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We're looking for an experienced Software Engineer to join our Data Platform Group. In this key role, you will build the company data platform: cloud-based microservices and data pipelines that process on the order of 1M records/sec at low latency. Because the platform is the foundation other groups build on, your work has a direct impact on our customers and enables engineering, product, and research teams across the organization.
The Lakehouse team owns the data itself - how it is stored, organized, retained, and served. We own our analytical storage layer, the batch processing built on top of it, and the APIs through which customers and the rest of the company consume data. If you enjoy the problems that only appear at petabyte scale - physical data layout, query performance, storage cost, and retention - this is the role.

Responsibilities:
End-to-end ownership of our large-scale analytical storage layer: data modeling, schema and table design, partitioning, retention, and query performance.
Design and develop the batch processing layer over our data lake using Spark on EMR (Java and PySpark).
Build and evolve Java/Spring Boot services that expose our data through well-defined APIs to customers and to consumers across the company.
Own performance and cost: query optimization, file layout and compaction, cluster sizing, and storage efficiency at scale.
Research new technologies in the lakehouse and analytical-storage space and adapt them for use in our product.
Work closely with product, DevOps, and security teams.

We're looking for a Senior Backend Engineer to join our R&D team. You will work closely with our product team to build our unique product offering. As a Senior Backend Engineer, you will be responsible for building complex backend designs that are both scalable and fault-tolerant, developing our data ingestion pipeline and introducing new analysis engines.


What You'll Be Doing
Design, develop, test, deploy, maintain and improve the software.
Youll have your domain of expertise in which you'll assist the product team with future directions, lead the technology and cooperate with other engineers.
Youll develop backend services that integrate with and ingest data from various cloud providers that store sensitive data.
Youll build pipelines that analyze, classify, correlate and process this data.
Youll build systems that detect anomalies in the ingested data for alerting the customer, that automatically resolve issues and that generate sophisticated yet easily consumable insights arising from the processed data.
Youll have end-to-end responsibility from the technical design phase up to making sure the system is scalable and can meet high customer demands in production.
Youll identify and solve for bottlenecks within our software stack.
Youll bring innovation to the product
Youll work in an agile environment that focuses on high velocity and responds quickly to new insights.
As an all-around player, you'll work closely and at a high pace with other engineers, product, design, and other internal key stakeholders, as well as have a direct line of sight into how your work solves real-world problems for our clients and accelerates our business.

We are looking for a passionate and experienced Software Engineer to join our Networking Group.
In this role, you will play a key part in developing our cloud-based, proprietary networking and security management solutions.
You will also design and implement highly scalable processes for gathering and analyzing real-time network statistics, events, and large-scale data.

Responsibilities:
End-to-end backend development: from processing large-scale data to designing efficient microservices.
Develop and enhance high-performance, scalable services.
Improve the reliability, security, and scalability of existing infrastructure.
Work closely with cross-functional teams including Product, Data, Security, and UX.
Research and adopt new technologies to improve our products.

Were looking for an experienced Software Engineer to join our RBI (Remote Browser Isolation) team. In this critical role, you will take part in building a new SaaS product from scratch to production and solve architectural and engineering challenges. You will be building highly scalable solutions, providing infrastructure and value to a new asset management product.

Responsibilities:

Develop a new SaaS product from scratch to production, and participate in defining the specifications, architecture, and other tech-related areas of the project.
Take ownership of end-to-end development, from processing large-scale data to building backend services that power web interfaces.
Work closely with multiple stakeholders - Product Management, Research, SOC and NOC services, and Automation teams.
Design and implement enterprise platform solutions.
Research new technologies and adapt them for use within the company's products.
Collaborate with multiple development teams to deliver scalable, high-quality solutions.
Participate in code reviews, architectural discussions, and continuous improvement of engineering practices.

Were building a secure, high-performance Enterprise Browser that integrates deeply with the Cloud and delivers exceptional usability, security, and manageability for enterprise users. We are looking for a talented Software Engineer with deep systems experience and a passion for modern, secure browser engineering.

Responsibilities:

As a Software Engineer on the Enterprise Browser team, you will:
Design, implement, and maintain core browser components written in modern C++ / Rust / TS, focusing on performance, security, and stability in a multi-threaded environment.
A passion for solving problems and providing workable solutions.
Collaborate across teams (product, UX, backend engineering, security) to define specifications and deliver new features.
Optimize performance and memory usage for complex browser subsystems.
Participate in all phases of the development lifecycle, from design and prototyping to testing, release, and continuous improvement.
Ensure code quality and reliability via unit/integration testing, code reviews, and automated CI pipelines.
Keeping abreast of new technologies and finding opportunities to keep our technology stack up to date.
You will help shape the next generation of our enterprise browser: solving challenging problems at the intersection of security, performance, and user experience.

Who We Are: Incredibuild is the leading platform empowering developers and enterprises to radically accelerate their development cycles. We help world-leading brands like Microsoft, Citi Bank, GM, Amazon, and Adobe shorten build times, allowing for more iterations, faster product releases, and significant resource savings. Our technology streamlines and accelerates everything from compilation to release automation, dramatically expediting time to market for our clients. You aren’t just "fixing CI/CD pipelines" - you are building a robust Internal Developer Platform (IDP) and creating the tools that enable our engineers to ship high-performance code at scale. If you love writing clean code and get equally excited about a perfectly orchestrated Kubernetes cluster or an elegant Terra grunt module, you’ll fit right in.
What you'll do: Architect & Build: Take full ownership of our infrastructure, from backend services to cloud resources. Empower Developers: Develop and maintain our homegrown IDP , ensuring a seamless "golden path" for engineering teams. Scale the Stack: Design and manage scalable, reliable environments using AWS, Argo CD, and Helm. Automate Everything: Build sophisticated CI/CD workflows using GitHub Actions and manage stateful infrastructure with Terra grunt. Innovate: Evaluate and integrate new CNCF tools and internal utilities to keep our platform at the cutting edge.

We are looking for a strong Backend Software Engineer to bridge the gap between our Machine Learning research team and our enterprise production systems. You will act as the technical backbone for our ML Scientists - by advising, designing and implementing the production facing features. If you are a backend expert who wants to solve complex system architecture challenges and dive into the world of ML platforms & Agentic LLM pipelines, this is the role for you - An exciting role collaborating with ML science team, data/infra team and DevOps to drive real customer impact.



As a ML Engineer, you will:



Lead ML delivery: transforming research output (code, models, ideas) into robust, scalable, low-latency microservices in production

Help architect e2e solutions to real customer pains ranging from ingestion, integration, ETLs, DB design up to low-latency services

Design, build, and maintain automated workflows for ML models, including auto-trains, benchmarking, testing, performance gating, and production deployment.

Tackle complex backend challenges: optimizing API response times, managing database connectivity and concurrency at scale, balancing accuracys drive for complex questions with the business needs of fast responsiveness by making hard technical trade-offs between customer gains and business costs.

Design and optimize data pipelines and ETL processes, connecting our Snowflake data warehouse to our training environments.

Work within our existing ML infrastructure (Kubeflow, MLflow, KServe) to ensure smooth model lifecycles and performance monitoring.

Collaborate closely with ML Scientists, guiding them on software engineering best practices without slowing down their research.

Monitor and optimize production models for performance, cost efficiency, availability, and observability.

We're looking for a System Architect to own the technical foundation end to end.

What you'll do

Own the architecture - a scalable, cloud-native system from whiteboard to production on a greenfield Azure environment you'll stand up yourself (Kubernetes-native, Everything-as-Code, GitOps, CI/CD from day one).
Work directly with our Chief AI Officer to translate complex decisioning methodologies into clean,self-service products a customer can run without a data-science team.
Lead the coding. Set the standards, make the hard calls, and write the core code yourself. You'll guide the engineers shoulder-to-shoulder - leadership by example, not by org chart, without managing them directly.
Stand up a fully agentic SDLC - building the product withAI coding agents end to end, so a small team ships like a large one.
Design the integration layer so the product plugs into each host's native agent and data surfaces - customers adopt it without leaving the tools they already use.

We are seeking an MLOps Engineer to help us grow our technical team's capabilities. The ideal candidate has relevant experience in data engineering, preferably within the AI field. Aviation industry experience would be a great addition.

You will be responsible for building and maintaining models and data pipelines that power our data science workflows. You'll play a crucial role in ensuring the accuracy, consistency, and efficiency of the data we use for model training and inference. This involves working with both structured and unstructured data from various sources, leveraging your expertise in data engineering and machine learning to create a robust and scalable system.

We are looking for an MLOps Team Leadto drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example.

You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform.

Responsibilities:

Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality.
Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production.
Stay hands-on: contribute to design and code, review work, and set engineering standards.
Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership.
Partner with R&D and other stakeholders to translate research needs into robust, scalable systems.
Help evolve the platform, including our ongoing migration from Dask to Ray.

we are transforming our internal infrastructure into a high-velocity, self-service product. This is a senior opportunity to architect the future of our platform, setting the technical standard for how we deliver services while ensuring reliability and developer independence across diverse global markets.

Responsabilities:

Self-service enablement: Build secure, automated pathways that accelerate development while keeping organizational standards intact.
Architectural modularization: Design Kubernetes-native abstractions - controllers and operators - and decouple infrastructure into independent service lifecycles that support rapid iteration.
Everything as code: Treat infrastructure, policy, and configuration with the same SDLC as application software - versioned, reviewed, tested, and CI-gated.
Proactive reliability: Own production through robust observability, clear SLOs, and high operational hygiene; define alerting that fires correctly and lead blameless postmortems that fix the system.

We are seeking an MLOps Engineer to help us grow our technical team's capabilities. The ideal candidate has relevant experience in data engineering, preferably within the AI field. Aviation industry experience would be a great addition.

You will be responsible for building and maintaining models and data pipelines that power our data science workflows. You'll play a crucial role in ensuring the accuracy, consistency, and efficiency of the data we use for model training and inference. This involves working with both structured and unstructured data from various sources, leveraging your expertise in data engineering and machine learning to create a robust and scalable system.

We are seeking an AI Full-Stack Developer to build and scale automation solutions across internal company processes using AI, LLMs, and agent-based systems. This role focuses on delivering practical automation solutions, integrating AI capabilities with internal tools, and orchestrating workflows across multiple systems, with a dynamic range of tasks that offer both quick wins and complex challenges.

Responsibilities:

Build AI-driven automation solutions using LLMs, APIs, and agent frameworks.
Develop systems to automate document processing, data extraction, and operational workflows.
Design and implement multi-step automated workflows connecting AI models and internal services.
Integrate automation solutions with internal systems such as HR, finance, legal, dashboards, and ticketing tools.
Deliver and iterate practical automation solutions swiftly, from simple GPT/AI integrations to complex workflows.
Train and support internal teams on newly built or optimized systems for strong adoption and self-sufficiency.
Collaborate with Technical Team Lead, Product Manager, and IT teams on architecture and system integration.
Communicate clearly with internal stakeholders and external partners or vendors.

We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent - but also informed.

We work with some of the most innovative teams in AI - from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.

The Role: DevOps Engineer
Managing Kubernetes clusters across multiple environments and regions

Owning infrastructure as code for all resources

Maintaining and improving CI/CD pipelines and GitOps-based deployments

Maintaining and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors

Building out monitoring, alerting, and observability

Debugging production issues across services

Managing cloud costs and capacity planning

Working closely with a small engineering team - you'd own infra, not a slice of it

We are seeking a high-performing GTM Engineer to join our team as a strategic force multiplier for our sales and marketing engines.

In this role, you will work closely with our GTM Engineering Lead to accelerate the transition from "old school SalesOps" to a modern, AI-driven Go-To-Market infrastructure.

This is an AI programming job in the field of Go-to-Market.

You will be a key developer and builder behind our AI-driven growth, turning strategy into high-performing code, autonomous agents, and scalable workflows.

Key Responsibilities

Identify high-leverage opportunities to automate manual workflows across Marketing and Sales using LLMs, autonomous agents, and modern API integrations.
Work closely with the GTM Engineering Lead to translate strategic growth initiatives into functional, AI-powered internal tools.
Design and build custom data pipelines and automations that remove friction for SDR and Marketing teams, allowing them to work smarter and move faster.
Own the development lifecycle of internal growth tools-from building and testing to shipping and iterating on production-level solutions.
Partner with Finance, Marketing, and Sales stakeholders to ensure AI deployments are scalable, secure, and measurably improve conversion rates.
Help establish ROI models and best practices for new AI-driven processes across the company.