Role 

We are looking for an AI Operations Engineer to join our team. This is a hybrid role based in our Zagreb office, reporting to Dominik Jurincic within the Red Teaming department. As an AI Operations Engineer, you will support the AI Red Team by operating and scaling the evaluation infrastructure that powers SPLX’s model benchmarks and MCP server registry. You’ll be the engineering force behind our continuous AI security testing workflows, ensuring our evaluation pipelines run reliably across a rapidly expanding ecosystem of LLMs and agentic tools.

What you’ll do (Role Expectations)

• Operate and extend our LLM benchmarking pipeline by integrating new models — whether through provider APIs or self-hosted deployments on virtualized infrastructure — and executing our security suite to populate and maintain the model benchmarks page
• Kick-off and maintain the SPLX MCP server registry by onboarding open-source MCP servers, provisioning their runtime dependencies, and running our dynamic code scanning and security testing against them
• Build and maintain reproducible deployment environments for evaluating third-party AI systems, ensuring consistent and reliable test conditions across diverse model and tooling configurations
• Partner with Red Team engineers and researchers to streamline evaluation workflows, automate recurring testing operations, and surface insights from benchmark and registry data
• Continuously improve the team’s internal tooling and operational processes, identifying opportunities to reduce manual effort and accelerate the cadence of model and MCP evaluations

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.
• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution.
• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.
• You are a learner. You have a true growth mindset and never stop developing yourself, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.
• You operate with urgency. You understand that in a high-growth environment, speed and quality are not mutually exclusive. You have a relentless focus on execution and a bias for action, delivering high-impact results quickly to win for the customer and the team.

What We’re Looking for (Minimum Qualifications)

• 1+ years of professional software engineering experience with Python, including the ability to ship reliable, production-quality code in a collaborative environment
• Working familiarity with the modern AI/ML ecosystem, including LLM provider APIs, model deployment patterns, and emerging protocols such as the Model Context Protocol (MCP)
• Hands-on experience with containerization (Docker) and deploying applications across cloud or virtualized infrastructure
• Solid working knowledge of REST APIs and modern integration patterns, including authentication, service orchestration, and debugging across distributed components
• Strong attention to detail and a track record of operating consistently in environments where reproducibility, rigor, and follow-through matter

What Will Make You Stand Out (Preferred Qualifications)

• Prior exposure to LLM evaluation, AI security, or red teaming workflows in a research or applied setting
• Familiarity with the broader open-source AI tooling landscape — including MCP servers, model serving frameworks, or agentic systems — and the curiosity to keep up with a fast-moving space
• Background in DevOps, platform engineering, or infrastructure automation, with comfort building reproducible test environments at scale

#LI-MM8 

#LI-HYBRID

he Gaming Integrations team is at an inflection point. We operate ~26 provider integrations across three runtimes (Elixir, Node.js, Erlang) and are the critical path for Superbet entering new markets.

This role is a key part of our capacity plan. You'll join a small but high-impact team and immediately contribute to real challenges: rebuilding our game platform into a scalable, multi-studio platform, and accelerating integration delivery so Superbet launches in new countries faster.

What You'll Be Working

• Elixir platform migration: Contributing to the migration of our Node.js/Erlang integrations to the new Elixir-based platform. Feature parity across runtimes is a blocker for many localizations today.
• Game Studio Integrations: Owning the full lifecycle of new provider integrations (launchUrl, authenticate, balance, debit, credit, void) from implementation through production sign-off.
• Platform architecture: Implementing CI/CD pipelines, shared services, and the modular architecture needed to support multiple exclusive gaming studios at scale.
• Operational excellence: Keeping KTLO (keeping the lights on) under 10% of team capacity while maintaining high availability across all 26+ live integrations.

What We Expect

Project Impact

• Consistently high productivity across many concurrent projects, and delivers large scope with quality and mature practices
• Proactively identifies problems and drives resolution, often without guidance
• Leads larger projects or small squads, runs meetings, writes status reports, tracks delivery
• Helps make the people around them move faster by identifying what's slowing the team down
• Demonstrates impact clearly through metrics, not just activity

Engineering Excellence

• Takes end-to-end ownership of product quality: reliability, efficiency, security, and performance
• Drives engineering efficiency improvements across the org (faster onboarding, better tooling, reduced cycle time)
• Becomes the established go-to owner of at least one component or system with expert depth
• Advocates for rapid prototyping and data-driven idea validation
• Develops and tracks metrics that quantify product quality and engineering efficiency

Communication & Collaboration

• Builds working relationships cross-functionally (product, SRE, QA, integration managers, gaming studios)
• Proactively seeks and acts on feedback
• Gives detailed, specific positive and constructive feedback to the Tribe lead and teammates
• Facilitates fast learning cycles and nurtures innovation within the team

Organizational Impact

• Actively mentors less-experienced engineers and creates conditions for them to grow
• Participates in recruiting and interviewing (especially for diversity recruiting)
• Onboards new team members and makes codebases easy to ramp up on
• Invests in their own skills and brings new knowledge back to the team (currently relevant: Elixir, Kafka operations, distributed systems at scale)

What We're Looking For

• MUSTs
  • High agency — proven track record of unblocking themselves and helping drive improvements across a team
  • Experience with microservice and event-based architectures
  • Experience with Kafka (operating Kafka in production is a strong bonus)
• Experience
  • 5+ years building high-quality software with strong engineering practices (code reviews, CI/CD, design docs)
  • Experience building highly-available, highly-scalable, distributed backend systems
  • Worked cross-functionally in product organizations alongside product managers, designers, and stakeholders
• Technical
  • Node.js / TypeScript
  • Kafka
  • Elixir or functional programming experience — strong bonus (our strategic direction)
  • Kubernetes, Docker, AWS
  • Experience in the betting or gaming industry
• Cultural & Behavioral
  • Strong collaborator — not a solo player, not an asshole
  • Product engineer mindset — not purely tech-focused, understands business context
  • Strong sense of ownership and problem-solving instinct
  • Clear, direct communication

Why Join Us

• T-shaped team where engineers contribute across the full stack and influence technical direction
• Fully remote, team distributed across Europe
• Partner directly with exclusive Game Studios building casino content for Superbet
• Lead and mentor in a small team with high visibility and real ownership
• High-revenue, high-stakes domain with real business impact
• Help steer the technical strategy of a growing team

• Owning the full development lifecycle – from planning and implementation to release and maintenance
• Building innovative solutions using modern technologies such as TypeScript, Vue, AWS, Docker, k8s, GitHub Actions and more...
• Leveraging best-in-class tools like Notion, Jira Cloud, GitHub, Zoom, Lattice, and Slack to maximize productivity and collaboration
• Collaborating cross-functionally with backend, frontend, design and QA engineers across squads, as well as our product team.
• Working on new product features that should provide a big customer growth by the end of the year
• Contributing to a high-growth environment
• Ensuring reliability, security, and compliance while keeping customer friction to a minimum

• 3+ years of frontend development experience with strong knowledge of JavaScript and TypeScript
• A self-starter mentality – we need autonomous engineers who proactively unblock themselves, collaborate across teams, and take initiative
• Strong attention to detail and a commitment to delivering exceptional products
• Deep understanding of best practices, design patterns, and core principles in software development
• A customer-first mindset – an understanding of how frontend decisions impact millions of users
• Strong problem-solving skills – ability to navigate complex domains and optimize high-traffic, high-availability systems
• Take ownership for technical quality, development process and developer experience
• A team-first mindset, thriving in collaborative environments where success is shared
• Willingness to learn new things. Even though Frontend will be major part of the day-to-day, we seek for an engineer who is open to learn and contribute to occasional BE tasks as well.

• Experience working in high-growth, high-scale environments.
• Experience in Go

🚀 Why this role matters

Happening powers the technology behind Superbet’s platforms and brands, serving millions of customers. Our Game Integrations squad connects third-party providers to our core platform and ensures those experiences are reliable, scalable, and compliant.

We’re growing and scaling fast, and we need a Backend Engineer who can deliver high-quality integrations, shape engineering standards, and help accelerate how quickly new providers go live.

How we work: We’re product-minded squads with strong ownership, candid feedback, and measurable outcomes. We build, run, and continuously improve the tech that powers Superbet’s customer experience.

What you’ll do

• Build integrations end-to-end - design contracts, implement services, write tests, and ship with confidence.

• Own reliability - define SLIs/SLOs, set up observability (metrics, logs, traces), and join on-call.

• Keep systems healthy - tackle production issues, reduce tech debt, and simplify through pragmatic refactors.

• Work across boundaries - collaborate with Product, Compliance, SRE, Data, Security, and external partners to keep delivery smooth.

• Level up the team - mentor more junior teammates through sharp code reviews, pairing, and knowledge sharing.

🛠️ Tech we use

• Node.js + TypeScript (backend services & integrations)

• Kubernetes (K8s) in production, CI/CD pipelines, containerized deployments

• REST APIs with versioning & backward compatibility

• Observability stack → metrics, tracing, logging, dashboards, and alerts

What we’re looking for

• 3+ years building backend systems (ideally integrations) with Node.js + TypeScript

• Event-driven systems (Kafka) and low-latency/high-throughput workloads

• Solid production experience with Kubernetes and CI/CD pipelines

• Strong background in API design (REST) and maintaining compatibility at scale

• Focus on testing & quality (unit, integration, QA collaboration)

• Ability to write clear docs and status updates that keep teammates aligned

Nice to have  

• Experience with Nest.js

• Gaming/fintech/e-commerce integrations (wallets, catalogs, identity, compliance)

• Experience in regulated environments with staged rollouts

🚀 Why this role matters

Happening powers the technology behind Superbet’s platforms and brands, serving millions of customers. Our Game Integrations squad connects third-party providers to our core platform and ensures those experiences are reliable, scalable, and compliant.

We’re growing and scaling fast, and we need a Backend Engineer who can deliver high-quality integrations, shape engineering standards, and help accelerate how quickly new providers go live.

How we work: We’re product-minded squads with strong ownership, candid feedback, and measurable outcomes. We build, run, and continuously improve the tech that powers Superbet’s customer experience.

What you’ll do

• Build integrations end-to-end - design contracts, implement services, write tests, and ship with confidence.

• Own reliability - define SLIs/SLOs, set up observability (metrics, logs, traces), and join on-call.

• Keep systems healthy - tackle production issues, reduce tech debt, and simplify through pragmatic refactors.

• Work across boundaries - collaborate with Product, Compliance, SRE, Data, Security, and external partners to keep delivery smooth.

• Level up the team - mentor more junior teammates through sharp code reviews, pairing, and knowledge sharing.

🛠️ Tech we use

• Node.js + TypeScript (backend services & integrations)

• Kubernetes (K8s) in production, CI/CD pipelines, containerized deployments

• REST APIs with versioning & backward compatibility

• Observability stack → metrics, tracing, logging, dashboards, and alerts

What we’re looking for

• 3+ years building backend systems (ideally integrations) with Node.js + TypeScript

• Event-driven systems (Kafka) and low-latency/high-throughput workloads

• Solid production experience with Kubernetes and CI/CD pipelines

• Strong background in API design (REST) and maintaining compatibility at scale

• Focus on testing & quality (unit, integration, QA collaboration)

• Ability to write clear docs and status updates that keep teammates aligned

Nice to have  

• Experience with Nest.js

• Gaming/fintech/e-commerce integrations (wallets, catalogs, identity, compliance)

• Experience in regulated environments with staged rollouts

Thousands of hotels, resorts, and casinos around the world depend on Duetto’s platform to run their revenue strategy — and you’ll be one of the people making sure it never lets them down. As a Senior DevOps Engineer, you’ll own the infrastructure that powers our global SaaS platform: designing for scale, building for reliability, and driving the kind of security-first culture that keeps us ahead of the curve. If you thrive in complex cloud environments, love solving hard problems, and want your work to have real, tangible impact — this is the role.

What makes us different?

Duetto is the hospitality industry’s leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world’s first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability.

Trusted by clients ranging from independent boutique hotels to global chains, we’ve been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we’re accelerating our investment in AI — and we’re genuinely passionate about the industry we serve. We build products we’re proud of, for customers we care about.

What you’ll be doing

• Design and implement robust, scalable AWS infrastructure — supporting key system migrations, platform growth, and the reliability our customers depend on.
• Own the reliability, performance, and security of our production environment: high uptime, rapid incident resolution, and proactive capacity planning.
• Build and maintain CI/CD pipelines, deployment automation, and infrastructure-as-code using Terraform, Terragrunt, and Chef.
• Monitor system health using enterprise observability tools (Prometheus, Grafana, DataDog), defining metrics and response playbooks that get ahead of incidents before they happen.
• Lead security-first practices across the infrastructure estate — proactively addressing vulnerabilities and driving SOC 2 compliance.
• Partner with engineering teams to integrate operational requirements into the development lifecycle and align on architecture decisions.
• Champion AI adoption within DevOps and SRE workflows, evaluating tooling that increases team velocity and reduces toil.
• Respond to on-call incidents with urgency — troubleshoot complex issues, lead detailed root cause analyses, and implement fixes that prevent recurrence.

What we’re looking for

You may be a great fit if you have:

• 5+ years in a DevOps, SRE, or infrastructure engineering role.
• Hands-on AWS experience across IAM, VPC, EC2, ELB, RDS, S3, Lambda, API Gateway, Secrets Manager, KMS, CloudWatch, and CloudTrail — including multi-account management and SSO.
• Proficiency with Terraform for infrastructure-as-code, plus experience with configuration management tools like Chef or Ansible.
• Experience with CI/CD tooling including GitHub, GitHub Actions, JFrog Artifactory, and Jenkins, with familiarity with GitOps methodologies.
• Strong working knowledge of enterprise monitoring platforms — Prometheus, Grafana, or DataDog.
• Solid troubleshooting skills and a track record of leading root cause analyses and implementing durable fixes.
• Proficiency reading Java, Ruby, Bash/Zsh, HCL, Python, and JavaScript.
• Experience with SOC 2 compliance and security-first infrastructure practices.
• Comfort with a weekly on-call rotation.

Strong candidates may also have:

• Experience with container and orchestration technologies — Docker, ECS, or EKS.
• Experience migrating workloads from on-prem or colocation environments to AWS.
• Familiarity with Windows Server, SQL Server, IIS, and .NET environments.
• Experience administering and synchronising MongoDB replica sets.
• Knowledge of ISO 27001, Layer 7 load balancing, or Terragrunt.
• Background in hospitality technology.
• A degree in Computer Science or a related field — or equivalent experience.

Why Duetto?

• Infrastructure that matters — your work directly underpins a platform that hotel operators around the world rely on every day. The stakes are real, and so is the satisfaction.
• AI is how we work — we’re not just talking about AI adoption; we’re actively investing in it across every function, including DevOps. You’ll have space to evaluate and implement tooling that makes a genuine difference.
• A team that moves fast — you’ll report into the Senior DevOps Manager and work alongside engineers who are serious about craft, reliability, and continuous improvement.
• Growth with purpose — backed by GrowthCurve Capital, we’re scaling our platform and our team. There’s a lot being built here, and senior engineers have real influence over how it’s done.
• Come as you are — we’re a diverse, distributed team that values different perspectives and builds inclusively.

The details

Location:  Croatia

Work model:  Remote

Reports to:  Senior DevOps Manager

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

We’d love to hear from you — even if you don’t tick every box. Diverse perspectives and non-traditional paths make our team stronger. Apply and let’s talk.

#LI-REMOTE

• Develop and maintain reusable, maintainable, and high-quality code for our Android applications.
• Ensure code is optimised for performance, scalability, and security.
• Collaborate closely with the product team to conceptualise, design, and implement new features and innovative experiments.
• Actively participate in brainstorming sessions, providing technical insights to shape product ideas.
• Contribute to the continuous improvement of our technology stack, adopting best practices and exploring new tools and frameworks.

• Develop and maintain reusable, maintainable, and high-quality code for our Android applications.
• Ensure code is optimised for performance, scalability, and security.
• Collaborate closely with the product team to conceptualise, design, and implement new features and innovative experiments.
• Actively participate in brainstorming sessions, providing technical insights to shape product ideas.
• Contribute to the continuous improvement of our technology stack, adopting best practices and exploring new tools and frameworks.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects.

As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
• Exposure to streaming data platforms like Kafka
• Contributions to open-source ML projects

THE ROLE 

The Senior Application Security Engineer is a key member of Cognism’s Information Security Team, reporting into the Application & Infrastructure Security Manager. Your mission is to embed security by design across our engineering and product organization by integrating modern application security practices throughout the full development lifecycle. We focus on building secure, scalable, and resilient systems while enabling the business to innovate quickly and safely. It is to drive a culture where the fastest path for our engineers is the securest path. 

You will work closely with Product, Engineering, Architecture, and Data teams to understand risks within our platform, including risks introduced by AI powered features, and ensure the right controls, guardrails, and security patterns are built into the product at its inception – all the while ensuring a balanced approach to the product experience that our thousands of large global enterprise customers use every day. 

This role is ideal for a senior IC who is technical, collaborative, and pragmatic, with the ability to influence engineering teams while driving hands on improvements to Cognism’s secure SDLC. 

KEY RESPONSIBILITIES 

Security by Design & Product Integration 

• Partner with Product, Web and Data Engineering teams from the ideation stage to ensure security requirements are considered early in feature and model design.
• Translate product and application risks into actionable security controls, making recommendations repeatable to build guardrails and guidance that product, design, and engineering teams can apply as they scale and build the products in the teams they own.
• Help shape security acceptance criteria and guide engineering teams during design reviews and backlog planning. 

Application Risk Assessment & AI Security 

• Identify and assess application risks across Cognism’s SaaS platform, data processing pipelines, including emerging risks associated with AI/ML capabilities.
• Contribute to AI feature reviews and participate in AI risk assessments to ensure responsible and secure use of models, in a way that balances the need to innovate and challenge the status quo in AI implementation.
• Assess and pragmatically recommend mitigations for security risks in data pipelines, model-training workflows, feature stores, and ML systems, ensuring strong controls for data access, data lineage, model integrity, and protection of sensitive datasets. 

Secure SDLC & DevSecOps Enablement 

• Partner with our engineering and platform team to embed security guardrails into our software development lifecycle and agile engineering workflows.
• Partner with engineering teams to integrate and optimize security tooling into CI/CD pipelines (SAST, SCA, DAST, container scanning, IaC scanning).
• Drive automation and developer-friendly security processes that minimize friction and support rapid delivery. 

Threat Modelling & Architecture Support 

• Conduct and facilitate a self-serve, risk-driven approach to pragmatic threat modelling sessions for new features, services, and AI components.
• Conduct threat modelling for data architectures, including ingestion, transformation, storage, streaming, and ML model deployment patterns, ensuring data confidentiality, integrity, and responsible use.
• Provide hands-on application security guidance to engineering teams, helping them implement secure APIs, microservices, data flows, and integrations.
• Maintain and expand Cognism’s secure coding standards, guidance, and reusable security patterns. 

Application Security Testing & Engineering 

• Perform hands-on security testing (manual and automated) for web applications, microservices, APIs, and cloud components.
• Plan, coordinate, and oversee penetration tests, red team exercises, and third-party security assessments, ensuring findings are addressed and tracked.
• Validate findings, assist with prioritization, and partner with engineering teams on remediation strategies. 

Collaboration, Education & Influence 

• Work directly with product squads, acting as a trusted advisor and embedded security partner. Take the time to understand what other teams are working on, what business priorities are, and partner with teams to recommend risk mitigations that balance risk with opportunity and that take into account the threat landscape. 
• Deliver security training, workshops, and guidance to improve engineering teams’ security maturity.Communicate security risk and tradeoffs clearly and constructively to technical and nontechnical stakeholders. 

CORE COMPETENCIES 

• Strong technical depth in application security, cloud security, and secure development.
• Understanding of modern data stack components (e.g., data pipelines, feature stores) and the ability to collaborate effectively with data practitioners.
• Deep understanding of communication protocols used for web development is a must-have.
• Hands on experience with web application development, specifically for back-end development is a must-have competency. 
• Risk-Based Prioritization: Ability to distinguish between theoretical security risks and actual business threats, demonstrating a "risk-driven" rather than "compliance-driven" mindset. Comfortable balancing security risk with product and commercial realities.
• Contextual Communication: Capacity to translate complex technical vulnerabilities into business-impact stories that resonate with non-technical stakeholders and product owners. 
• Collaborative Conflict Resolution: Proven track record of approaching engineering friction with transparency and pragmatism, balancing a firm stance on security with a deep care for the developer experience. Pragmatic problem solver with a growth mindset and bias toward action.
• Architectural Empathy: Ability to put yourself in the position of your users (the engineers) to build security guardrails that are repeatable and embedded into existing workflows rather than added as hurdles. 

EDUCATION & EXPERIENCE 

• 5–10+ years of experience in Application Security, Product Security, or Security Engineering roles.
• Strong experience securing cloud native SaaS platforms (AWS preferred) and Data pipelines. 
• Handson experience with secure coding, application testing, and CI/CD security automation.
• Experience working closely with engineering and product teams in agile environments.
• Familiarity with security frameworks such as OWASP ASVS, OWASP Top 10, NIST, ISO 27001/2.
• Experience evaluating and securing AI/ML enabled features is a strong advantage.
• Experience in SME or high-growth SaaS environments preferred.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
• Exposure to streaming data platforms like Kafka
• Contributions to open-source ML projects

As a Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
• Exposure to streaming data platforms like Kafka
• Contributions to open-source ML projects

As a Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
• Exposure to streaming data platforms like Kafka
• Contributions to open-source ML projects

About Vumedi:

Vumedi is the largest video education platform for doctors worldwide, dedicated to advancing medical education through innovative video-based learning. Our mission is to empower healthcare professionals by providing them with access to the latest clinical knowledge and surgical techniques from experts around the globe. We curate a vast library of high-quality educational content, enabling users to enhance their skills, stay informed about industry trends, and improve patient outcomes. We are headquartered in Oakland, CA, and have additional offices in Minneapolis, MN, and Zagreb, Croatia. 

We're hiring a Senior DevOps Engineer to lead the development of our digital platform and products at this critical stage of Vumedi’s growth. 

Why join Vumedi right now?

• Build technology that matters in a fast-scaling Silicon Valley digital healthcare company: Your work directly impacts how doctors across the world learn and make decisions that save lives.
• Grow as we grow: Be part of a company in an accelerated growth phase, where expanding teams, products, and markets create real opportunities for ownership, leadership, and career progression.
• Build with AI: Work on applied LLM systems - from intelligent search to AI-driven content agents - and shape how AI transforms medical knowledge delivery.
• Own your craft end-to-end: Take full responsibility for building systems that scale globally and power mission-critical workflows.
• Collaborate globally: Join a world-class team of passionate engineers on modern tech stack which will further drive your career development.
• Have real product impact: Influence the direction of product development by collaborating closely with product and leadership teams.

About the role:

We are looking for a Senior DevOps Engineer to join our engineering team and take ownership of our infrastructure, deployment processes, and overall platform reliability. You will work closely with backend and data teams to support a growing video and data platform used by millions of healthcare professionals worldwide.

In this role, you will focus on improving our CI/CD pipelines, system reliability, and developer experience, while helping scale our cloud infrastructure in a secure and cost-efficient way. You will work extensively with AWS services (compute, storage, networking, IAM, monitoring) and help ensure our systems are reliable, observable, and well-architected.

You’ll also support and enable emerging AI/ML and LLM-powered systems used for large-scale medical content processing, helping build and operate the infrastructure required for these workloads. This includes improving data pipelines, optimizing resource usage, and ensuring production-grade reliability of AI-driven services.

This is a high-impact role with a broad scope—from supporting production systems and data pipelines to driving long-term improvements in how we build, deploy, and operate our platform, with strong ownership and autonomy in shaping DevOps practices.

What you will do:

• Own and improve our infrastructure, CI/CD pipelines, and deployment processes across multiple environments
• Work with AWS services (compute, storage, networking, IAM, monitoring) to ensure scalable, secure, and reliable systems
• Collaborate closely with backend and data teams to support production systems, data pipelines, and overall platform reliability
• Continuously improve developer experience by streamlining workflows, reducing friction, and enabling faster, safer deployments
• Contribute to improving security practices, access control, and compliance of our infrastructure
• Automate infrastructure and workflows using Python 
• Improve observability by implementing and maintaining monitoring, logging, and alerting systems
• Troubleshoot production issues, participate in incident response, and implement long-term fixes to improve system stability
• Identify and drive improvements in performance, scalability, and cost efficiency across the platform
• Support and scale AI/ML and LLM-based systems, ensuring reliable infrastructure for data processing and content classification workloads

Who you are: 

• You have 5+ years of experience in DevOps, SRE, or infrastructure engineering, with a strong focus on cloud-native environments (preferably AWS)
• You have managed cloud infrastructure (networking, IAM, compute, storage) with a strong understanding of security best practices and cost optimization
• You have experience building and maintaining CI/CD pipelines to support rapid, reliable software delivery across multiple environments
• You are comfortable writing Python for automation, scripting, and building internal tooling to improve infrastructure and developer workflows
• You have a strong understanding of monitoring, logging, and observability (e.g., Datadog, Prometheus, CloudWatch), and proactively identifying and resolve issues
• You are comfortable debugging production issues across systems and collaborating with engineering teams to resolve them
• You are proactive, take ownership, and enjoy working in environments with high autonomy and evolving processes
• You communicate clearly and collaborate effectively with engineers, product managers, and other stakeholders
• You are curious and motivated to learn, especially in areas like AI/ML infrastructure and large-scale systems

Required Qualifications:

• 5+ years of experience in DevOps, Site Reliability Engineering, or infrastructure-focused roles
• Proven experience designing and operating scalable, reliable, and secure cloud infrastructure (preferably AWS) in production environments
• Strong understanding of cloud security best practices (IAM, network security, secrets management), preferably within AWS
• Proficiency in Python for automation, scripting, and tooling
• Hands-on experience building and maintaining CI/CD pipelines
• Experience with monitoring, logging, and alerting tools (e.g., Datadog, CloudWatch, Prometheus)
• Experience working in a Linux-based environment
• Ability to drive infrastructure and DevOps strategy, balancing scalability, reliability, and cost
• Experience working cross-functionally and influencing engineering teams on best practices and architectural decisions
• Strong ownership mindset with the ability to operate autonomously in ambiguous environments

Preferred Qualifications:

• Experience supporting or scaling AI/ML or LLM-based systems in production
• You have worked with containerized applications (Docker) and are familiar with orchestration concepts (Kubernetes or ECS is a plus)
• You are familiar with Infrastructure as Code principles (e.g., Terraform) and have experience implementing Infrastructure as Code from scratch in existing environments
• You have experience working with or supporting backend systems and data platforms (e.g., Postgres, Airflow is a plus)
• Background in backend engineering or software development
• Experience working in a fast-paced startup or scale-up environment
• Experience leading and mentoring engineers, while contributing to team-wide best practices

You can expect:

The base salary range for this role is determined by a number of factors, including but not limited to skills and scope required, unique relevant experience, and job-related skills.

Cash salary is but one component of our compensation package. It’s inclusive of base salary, education budget, supplemental health insurance, free meals allowance, work from an alternative workplace allowance, occasional awards - Christmas bonus, and an annual bonus.

We also offer stock options as part of our compensation package, giving you the opportunity to share in the long-term success and growth of the company.

This is a hybrid role, working 3 days a week (Monday, Wednesday, and Friday) in our Zagreb office.