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We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructuresomeone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacksits about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakesdesigned for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

We are seeking a visionary and hands-on QA Lead to establish and lead our new, centralized Engineering Quality function.

Your mission is to act as the centralized muscle that researches, defines, implements, and promotes engineering excellence across the company. You will own the quality strategy and enable its adoption through tooling, guidance, and hands-on support, transforming high standards into a company-wide reality.

This is a high-impact role for a leader who is passionate about building robust systems and fostering a culture of excellence.

What Youll Do: Scope & Responsibilities:

As the Engineering Quality Lead, you will be empowered to not only define our quality standards but also to enforce them and implement the solutions needed to achieve them.

Strategy & Vision: Own the company-wide engineering quality strategy. Define, measure, and report on key quality benchmarks and success metrics (KPIs) such as test coverage, Continuous Integration (CI) health, and performance signals.
Tooling & Standards: Research, evaluate, and standardize the tools and best practices for the entire software development lifecycle (SDLC). This includes static code analysis, linters, test coverage, logging, telemetry, instrumentation, and performance tracking.
Drive Adoption & Enablement: Lead the charge in driving the adoption of new standards. You will achieve this through a combination of clear guidance, enablement sessions, and hands-on development alongside product line engineers.
Cultural Leadership & The Quality Guild: Establish and lead the Quality Guild, a cross-company community of engineers passionate about quality. You will identify and mentor these Ambassadors to act as local champions, scale your influence, and create a bottom-up movement of engineering excellence.
Data-Driven Improvement: Continuously report on quality signals to leadership and recommend strategic investments based on measurable gaps and improvement trends.

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

We are seeking a Senior Software Architect to lead and shape the architectural vision of our SaaS healthcare platform, guide the adoption of cutting-edge AI technologies, and ensure our solutions remain scalable, secure, and future-ready.
This is a hands-on, strategic leadership role that combines visionary system design, proof-of-concept development, and AI-first innovation enablement.
Responsibilities:
1. Architectural Leadership
Define, communicate, and evolve the platforms architectural vision to ensure alignment with business goals.
Lead high-level design discussions and decisions for new and existing products.
Establish and maintain architectural principles, standards, and patterns across all engineering teams to ensure consistency and coherence.
Drive cloud-native architecture in AWS with a strong focus on scalability, availability, performance, and cost efficiency.
2. Innovation & Emerging Technology
Build POCs and pilots for new solutions, frameworks, and AI capabilities.
Evaluate emerging trends in AI, LLMs, MCPs, agents, and developer productivity tools, ensuring strategic adoption where relevant.
Initiate projects/features to solve widespread problems (including work with Support, DevOps, Infosec)
3. AI Tooling Evangelism
Spearhead engineering-wide adoption of AI-assisted development workflows, including developer productivity tools, code copilots, automated quality checks, and automated documentation.
Define best practices, guidelines, and governance for AI usage in development (e.g., Cursor configuration rules, prompt engineering standards).
Educate and mentor teams on effective AI utilization for engineering, product, and operational tasks, taking into account security, costs, and compliance.
4. Technical Governance & Best Practices
Overall ownership of the system scalability, COGS, and stability of the Navina product(s)
Define standards for coding, testing, CI/CD, and monitoring.
Enforce architectural and design reviews for key initiatives.
5. Cross-functional Collaboration
Work closely with Engineering, Product, Data Science, DevOps, and Security teams to deliver well-architected solutions.
Communicate complex technical concepts to non-technical audiences, including executives and external partners.

As a Platform Team Lead , you will lead a critical cross-functional team focused on building and evolving the core infrastructure that powers our Big Data, Marketing Tech, CRM, and Data Science initiatives.

You will drive technical strategy, mentor engineers, and work closely with R&D, Product, and Data Science teams to deliver high-performance, scalable, and innovative platform solutions.




What You'll Be Doing

Lead and grow a high-performing platform engineering team.
Design, develop, and maintain scalable backend systems, ensuring stability, performance, and operational excellence.
Build core services and infrastructure that enable Marketing, Data Science, CRM, and Engineering teams to move faster and smarter.
Drive platform initiatives around Big Data processing, event-driven architectures, and distributed systems.
Partner with stakeholders across the company to understand evolving business needs and translate them into technical solutions.
Champion innovation by evaluating and integrating new technologies, frameworks, and practices that elevate our product and internal capabilities.
Maintain a high bar for code quality, security, and scalability.
Provide hands-on technical leadership guiding design, code reviews, and system architecture discussions.
Foster a culture of learning, collaboration, and continuous improvement.

Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

we are looking for a Senior Data Engineer
What You'll Do:

Shape the Future of Data - Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

We are looking for a DevOps DevOps Engineer to take ownership of our Cloud Infrastructure and Platform Engineering strategy, enabling high-scale, cutting-edge GenAI products running across 40+ Kubernetes clusters on GCP and AWS.
This role is a hands-on engineering , requiring deep expertise in cloud-native technologies, Kubernetes at scale, and modern DevOps principles. You will work closely with engineering teams to design and implement scalable infrastructure solutions, optimize developer workflows, and ensure reliability and efficiency across our platform.
Role and Responsibilities:
Cloud & Kubernetes Expertise: Design and implement highly scalable multi-cluster Kubernetes environments across GCP & AWS.
Developer Experience & Enablement: Lead the development of self-service tools and automation that improve efficiency for R&D teams.
Incident & Reliability Engineering: Work with engineering teams to optimize cost, performance, and reliability of production infrastructure through monitoring, capacity planning, and scaling strategies.
Security & Governance: Contribute to best practices for RBAC, IAM, cloud security, and compliance while ensuring infrastructure reliability.
Automation & Infrastructure as Code: Drive adoption of GitOps workflows and Infrastructure as Code (Terraform, Helm, Crossplane) to enhance automation and consistency.
Mentorship & Team Growth: Provide technical mentorship within the platform engineering team and contribute to knowledge-sharing across R&D.
Cross-Team Collaboration: Work closely with engineering teams to align cloud infrastructure goals with business needs and reliability requirements.

we are building an internal carrier-grade testbeda cloud-native platform that spins up realistic ISP-level topologies on Azure AKS so every engineer can validate new routing features straight from the monorepo. As Network Simulation Platform Lead you will architect, code and operate this infrastructure, weaving it into our GitHub Actions → Argo CD pipeline and mentoring a small DevOps-minded team.
What you will do
Design & build the platform develop Python services, Kubernetes operators and Temporal/Airflow workflows that simulate BGP, EVPN, fail-overs and traffic storms.
Own cloud & container operations deploy, scale and troubleshoot high-throughput networking workloads on Azure AKS; craft custom Docker images and automate resource lifecycle management.
Integrate with CI/CD plug the simulation framework into our nx-based monorepo using GitHub Actions and GitOps with Argo CD; provide one-click, self-service environment spin-up/down for development and testing.
Champion DevOps practices manage Helm/kubectl manifests, secrets, observability hooks and automated cleanup; keep infra-as-code tidy and reviewable.
Lead the team mentor 4-6 engineers, run design reviews, pair on complex infra problems and uphold high standards for code quality and security.
Collaborate cross-functionally work daily with feature developers, networking architects and QA automation engineers to embed simulation hooks directly into everyday workflows.

we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online.
Our unique data and solutions empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies.
In 2021, we went public on the New York Stock Exchange, and we continue to reach new heights! Come work alongside across the globe who are bright, curious, practical and good people.
What Youll Do:
Youll be part of the group responsible for main products. You will impact the work of developers in the group by designing, building and maintaining the core infrastructure of our solution and leading the research and development of new technologies as well as maintaining code standards and practices.
What does the day to day of Infrastructure Engineer at look like:
You will be working on core B2B platform that serves tens of thousands of customers, serving hundreds of terabytes in production. Our backend engineers are responsible for the entire data lifecycle - from our endless datatlakes, through choosing the right serving methods and databases, all the way to our api services.

Your role will include:
Design and implement scalable backend services and libraries that are reusable and maintainable, serving as the foundation for various applications across the company.
Build and maintain tools that streamline development workflows, enabling product teams to focus on delivering business value.
Define and promote best practices for code quality, performance, and reliability, ensuring healthy production environments and rapid development cycles.
Lead the adoption and integration of AI tools to assist in code generation, testing, documentation, and debugging, thereby accelerating development processes.
Perform proof-of-concepts (POCs) on emerging technologies, including AI agents and platforms, to assess their applicability and benefits to our development ecosystem.
Drive cross-team technical projects aimed at improving infrastructure scalability, reliability, and developer experience.
Analyze and resolve complex production issues, ensuring minimal downtime and optimal performance.
Contribute to the evolution of our system architecture, ensuring it supports rapid development and scaling needs.