborating with the team in a way that actually works for you.

What the Work Looks Like Day-to-Day

  • Take complete technical ownership of the Discovery team's services, ensuring our conversational search and content intelligence pipelines are scalable, highly available, and structurally sound.
  • Design resilient, decoupled distributed systems using event-driven architectures, ensuring clean API boundaries and robust fault tolerance.
  • Champion DevSecOps practices within the team, embedding automated security scanning, vulnerability management, and strict IAM principles into everything we build.
  • Own and optimize our CI/CD pipelines, driving automated testing, seamless deployment strategies (like blue-green or canary releases), and infrastructure reproducibility.
  • Act as the financial guardian (FinOps) of our domain, actively monitoring and optimizing total AWS infrastructure spend across compute (ECS/Fargate/Lambda), storage (S3), search indexes, and LLM usage.
  • Provide technical steering for our Generative AI and RAG architectures, ensuring we evaluate and integrate tools like AWS Bedrock safely, cost-effectively, and pragmatically.
  • Partner closely with the Engineering Manager to balance the delivery of new product capabilities with the long-term health of our architecture and technical debt reduction.
  • Collaborate with business stakeholders and Designers to deconstruct complex technical concepts, outline system boundaries, write realistic user stories, and map out accurate estimates.
  • Stay close to the code by writing clean, resilient backend services using Node.js and TypeScript on AWS.
  • Provide supportive technical mentorship, lead architectural workshops, and run thorough code reviews for both junior and senior engineers on the team.

What We Are Looking For

  • A solid foundation of 8+ years of hands-on experience building, scaling, and maintaining complex distributed systems in production.
  • Deep production experience with cloud-native AWS environments, specifically serverless architectures (Lambda, API Gateway, DynamoDB), containerized workloads (ECS/Fargate), and Infrastructure as Code using AWS CDK or Terraform.
  • Proven capability in modern DevSecOps practices, including building and maintaining robust CI/CD automation pipelines and implementing the AWS Well-Architected Framework.
  • A strong track record of rigorous system design, with a deep understanding of caching strategies, database optimization, web performance tuning, and distributed debugging.
  • The technical maturity to evaluate, architect, and safely implement Generative AI workflows (such as RAG and orchestration via AWS Bedrock) without losing sight of cost control and data security.
  • Advanced programming skills in Node.js and TypeScript.
  • Comfort working in iterative, agile engineering environments that leverage Scrum or Kanban frameworks.

Tools and Context That Will Help You Stand Out

If you have a strong background in enterprise search engines (like Elasticsearch or OpenSearch) or data engineering pipelines, you'll have a massive head start here. While this is a heavily backend-focused infrastructure role, a passing literacy in React/JS/CSS helps keep frontend integrations smooth. Experience with modern cloud observability and monitoring tools (like Dynatrace, DataDog, or AWS CloudWatch) will also make you feel right at home.

About Squiz

Our mission is to empower organisations to create exceptional digital experiences that engage users, drive growth and build deeper relationships. Our long-term ambition is to redefine the digital experience landscape and become the platform of choice for enterprises pursuing customer-first digital transformation.

You’ll join a company that’s evolving quickly, investing heavily in modern AI-powered products, and competing in a space that’s becoming increasingly important.

You’ll work with some of the most intelligent and down to earth people you’ll ever meet: we are made up of a diverse range of passionate people who love challenging the status quo. Every day is different, but what is constant is we enjoy what we do.

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