What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.
• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Observability: 5+ years of experience working with observability tools, and defining

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organizational & Communication Skills: Self-organized with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.
• Language: English proficiency is mandatory.

#LI-Remote

#LI-DC1

AE Studio is a development, data science, and design studio that works closely with founders and executives to create custom software and machine learning solutions.

We build products, platforms, and internal ventures that increase agency for all conscious beings. We combine world-class software engineering, AI expertise, and product design to ship ambitious projects that matter.

We’re looking for a Full-Stack Developer who bridges modern web engineering with practical AI; someone who can design, build, and ship production-ready, AI-powered applications while maintaining the standards of a top-tier software developer.

What You’ll Do

• Design and ship end-to-end applications from prototype to production across frontend, backend, and cloud.
• Build clean, scalable APIs and services and integrate AI models where they create real value.
• Create AI pipelines (data ingestion, preprocessing, embeddings, retrieval, orchestration) that are reliable and maintainable.
• Engineer prompting strategies and guardrails for real-world performance (latency, cost, accuracy), not just demo hype.
• Integrate AI features into full-stack apps with robust APIs, frontend UX, and CI/CD pipelines.
• Collaborate with designers, PMs, and engineers to deliver polished product experiences.
• Continuously evaluate new AI tools/models for performance, cost, and fit.
• Write production-grade, testable, maintainable code in TypeScript/JavaScript and Python (and other languages as needed).
  
  

What We’re Looking For

• 7+ years of professional software engineering experience.
• Proven track record shipping production applications (links to live products welcome).
• Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic), embeddings, vector databases, and orchestration frameworks.
• Strong command of modern web stacks (e.g., React/Next.js, Node.js/Nest/Fastify, Python/FastAPI) and cloud infrastructure.
• Solid grasp of architecture, scalability, performance, and security.
• A bias toward shipping with best practices (testing, code reviews, monitoring/observability).
• Clear communication, self-management, and comfort in a collaborative remote environment.
• Comfortable picking up new languages and frameworks, leveraging modern AI dev tools to move faster.
  
  

What Sets You Apart

• Experience fine-tuning models or training custom models on domain-specific data.
• Contributions to open-source AI or developer tooling.
• Mature approach to prompt engineering and evaluation (beyond trial-and-error).
• Background in data engineering or MLOps.
• Passion for AI alignment, agency-increasing technologies, and ethical AI development.
  
  

If you can write prompts that work today and code that still works in two years, we want to talk to you.

Salary range from $115k/year to $185k/year (if you're based in LA). Not in the range? That's fine, you can still apply and our team may fit you in a more senior position that we're not actively hiring for right now, since we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

About us

AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.

About AB InBev Growth Group

Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.

In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft.

We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities.

About the job

We are looking for a highly skilled AI Engineer to join our team and lead the design and implementation of complex AI agents capable of reasoning, planning, and collaborating with humans and other systems. This role goes beyond building simple chatbots: you will be responsible for creating multi-agent architectures, integrating advanced LLMs, and ensuring robustness, scalability, and security in production environments.

You will work closely with product managers, data engineers, and security specialists to develop agent-based systems that handle real-world complexity at scale.

What you'll do:

• Design, develop, and deploy multi-agent AI systems for reasoning, planning, and task execution.
• Implement RAG (Retrieval-Augmented Generation) pipelines, using orchestration tools and frameworks (LangChain, LangGraph, Azure AI Foundry).
• Optimize model serving for low-latency, high-throughput inference using frameworks like KServe, Triton Inference Server, or Ray Serve.
• Build observability and evaluation frameworks to monitor agent reasoning, success rates, and failure cases.
• Collaborate with ML and data engineers to integrate structured and unstructured data sources into agent workflows.
• Apply security and alignment techniques (guardrails, prompt injection prevention, red-teaming) to ensure robust behavior.
• Work in a CI/CD environment (Azure DevOps, GitHub Actions, ArgoCD) for rapid iteration and reliable deployment.
• Participate in architectural decisions involving distributed systems, GPU usage, caching strategies, and memory management.

What you'll need:

• Strong proficiency in Python (for prototyping) and C++/Go (for performance-critical components).
• Proven experience with LLMs (OpenAI, Anthropic, Llama, Mistral, or similar).
• Practical experience with agent orchestration frameworks (LangChain, LangGraph, Semantic Kernel).
• Deep understanding of search and retrieval systems (vector databases like Pinecone, Weaviate, FAISS, Milvus).
• Knowledge of distributed systems and experience deploying ML models in Kubernetes/AKS/EKS/GKE environments.
• Familiarity with ONNX Runtime, TensorRT, or DeepSpeed for inference optimization.
• Experience with public clouds (Azure, AWS, or GCP) and infrastructure as code (Terraform, CloudFormation, or Bicep).
• Understanding of AI security (prompt injection, data leakage, adversarial testing).

Nice to have:

• Experience with multi-agent simulations (AutoGen, CrewAI, OpenAI Swarm).
• Background in red-teaming and offensive security for AI models.
• Knowledge of graph databases (Neo4j, ArangoDB) for agent memory and reasoning.
• Publications, research contributions, or involvement in open-source projects related to LLM or agent frameworks.

What We Offer:

• Performance based bonus*
• Attendance Bonus* 
• Private pension plan
• Meal Allowance
• Casual office and dress code
• Days off*
• Health, dental, and life insurance
• Medicines discounts
• WellHub partnership
• Childcare subsidies
• Discounts on Ambev products*
• Clube Ben partnership
• Scholarship*
• School materials assurance
• Language and training platforms
• Transport allowance

*Rules applied

Equal Opportunity & Affirmative Action:

AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.

The following fields are optional, but anticipate the information for your registration*.

Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. 

For more information: www.abinbev.com 

Brazil, Londrina

At Platform Science, we’re working to connect everything that moves.

Founded in 2015, we are an open IoT platform that partners with innovative fleets, application developers, vehicle manufacturers, and equipment providers in the transportation industry to deliver revolutionary solutions to supply chain professionals across the globe.

Our employees are an engaging, diverse group of people who believe in the power of great ideas. We hire people with different experiences and perspectives to build a company culture that fuels growth through innovation.

We value thoughtful actions and empathy for others. We approach challenges with resiliency and creativity, while encouraging transparency because, no matter our backgrounds or responsibilities, we are one team.cker, and Kubernetes.

What You’ll Do:

• Serve as a developer for our data analytics platform, informing technical direction, standards, and long-term strategy for data ingestion, storage, processing, and consumption.
• Partner with business stakeholders, product owners, engineers, analysts, and data scientists to design and develop highly scalable, resilient, and performant software and data architectures for both batch and streaming data pipelines.
• Collaborate closely with product and engineering teams to define and enforce governance around data models that enable complex analysis, visualization, and data science across the organization.
• Leverage our modern data stack (e.g., Snowflake/dbt), to continue to buildout, data model, cost optimize, and manage our data warehouse.
• Partner with Data Scientists to design, build, and productionize robust Machine Learning pipelines and feature stores.
• Establish data quality standards and processes to ensure data is properly filtered, cleaned, and transformed from a variety of sources to enable accurate and trustworthy analysis.
• Work directly with management and executive teams to prioritize and scope platform initiatives that align with the company's highest business and information needs.
• Mentor and coach team members on best practices, complex system design, and career growth, serving as an authoritative voice for data engineering excellence.

What We’re Looking For:

• 3+ years of progressive experience as a Data Engineer, focusing on building high-scale, production-grade data analytics platforms.
• Proficiency (3+ years) in software development, including the ability to write expert-level, maintainable, and robust code using Python and SQL.
• 3+ years designing, managing, and maintaining data warehouses (especially modern columnar databases), including expertise in dimensional data modeling and maintaining complex ETL/ELT pipelines.
• Experience working with both OLTP/OLAP relational databases and distributed data systems.
• 3+ years working with AWS services such as EC2, Lambda, S3, RDS, ECR, EKS, IAM, and IoT, specifically in the context of data infrastructure.
• 3+ years of experience working with streaming data technologies such as Kinesis, Kafka, or Storm, and designing real-time data processing architectures.
• Advanced SQL skills including performance tuning, window functions, and complex query optimization.

Great to have:

• Proven ability to design and manage CI/CD pipelines using tools like Jenkins, TravisCI, or GitLab Runners for data platform code deployment.
• Demonstrated experience using Terraform (or similar IaC tool like CloudFormation) to provision, manage, and scale cloud infrastructure, data pipelines, and platform resources.
• Hands-on experience with AWS Database Migration Service (DMS) for large-scale database migrations and continuous data replication from various data sources.
• Demonstrated technical leadership regarding all things data: mining, modeling, transformation, cleansing, validation, security, and governance.
• Exceptional communication and presentation skills, with the ability to articulate complex technical trade-offs to both technical and non-technical audiences.
• Experience building and managing a workflow management system such as Airflow, Luigi, or Prefect.
• Expertise with containerization and orchestration using Docker/Kubernetes/EKS.
• Proven experience building and optimizing serverless data pipelines (e.g., AWS Lambda, Step Functions).
• Experience with Data Build Tool (dbt) for transformation and modeling.
• Experience with Snowflake or other major columnar/cloud data warehouses.
• BS/MS in Computer Science, Engineering, or equivalent practical experience.
• Experience with Feature Store architectures (e.g., Feast, Tecton) and developing standardized feature engineering pipelines.

About the Team

At DoorDash, we’re on a mission to empower local economies — and that mission drives everything we do. What started as food delivery has evolved into a technology and logistics platform designed to help people access anything in their city, from meals to everyday essentials. We’re building the future of local commerce, and we’re looking for team members excited to be part of that journey.

Joining DoorDash means working in a fast-paced, dynamic environment where your ideas can shape products, impact millions of users, and help merchants, Dashers, and customers thrive. We value creativity, ownership, and continuous learning — and we’re committed to creating a workplace where everyone can grow their careers while making a real difference.

We also care deeply about our team’s well-being. DoorDash offers comprehensive benefits, including premium healthcare, paid parental leave, wellness reimbursements, and more — because we believe that when our people thrive, our communities thrive too.

About the Role

You will lead a team of backend engineers responsible for the design and evolution of DoorDash’s Resolution Center platform. Your focus will be on building and scaling the systems that power Credits and Refunds, operational interventions, and resolution workflows across self-help, chatbot, voicebot, and agent-assisted channels.

You will partner closely with Product, Machine Learning, Fraud, Data Science, and Strategy & Operations to define and deliver a roadmap that integrates ML-driven decisions, workflow orchestration, and strong configuration safeguards into high-volume production systems. This platform directly influences cost, fraud exposure, and customer trust. You will own the technical direction and operational excellence required to run it at scale.

You're excited about this opportunity because you will…

• Lead and grow a high-performing team of backend engineers focused on Credits & Refunds, operational resolution workflows, and policy configuration systems.
• Own the migration of resolution workflows to the unified stack, ensuring data continuity, reliability, and zero regression in production systems.
• Partner with Machine Learning teams to productionize AI-driven C&R models and integrate them safely into high-volume workflows.
• Shape the long-term architecture of a decision engine that balances personalization, fraud prevention, and business guardrails.
• Improve configuration safety by implementing validation tooling, staged rollouts, and guardrails to reduce operational risk.
• Mentor engineers in distributed systems design, experimentation frameworks, and platform excellence.
• Foster a culture of ownership, velocity, and strong cross-functional collaboration.
• Partner with Recruiting to build a diverse, inclusive, and high-caliber engineering team.

We're excited about you because you have… 

• BS, M.S., or PhD. in Computer Science or related field
• 2+ years of experience in people management, leading eading backend/platform teams of 5+ engineers
• 7+ years of industry experience
• Experience working with remote teams in different time zone(s) and fluency in English
• Extensive experience as an engineer in a fast-paced, product-focused development environment
• Experience with distributed system design, system scaling, and performance optimization
• Hands-on leadership and strong product intuition
• Humility - willing to get into the details and open to feedback
• Growth mindset - you're eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
• Adaptability, resiliency, and ability to thrive in ambiguity - things can change quickly, and you'll need to help the team evolve

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems
  
  
  

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL

About us

Radiant Security is building the most advanced AI SOC platform, featuring unbounded alert triage, investigation, and response for security teams at scale. Our platform ingests alerts from across an organization's entire security stack (SIEM, EDR, identity, cloud) and uses AI to triage, investigate, and surface what actually matters. We're replacing alert fatigue with clear signal, so analysts can focus on real threats.

We're a small, fast-moving team. We ship continuously, stay close to customers, and hold ourselves to a high standard. Our product touches the daily workflows of security teams, and decisions we make have a direct impact on how quickly threats get resolved.

Join us and boost your career with hands-on AI experience.

The Role

We are looking for a technically-adept and customer-obsessed Technical Customer Success Manager to join our team in San Francisco. This is a high-impact role designed for someone who doesn't just manage accounts, but acts as a strategic technical advisor.

The ideal candidate will bridge the gap between complex cybersecurity technology and business value, ensuring our enterprise customers successfully adopt, integrate, and scale our B2B SaaS platform. You will be the primary technical point of contact, helping customers navigate the technical nuances of our AI-powered security solutions.

What you'll do

• Lead technical implementation for new customers to ensure rapid time-to-value and seamless security stack integration.
• Serve as a technical expert, guiding customers through platform configurations and optimizing their security posture.
• Monitor usage data to identify health risks and execute success plans that drive retention and account growth.
• Act as a bridge to Product/Engineering by translating external customer feedback into actionable roadmap influence.
• Conduct technical deep-dives and business reviews, translating platform wins into clear ROI for customer stakeholders.
• Create documentation and deliver product demos to empower technical champions within the customer’s organization.
• Serve as the lead for technical escalations, partnering with Engineering to ensure swift resolution of critical issues.
• Stay current with cybersecurity trends and emerging technologies to provide informed, strategic guidance.

Things we’re looking for

• 3+ years of experience in a customer-facing technical role (e.g., Junior CSM, Sales Engineer, or Technical Support) within B2B SaaS.
• Proven experience working directly with external enterprise customers; you are comfortable being the "face" of the company.
• A strong interest in or foundational knowledge of SIEM, SOC automation, or cloud security.
• Ability to quickly learn APIs, integrations, and cloud infrastructure to troubleshoot alongside customers.
• Ability to explain technical "how-tos" clearly to both users and managers.
• A self-motivated "startup" mindset. Able to manage multiple priorities and deadlines with minimal oversight.
• Education: BSc/MS in Computer Science, Engineering, or a technical 4-year degree.
• Domain knowledge of AI/ML is a plus.

Benefits

• Generous equity package
• Unlimited PTO (take time when you need it)
• Great healthcare
• Stay Healthy subsidy (for gym and sports)

The process

We’re a startup and we’re making decision quickly. Our process is designed to give you the best glimpse of our team and allow us to evaluate your technical and culture fit.

People Screening > Manager Interview > Case > Interview with the VP of Product (where you'll present your case) > Peer Interview

Why You'll Love This Role: 

We're looking for an experienced ML Ops Engineer to join the ML/AI team at Newsela. This team works on projects ranging from classical Machine Learning to AI / Generative pipelines.  This is a hands-on role. You'll work closely with ML/AI, data and site reliability engineers to take models from prototype to production, build robust data pipelines, and keep our services running smoothly as we continue to scale.

What You'll Be Doing:

• Design and maintain CI/CD pipelines for ML model training, packaging, and deployment across our microservices.
• Manage containerized services on AWS ECS, optimizing for cost, latency, and availability.
• Automate infrastructure provisioning and service configuration with Terraform.
• Work to maintain and scale services that make use of third party LLM providers.
• Build and improve data pipelines that feed models from BigQuery, S3, and DynamoDB into training and inference workflows.
• Instrument services with observability tooling (Datadog, OpenTelemetry, Langfuse) and establish SLOs for model-serving endpoints.
• Collaborate with ML engineers to productionize new models using BentoML, FastAPI, and container-based serving.

About You:

• 2-3 years in ML Ops supporting ML/AI features, systems and workflows with 3-4 years prior experience in DevOps, CloudOps or SRE.
• Strong proficiency in Python.
• Hands-on experience with Docker containerization and container orchestration.
• Solid understanding of CI/CD for ML workflows in an enterprise production environment.
• Experience with Infrastructure as Code, preferably Terraform.
• Familiarity with cloud platforms — specifically AWS (ECS, ECR, S3, DynamoDB, CloudWatch) and GCP (BigQuery, Vertex AI).
• Experience with LLM integration and observability (OpenAI API, Google GenAI, Langfuse tracing).
• Experience building and maintaining data pipelines for ML training and feature engineering
• Familiarity with ML modeling workflows — training, evaluation, experiment tracking (e.g. MLFlow, Weights & Biases), and model versioning
• Experience monitoring and flagging model drift over time.
• Exposure to NLP/NLU models and frameworks such as Hugging Face Transformers, spaCy, or sentence-transformers
• Knowledge of vector databases (LanceDB, FAISS) and embedding-based retrieval systems
• Experience with scaling and maintaining deep learning frameworks (TensorFlow, PyTorch) in production settings
• Familiarity with classical ML libraries (scikit-learn, XGBoost, LightGBM) and model explainability tools (SHAP)
• Working knowledge of ML serving frameworks such as BentoML or similar.
• Comfort working with FastAPI or similar async Python web frameworks.

Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits

About Newsela:

Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner.

#LI-Remote

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated  Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Cross-Departmental AI Utilization: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is $6,000 - $12,500 per month (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

Compensation:

For this principal development role, with 12+ years of experience, the compensation range is  $6,000 - $12,500 per month. This range acknowledges the extensive expertise, leadership capabilities, and significant contributions expected at this level, offering a competitive salary to reflect the value of advanced skills and experience.

Interview Process

We believe transparency is important at Sezzle. Regularly providing feedback while setting expectations is part of our culture starting with the interview process. Advancement through each step is not guaranteed.

• Application submitted (you are here)
• Wonderlic test (30-40 min)
• Interview with recruiters (30 min)
• Coding assessment (~1.5 hours)
• Interview with engineers (1 hour)
• Interview with engineering leadership (30-45 min)
• Offer!

About the Role: 

We are seeking a talented and motivated best-in-class Principal Software Engineer. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

As a Principal Software Engineer with Sezzle, you will work with highly-motivated teams to tackle interesting and challenging problems across multiple areas of the organization. Your experience and guidance will help other members of the team level-up their own skills as well. You will spend your time working with AI/ML tooling to identify creative uses to fill existing and emerging gaps in the applications.

In this backend focused role, you will work closely with stakeholders from Product, Support and the business. You’ll also partner with other engineering teams to provide high-quality, scalable, and innovative solutions to internal and customer problems. Your day-to-day responsibilities will include designing, developing, and delivering new features, as well as unblocking and mentoring your teammates. Your work will generally focus on the lower level features and optimizations.

This role has both an internal and external focus, your contributions will make a meaningful difference in the day-to-day lives of your peers at Sezzle, enhancing their ability to support our business and customers, and you will have opportunities to take any feedback and iterate.

What You'll Do:

• Architect, design, and build scalable backend services and APIs primarily in Golang, leveraging AWS, RDS (MySQL/Postgres), and modern distributed patterns.
• Lead Sezzle’s AI enablement efforts, identifying opportunities to apply AI and automation to enhance developer productivity, internal tooling, and customer experiences.
• Partner with teams across the organization to integrate modern AI capabilities - Primarily around tools like Claude Code, Codex, Cursor and enhancing team productivity.
• Drive consistency and scalability across a distributed microservices architecture while maintaining performance and reliability.
• Establish and evolve engineering best practices for observability, security, and CI/CD across teams.
• Mentor engineers and champion a culture of learning, innovation, and operational excellence.
• Collaborate cross-functionally to translate business goals into technical roadmaps and deliver results that matter.

What We Look For:

• 12+ years of professional software engineering experience, including significant backend experience.
• Deployed significant changes to a production application in the past 30 days.
• Strong proficiency in Golang, with experience building and maintaining RESTful APIs.
• Experience with React JS. 
• Expertise with SQL-based RDBMS (MySQL, PostgreSQL) and experience optimizing schema and queries for performance at scale.
• Solid understanding of distributed systems design patterns (e.g., transactional outbox, event-driven architecture, queues).
• Demonstrated ability to bring new ideas forward, influence decisions, and lead complex technical initiatives.
• Bachelor’s degree in Computer Science or equivalent practical experience.

Preferred Knowledge and Skills:

• Proficiency in observability tools (Prometheus, Grafana, Datadog, New Relic).
• Experience with AWS cloud infrastructure, mainly AWS Aurora RDS, both MySQL and Postgres.
• Experience in fintech, payments, BNPL, or consumer lending - familiarity with financial compliance, credit decisioning, or transaction processing systems.
• Experience with CI/CD pipelines and containerized microservices (Docker, Kubernetes).
• Working knowledge of TypeScript, React, or React Native.
• Familiarity with AI/ML tooling (e.g., OpenAI API, LangChain, Hugging Face, or custom LLM integrations).
• Track record of shipping commercial APIs and data-driven applications in high-growth environments.
• Proven leadership in guiding technical direction, improving system reliability, and scaling engineering organizations.

About You: 

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

Sezzle’s Technology Stack:

• Languages: Golang, Typescript, Python
• Frontend: Typescript - React and React Native
• Backend: Golang
• Database: MySQL, Postgres, Elasticsearch
• DevOps & Cloud: AWS, Kubernetes
• Version Control: Git
• CI/CD: Gitlab
• Testing: Developer and AI-driven, focus on automated end-to-end, integration, and unit tests
• Open Source: Sezzle is focused on using open source, and we build what we can before buying!

What Makes Working at Sezzle Awesome? 

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators; we are skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers. We believe in surrounding ourselves with not only the best and the brightest individuals, but those that are unique and purpose-driven in all that they do. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.

#Li-remote #full-time

 The salary range for this role is $3,333 - $6,000 per month (Gross in USD)

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer II who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer II on the Applied AI team, you will take on end-to-end ownership of complex platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered platforms from scratch, developing intelligent automation and orchestration systems, and embedding proprietary AI solutions directly into customer-facing products, internal tools, and operational workflows.

You will operate in highly ambiguous problem spaces, working closely with product, engineering, and operations teams to identify opportunities where AI can drive meaningful impact — whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers ready to move beyond scoped execution and into leading solutions: shaping architecture, driving implementation, and ensuring that what is built is reliable, scalable, and genuinely useful for both external users and internal teams.

What You'll Do:

• Lead the design, development, and ownership of AI-powered internal platforms and systems, including initiatives built from the ground up.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Design and implement AI-driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
• Embed AI capabilities into customer-facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
• Build full-stack systems spanning backend services, APIs, data layers, and frontend interfaces.
• Translate ambiguous business and operational problems into scalable, maintainable, AI-enabled technical solutions.
• Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
• Collaborate closely with engineers, teams, and stakeholders across the company to identify high-impact opportunities and drive adoption.
• Participate in production support and incident response for owned systems, helping define and uphold reliability and operational best practices.
• Mentor AI team members through code reviews, design feedback, and hands-on guidance, raising the overall quality bar of the team.

What We Look for:

• 3–5 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Experience building AI-first platforms or internal products from scratch, including early architectural decisions.
• Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.
• Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine-tuning strategies for domain-specific applications.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).
• Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.
• Familiarity with cloud-native development using AWS.
• Understanding of prompt engineering, retrieval-augmented generation (RAG), and LLM application patterns.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is 2,500 - 3,333 USD  per month (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer I who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer I on the Applied AI team, you will contribute to the development of platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered features, developing intelligent automation and agentic systems, and embedding AI solutions into customer-facing products, internal tools, and operational workflows.

You will work closely with senior engineers and cross-functional teams to identify opportunities where AI can drive meaningful impact—whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers early in their AI careers who want hands-on exposure to production-grade AI systems, with opportunities to grow into greater ownership and technical leadership over time.

What You'll Do:

• Contribute to the design and development of AI-powered platforms and systems, working alongside senior engineers on complex initiatives.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Build AI-driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity.
• Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally
• Integrate AI capabilities into customer-facing products, internal tools, and operational workflows.
• Build full-stack components spanning backend services, APIs, data layers, and frontend interfaces.
• Translate business and operational problems into maintainable, AI-enabled technical solutions with guidance from senior team members.
• Apply systems thinking to ensure reliability, performance, and security across platforms.
• Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions.
• Participate in production support and incident response for team-owned systems, learning operational best practices.
• Engage in code reviews and knowledge sharing to continuously improve skills and contribute to team growth.

What We'll Look For:

• 1–3 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Exposure to building AI-powered platforms or products, including contributing to architectural decisions.
• Foundational knowledge of core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, and model evaluation.
• Familiarity with transformer architectures (BERT, GPT, etc.) and basic understanding of attention mechanisms, tokenization, and fine-tuning concepts.
• Exposure to embeddings and vector representations, including text embeddings and similarity search concepts; interest in vector databases (Pinecone, Weaviate, pgvector, or similar).
• Familiarity with NLP techniques such as text classification, named entity recognition, or semantic search.
• Familiarity with real-world agentic frameworks workflow engines (e.g., in-house automation platforms, langchain/graph, n8n, Make, or similar), with a solid understanding of how they work under the hood.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with cloud-native development using AWS.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is 2,500 - 3,333 USD  per month (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer I who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer I on the Applied AI team, you will contribute to the development of platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered features, developing intelligent automation and agentic systems, and embedding AI solutions into customer-facing products, internal tools, and operational workflows.

You will work closely with senior engineers and cross-functional teams to identify opportunities where AI can drive meaningful impact—whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers early in their AI careers who want hands-on exposure to production-grade AI systems, with opportunities to grow into greater ownership and technical leadership over time.

What You'll Do:

• Contribute to the design and development of AI-powered platforms and systems, working alongside senior engineers on complex initiatives.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Build AI-driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity.
• Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally
• Integrate AI capabilities into customer-facing products, internal tools, and operational workflows.
• Build full-stack components spanning backend services, APIs, data layers, and frontend interfaces.
• Translate business and operational problems into maintainable, AI-enabled technical solutions with guidance from senior team members.
• Apply systems thinking to ensure reliability, performance, and security across platforms.
• Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions.
• Participate in production support and incident response for team-owned systems, learning operational best practices.
• Engage in code reviews and knowledge sharing to continuously improve skills and contribute to team growth.
• Familiarity with Braze or similar consumer facing CRM platforms and/or various B2C digital marketing channels like affiliate, CTV, paid social, paid search, GEO/SEO, DSP.

What We'll Look For:

• 1–3 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Exposure to building AI-powered platforms or products, including contributing to architectural decisions.
• Foundational knowledge of core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, and model evaluation.
• Familiarity with transformer architectures (BERT, GPT, etc.) and basic understanding of attention mechanisms, tokenization, and fine-tuning concepts.
• Exposure to embeddings and vector representations, including text embeddings and similarity search concepts; interest in vector databases (Pinecone, Weaviate, pgvector, or similar).
• Familiarity with NLP techniques such as text classification, named entity recognition, or semantic search.
• Familiarity with real-world agentic frameworks workflow engines (e.g., in-house automation platforms, langchain/graph, n8n, Make, or similar), with a solid understanding of how they work under the hood.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with cloud-native development using AWS.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is $3,333 - $6,000 per month (Gross in USD)

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated AI Engineer II who is best in class, with a high IQ and a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with strong prospects for continued growth and increased ownership.

As an AI Engineer II on the Applied AI team, you will take on end-to-end ownership of complex platforms and systems that power Sezzle's AI-driven capabilities. Your work will span initiatives such as building AI-powered platforms from scratch, developing intelligent automation and orchestration systems, and embedding proprietary AI solutions directly into customer-facing products, internal tools, and operational workflows.

You will operate in highly ambiguous problem spaces, working closely with product, engineering, and operations teams to identify opportunities where AI can drive meaningful impact — whether that's enhancing the customer experience, improving decision-making, or automating complex workflows. This role is ideal for engineers ready to move beyond scoped execution and into leading solutions: shaping architecture, driving implementation, and ensuring that what is built is reliable, scalable, and genuinely useful for both external users and internal teams.

What You'll Do:

• Lead the design, development, and ownership of AI-powered internal platforms and systems, including initiatives built from the ground up with a focus on Marketing.
• Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration.
• Design and implement AI-driven features, intelligent automation, and orchestration systems that enhance customer experiences and compound productivity across teams.
• Embed AI capabilities into customer-facing products, internal tools, and operational workflows, ensuring solutions integrate naturally and deliver measurable value.
• Build full-stack systems spanning backend services, APIs, data layers, and frontend interfaces.
• Translate ambiguous business and operational problems into scalable, maintainable, AI-enabled technical solutions.
• Apply strong systems thinking to ensure reliability, performance, security, permissions, and auditability across platforms.
• Collaborate closely with engineers, teams, and stakeholders across the company to identify high-impact opportunities and drive adoption.
• Participate in production support and incident response for owned systems, helping define and uphold reliability and operational best practices.
• Mentor AI team members through code reviews, design feedback, and hands-on guidance, raising the overall quality bar of the team.

What We Look for:

• 3–5 years of professional experience in software engineering, AI engineering, platform engineering, or related roles.
• Hands-on experience designing, building, and shipping AI-powered systems into production environments.
• Strong proficiency in Python, SQL, and frontend frameworks such as React.
• Proven experience designing and owning production-grade full-stack systems.
• Experience working with distributed systems, internal platforms, or complex data workflows.
• Ability to operate effectively in ambiguous problem spaces and drive solutions with minimal direction.

Preferred Qualifications:

• Experience building AI-first platforms or internal products from scratch, including early architectural decisions.
• Strong foundation in core machine learning and data science principles, including supervised/unsupervised learning, feature engineering, model evaluation, and statistical inference.
• Experience with transformer architectures (BERT, GPT, etc.) and understanding of attention mechanisms, tokenization, and fine-tuning strategies for domain-specific applications.
• Experience developing AI-assisted or agentic systems that interact with tools, data, or workflows.
• Familiarity with embeddings and vector representations, including text embeddings, similarity search, and integration with vector databases (Pinecone, Weaviate, pgvector, or similar).
• Experience with NLP techniques including text classification, named entity recognition, semantic search, and information extraction.
• Familiarity with cloud-native development using AWS.
• Understanding of prompt engineering, retrieval-augmented generation (RAG), and LLM application patterns.
• Experience with containerized systems and orchestration tools such as Docker and Kubernetes.
• Exposure to CI/CD pipelines and modern development workflows (e.g., GitLab).
• Experience with Golang is a plus (or willingness to learn).
• Experience with Braze or similar consumer facing CRM platforms and/or various B2C digital marketing channels like affiliate, CTV, paid social, paid search, GEO/SEO, DSP.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

The salary range for this role is $50,000 - $120,000 per year (Gross in USD) 

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

About the Role: 

We are seeking a talented and motivated Sr. AI engineer who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

You will be responsible for overseeing the design, development, and deployment of machine learning models that power and enhance our financial platform. In this role, you will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment, utilizing a combination of cloud services, open-source tools, and proprietary algorithms.

Your leadership will be key in blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of our ML models. You will collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address diverse challenges in the shopping and fintech space. You’ll ensure our AI-driven features are robust, efficient, and scalable as we continue to grow.

What You'll Do:

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment.
• Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively.
• Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime.
• Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases.
• Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution.
• Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency.
• Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration.
• Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

What We Look For:

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.

Preferred Qualifications:

• Deep expertise in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

About You:

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

What Makes Working at Sezzle Awesome:

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire. 

#Li-remote #full-time

As a Sales Systems Engineer at Veeam, you will act as a trusted technical and strategic advisor to customers facing complex data resilience and cyber recovery challenges. You will engage deeply with both technical and executive stakeholders to design secure, resilient, and future-ready architectures across hybrid, multi-cloud, and SaaS environments. This role blends hands-on technical expertise with executive-level influence, driving real business outcomes through resilient data platforms.

Territory Coverage

Brazil-COM-Named-4, Brazil-COM-Inside-2.

What You’ll Do

• Lead complex pre-sales engagements, including discovery, solution design, architecture validation, and technical closure
• Translate business objectives into secure, scalable, and resilient technical architectures for customers
• Deliver high-impact technical demonstrations and executive-level presentations focused on business value and cyber risk reduction
• Design, manage, and execute proof-of-concepts (POCs) aligned to customer success criteria and operational realities
• Collaborate with sales teams, partners, product management, and engineering to influence solution architecture and customer outcomes

Technologies You’ll Work With

Hybrid Cloud, Multi-Cloud & SaaS Platforms, Virtualization Technologies, Storage Systems, Cyber Resilience & Data Protection Technologies

What You’ll Bring

• 5+ years of experience in pre-sales engineering, solutions architecture, or senior technical leadership roles within clients' environments
• Foundational understanding of AI, machine learning, and large language models (LLMs), with the ability to articulate how trusted, resilient data underpins AI initiatives.
• Proven success leading complex, multi-stakeholder sales cycles including discovery, solution design, POCs, and executive engagements
• Strong technical foundation across data resilience, infrastructure platforms, cloud services, networking, and security
• Solid understanding of data security, privacy, governance, and regulatory considerations for customers
• Excellent communication and presentation skills, with the ability to engage C-level executives and senior IT leaders

Bonus Skills

• Experience with public cloud platforms such as AWS, Microsoft Azure, or Google Cloud
• Hands-on knowledge of Windows and Linux operating systems in deployments
• Experience with virtualization platforms such as VMware vSphere, Hyper-V, or Nutanix AHV
• Familiarity with Kubernetes, containerized workloads, and cloud-native data protection
• Background working with data protection, cyber resilience, or infrastructure vendors

What You’ll Get

• The opportunity to work on mission-critical data resilience and cyber recovery challenges for customers
• High impact and visibility influencing architecture and executive decision-making
• Collaboration with experienced engineers, architects, product leaders, and sales professionals
• A fast-paced, innovative environment that values curiosity, autonomy, and continuous learning
• The ability to shape the future of data resilience across hybrid, multi-cloud, and SaaS ecosystems

What You'll get

• Onboarding kit
• Company cellphone
• Paid home Internet
• Coffee & snacks at the office
• Car allowance
• Health insurance for employee and immediate family group
• Life insurance
• Paid gym academy (TotalPass)
• Hybrid work model

#LI-CC1

Type: Contract, per-project.
Location: Remote — within LATAM with ET ±1 hour
Availability: Contractor (40 hours per week)

Job Title: Data / Platform Engineer (AWS & Data Pipelines)

We are looking for a highly motivated Data / Platform Engineer to join our team and help design, build and operate scalable data pipelines and cloud-based solutions.

In this role, you will work closely with engineering and product teams to build both streaming and batch data pipelines, contribute to system design, and help drive automation and monitoring across our data platform.

Key Responsibilities

• Design, build, maintain and primarily operate scalable streaming and batch data pipelines, with a strong focus on maintenance, monitoring, troubleshooting and continuous improvement of existing pipelines.

• Work with AWS services, including Redshift, EMR and ECS, to support data processing and analytics workloads.

• Develop and maintain data workflows using Python and SQL.

• Orchestrate and monitor pipelines using Apache Airflow.

• Build and deploy containerized applications using Docker and Kubernetes.

• Break down high-level system designs into well-defined, deliverable tasks with realistic estimates.

• Collaborate with cross-functional teams in a fast-paced and distributed environment across the US and Europe.

• Drive automation, observability and monitoring to improve reliability, performance and operational efficiency.

• Support knowledge transfer and ownership handover as part of the planned transition to the consuming team.

Required Qualifications

• Strong professional experience with Python and SQL.

• Hands-on experience with AWS, specifically Redshift, EMR and ECS. AWS experience is mandatory (other cloud providers are not considered equivalent for this role).

• Proven experience building and operating both streaming and batch data pipelines.

• Professional experience with Apache Airflow, Docker and Kubernetes.

• Ability to translate high-level system designs into actionable technical tasks and realistic estimates.

• Comfortable working in dynamic and fast-paced environments and in distributed teams.

• Strong interest in automation and monitoring.

• Strong hands-on experience with Apache Spark.

• Senior-level profile with strong autonomy, communication skills and ability to work effectively in distributed teams.

• Proven ability to transfer knowledge and support ownership handovers.

• Fluent or professional working proficiency in English (both written and spoken).

Nice to Have

• Previous experience in the telecom industry.

• Experience with machine learning systems and/or event-driven architectures.

• Experience with Apache Iceberg.
  
  (*) SOUTHWORKS only hires individuals from countries that are not blocked or sanctioned by the United States, including those identified on the United States Office of Foreign Asset Control (OFAC).

The Role You’ll Play: 

As a Staff Software Engineer for the Data Platform Engineer team, you’ll shape the backbone of our data strategy—designing scalable pipelines, championing governance, and enabling AI-ready infrastructure. You’ll lead cross-functional projects that fuel analytics, automation, and decision-making across the Playlist ecosystem. Your work will directly empower our teams to create personalized, real-world experiences for millions of users.

• Architect and optimize cloud-native data warehouse solutions that power real-time decisions and long-term strategy
• Design and scale dbt models across bronze/silver layers with a focus on data contracts, observability, and semantic consistency
• Build and maintain robust ETL/ELT pipelines using tools like Fivetran, Snowpipe, and CDC to support streaming and batch workloads
• Lead the design of infrastructure-as-code deployments with Pulumi or Terraform, driving CI/CD maturity and cost-efficient operations
• Elevate data quality with comprehensive monitoring, anomaly detection, and validation frameworks
• Collaborate across squads to align data contracts, expand shared data marts, and support machine learning enablement
• Champion data governance, ensuring privacy and compliance through PII tagging, lineage, and role-based access controls
• Drive continuous platform improvement through systematic tech debt remediation and modernization initiatives

Experience You Bring:  

• Strong expertise in data engineering, software engineering, platform architecture, or modern data warehousing
• Proficient in Python and SQL for automation, transformation logic, and data platform development
• Experience implementing observability standards, anomaly detection, and data quality validation
• Proven ability to lead complex, multi-squad initiatives and deliver scalable outcomes
• Hands-on experience with job orchestration and infrastructure as code (e.g., Pulumi, Terraform)
• Strong understanding of data modeling principles and architectural patterns such as star schemas and bronze/silver/gold layering
• Comfort mentoring engineers, influencing technical roadmaps, and advocating for best practices

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

We are seeking a Senior Data Engineer with a strong background in data engineering, ideally with hands-on experience in Google Cloud Platform (GCP) services such as Pub/Sub, Dataflow, and BigQuery. The ideal candidate will have solid proficiency in SQL and Python, along with familiarity in moving and transforming data across cloud-based data zones and streaming pipelines (ETL/ELT). Comfort with cloud services, data management, automation tools, and real-time data processing is essential. 

Role responsibilities

• Demonstrate deep knowledge of the data engineering domain to build and support non-interactive (batch, distributed) & real-time, highly available data pipelines  
• Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines  
• Provide consultation and lead the implementation of complex programs  
• Develop and maintain documentation relating to all assigned systems and projects  
• Tune queries running over billions of rows of data running in a distributed query engine  
• Perform root cause analysis to identify permanent resolutions to software or business process issues
• Implement and maintain dbt transformation models, CI pipelines, and data contracts for curated campaign, ad group, keyword, audience, and landing-page marts.
• Build and monitor data quality gates (Great Expectations and reconciliation checks) and freshness SLOs.
• Optimize BigQuery cost and performance using query tuning, storage design, and reservation strategy.
• Implement platform hardening controls including retries, dead-letter queues, DR runbooks, and support for VPC-SC and DLP validation.

Must have qualifications

To be considered for this role, you must meet the following essential qualifications: 

• Strong expertise in:   
  • Python - for building data pipelines, processing tasks, and automation  
  • SQL - Advanced SQL capabilities (nested fields, analytic functions).  
• Hands-on experience with Core GCP Data Stack:  
  • BigQuery: Expert-level SQL, performance tuning, and specifically BigQuery for advanced SQL, performance tuning, partitioning and clustering strategy, and production-grade curated marts and feature tables; working knowledge of BQML for scoring and evaluation in analytics workflows. 
  • Dataflow (Apache Beam)
  • Strong proficiency in building reliable batch and incremental pipelines for GA4/Google Ads data into BigQuery, with streaming patterns (windowing/watermarks/triggers) used when near-real-time alerting is required.
  • Pub/Sub: Experience with event-driven architecture and message queuing.  
• Hands-on experience with Visualization & BI:       
  
  • Looker Core – Advanced proficiency in LookML (not just drag-and-drop), including derived tables, explores, and Liquid syntax.  
  • Semantic Modeling: Develop robust LookML models to create a trusted layer of data governance, ensuring metrics are consistent across the organization.  
  • Dashboard Creation: Design intuitive, high-impact dashboards in Looker for two distinct audiences: Operational teams (paid search performance monitoring, anomaly triage, and optimization workflows) and Executives (ROAS, conversion efficiency, budget pacing, and channel contribution reporting). 
• Ability to independently own workstreams while collaborating closely with data science, analytics, and engineering peers in agile delivery.
• Advanced English skills 

Nice to have qualifications  

• Google Cloud Professional Data Engineer certification  
• Google Professional Machine Learning Engineer certification  
• Google Cloud Professional Cloud Architect certification  
• Bachelor’s or Master’s degree in a quantitative or technical field (e.g., Computer Science, Engineering, Statistics)    
• Working knowledge of cloud architecture components in GCP  
• Proficiency in Big Data environments and tools such as Spark, Hive, Impala, Pig, etc.  
• Proficiency in Terraform  
• Familiarity with front and back-end web application stacks and frameworks, and API design and usage (REST/GraphQL)    
• Experience leading and managing technical data/analytics/machine learning projects    
• Experience supporting data products consumed by conversational analytics surfaces (BigQuery/Looker query routing, audit logging, and row-level access patterns).

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

About us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our institutional page https://international.nubank.com.br/careers/

ML Engineering at Nubank

Data Science is essential to every part of the business at Nubank, since Day 1. Most areas of the company use data science to some extent. ML Engineers are key to connecting ML models and ML-enabled systems to the rest of our infrastructure, while making sure that they work properly, delivering value to our customers. 

As a Machine Learning Engineer, you’re expected to

• Interact with other team members to understand how to best apply data science and artificial intelligence to Nubank’s problems;
• Help monitor and maintain models and ML systems, making sure they are working well as measured by performance, operational and business metrics;
• Help deploy ML models both in batch and real-time scenarios. This may include building pipelines, constructing features and integrating models to other systems;
• Help build and maintain tooling and platforms to scale operations across multiple teams; 
• Be familiar with modeling and statistics concepts;
  
  

Our ideal candidate

• Has extensive programming experience and is familiar with modern development techniques;
• Has experience creating, deploying and maintaining ML models and ML-enabled systems using modern frameworks;
• Understands the most common failure modes in ML-enabled systems and knows how to avoid and/or mitigate those; 
• Is familiar with all stages of the ML model lifecycle, from inception to deployment and steady-state operation;
• Is familiar with cloud-based services from vendors such as AWS, GCP and Azure.
• Is familiar with software engineering and architecture principles and how they enable sustainable and maintainable systems;
• Is familiar with data engineering routines, pipelines and job scheduling frameworks;
• Is able to navigate complex mathematical and analytical environments when needed;
  
  

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
  
  

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

About Us

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

About the Role
AI Platform Team - The mission of the AI Platform team is bold: to democratize AI by empowering every Nubanker—not just Data Scientists—with safe, scalable, and accurate Machine Learning capabilities.

We are looking for a Manager who is passionate about creating solutions that push the boundaries of our current stack. You will help us move beyond basic DS work to abstract the complexities of the entire ML lifecycle—from training and deployment to serving and governance.

Why is this role open?
We are scaling. Currently, our structure has grown significantly, and to ensure the organization's health and the growth of our engineers, we are opening this position to lead a dedicated squad. You will take ownership of a team that manages the base infrastructure for the entire Data Science function at Nubank.

You'll be responsible for:
As the ML Manager for the AI Platform, you will combine technical leadership with people management. You will lead a squad of 11 Machine Learning Engineers (varying from Senior to Intern levels) and work closely with a Staff ML Engineer and a Product Manager.

• People Management: Foster a culture of feedback and growth. You will guide the development of your direct reports, conducting performance reviews and helping them navigate their careers.
• Strategic Roadmap: Translate high-level business goals into actionable technical roadmaps. You will discuss needs with stakeholders and define the "how" and "when."
• Architecture & Innovation: Explore architecture gaps and opportunities. You won't just maintain; you will challenge the team to explore complex features like scalable parallel processing and better UX for Data Scientists.
• Execution: Conduct initiatives with autonomy and diligence, ensuring we deliver value while maintaining high engineering standards.
  
  

Nubank already has well-established tools for basic Data Science work. Your challenge is to take us to the next level. You will push the frontiers of technology to handle massive scale, integrate with multiple complex systems, and democratize access to AI tools across the company.

What we are looking for
You don't need to be a hands-on coder 100% of the time, but you must have the technical depth to challenge the team and understand the ecosystem.

• Experience in Leadership: You have experience managing high-performing engineering teams, sharing feedback, and hiring/developing talent.
• Domain Expertise: Solid background in ML Engineering, AI, or Data Science, specifically with a focus on MLOps, Infrastructure, and Platform building.
• Tech Stack Familiarity: You are comfortable discussing and architecting systems involving Kubeflow, SageMaker, and Databricks.
• The "Builder" Mindset: You enjoy building software. You want autonomy to make decisions and explore edge technologies, similar to the engineering culture found in Big Tech

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Role Summary

We're looking for a Developer Experience Engineer to revolutionize the development experience at Clara by building a self-service platform that automates and simplifies infrastructure, deployments, and operations. You'll be responsible for eliminating friction in the development lifecycle, enabling engineering teams to focus on delivering business value.

Key Responsibilities

Developer Experience & Self-Service Platform

• Design and maintain a developer portal (Backstage.io or similar) as the central hub for resource management
• Build abstractions and APIs that enable developers to provision resources without manual intervention
• Implement self-service workflows for environment creation, configurations, and permissions
• Create reusable templates and blueprints for services, repositories, and pipelines

CI/CD & Automation

• Design, implement, and optimize highly automated CI/CD pipelines
• Reduce build and deployment times through intelligent caching, parallelization, and optimizations
• Implement GitOps and continuous deployment with automated rollback capabilities
• Automate testing (unit, integration, e2e) in pipelines with clear reporting
• Create advanced deployment strategies (blue-green, canary, feature flags)

Ephemeral Environments

• Design and implement ephemeral/preview environment solutions for each PR/branch
• Automate the complete lifecycle: creation, configuration, and cleanup
• Optimize costs through auto-scaling, scheduling, and garbage collection of unused resources
• Integrate ephemeral environments with code review and testing workflows

Observability & Alerting

• Implement intelligent alerting systems with noise reduction and event correlation
• Configure dashboards and SLI/SLO metrics for critical services
• Establish automated runbooks and auto-remediation for common incidents
• Integrate observability (logs, metrics, traces) into the developer portal

Infrastructure as Code & Security

• Maintain and evolve infrastructure as code (Terraform, CloudFormation, etc.)
• Implement automated security controls (policy as code, security scanning)
• Manage secrets, configurations, and access securely and with full auditability
• Apply least privilege and zero-trust principles across all systems

AI/ML Ops Integration

• Explore and implement AI tools for resource optimization and failure prediction
• Automate operational tasks using ML (anomaly detection, capacity planning, incident classification)
• Evaluate and adopt emerging AI Ops tools

Technical Requirements

Must Have

• 5+ years of experience in DevOps/SRE/Platform Engineering
• Mastery of cloud providers (preferably AWS)
• Solid experience with Kubernetes and microservices architectures
• Expertise in CI/CD tools (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
• Proficiency in Infrastructure as Code (Terraform, Pulumi, CloudFormation)
• Experience with containers (Docker, Kubernetes, ECS/EKS)
• Advanced scripting skills (Python, Bash, Go)
• Knowledge of observability tools (Prometheus, Grafana, ELK, Datadog, New Relic)

Nice to Have

• Experience with Backstage.io or similar developer portal platforms
• FinOps knowledge and cloud cost optimization
• Experience in FinTech organizations or highly regulated environments
• Familiarity with AI Ops tools (AIOps platforms, ML-based monitoring)
• Cloud certifications (AWS Solutions Architect, CKA, etc.)
• Experience with service mesh (Istio, Linkerd)
• Compliance and security knowledge (PCI-DSS, SOC2)

Key Skills

• Automation obsession: If something is done twice, it should be automated
• Product mindset: Treat internal platform as a product with "customers" (developers)
• Ability to abstract complexity: Make the complex simple for end users
• Effective communication: Document clearly, create runbooks, and educate teams
• Problem solving: Systems thinking to solve problems at their root
• Continuous improvement mindset: Constantly seek ways to optimize and simplify

What You'll Build

• Self-Service Portal: Unified interface where developers can:
  • Create new services from templates
  • Provision ephemeral environments in seconds
  • Configure alerts and dashboards with clicks
  • Request access and permissions with automated approvals
• Intelligent Pipelines: CI/CD that:
  • Detects changes and runs only relevant tests
  • Auto-deploys to production with quality gates
  • Auto-rollback on failures
  • Provides instant feedback to developers
• On-Demand Environments: System that:
  • Creates complete environments per PR in <5 minutes
  • Sanitized copy of production data
  • Unique URLs for testing and demos
  • Automatic cleanup when PR is closed
• Proactive Observability: Platform that:
  • Alerts only when action is required
  • Automatically suggests root causes
  • Auto-remediation of known issues
  • Customized dashboards per team/service

Our backend team is building a highly-available and distributed data pipeline that powers Telnyx products like Voice, Messaging and Wireless. We leverage the Telnyx private backbone network to build a cloud-agnostic data platform that processes thousands of messages per second.

With our lean team, we're currently running and managing more than 30 dockerized microservices deployed in multiple regions in the U.S. and Europe. We are looking for a senior Java backend engineer with deep knowledge of Java Core.

In this role you will

• Work on 30+ microservices implemented in Java 11 and Scala that process, aggregate and expose all data our telecommunication and messaging engines generate
• Improve performance of our pipeline — we currently process 10k messages/sec and are growing
• Architect our services and pipelines so they work with minimum latency in all our locations around the world (U.S., E.U., Australia, South America)
• Implement fraud detection processes with machine learning (Kafka and Kafka Streams)
• Deploy services to multi-cloud Kubernetes environments to achieve 99.999% uptime
• Push code to production multiple times a day

What we're looking for

• Degree in Computer Science, Information Technology, or equivalent work experience
• 4+ years of experience with Java and its ecosystem of tooling
• Experience with at least one of these databases: Cassandra, ClickHouse, or OpenSearch
• Experience with AI tooling, or a strong willingness to learn

Nice to have

• Experience with Scala or another functional programming language
• Experience with Linux, Git, and Docker in a CI environment
• Experience with distributed systems and systems that maintain "five nines" (99.999%) of uptime

LI-KG1
LI-DUBLIN
LI-BRAZIL

AI Solution Engineer– LAC (Brazil) - 12 months contractor 

Overview:
Working with governments, foundations, and public sector partners to turn complex challenges into buildable solutions and real impact through AI product-driven delivery.

About Delivery Associates
Delivery Associates (DA) is a global social impact consultancy specializing in transforming the public sector. With over a decade of experience and a foundation in Deliverology®, DA guides leaders through every phase of implementation—delivery-oriented strategy formulation, execution, and evaluation. DA partners with governments, philanthropies, and international organizations, employing actionable strategies to achieve sustainable, lasting outcomes. In every one of our services, you will find a throughline back to this focus on helping our partners deliver better results through better implementation.

Job Description
Delivery Associates is building a new kind of team—one that helps partners across government and the social sector move from policy ambition to real, AI-enabled products and services that improve outcomes for people.

We are hiring an AI Solutions Engineer to serve as the technical backbone of this effort. This is neither a research role nor a narrowly defined engineering position. It is a delivery role at its core: translating complex, ambiguous public sector challenges into working solutions that can be deployed and used in the real world.

In this role, you will work closely with Product, Delivery teams, and government counterparts to rapidly design, prototype, and ship AI-powered tools that are not only technically sound, but also practical, credible, and impactful. You will be expected to move quickly from problem definition to functional systems, operating in short, iterative cycles.

This role is designed for someone who combines strong engineering judgment with a deep understanding of modern AI systems—and who can build quickly without compromising quality. Someone who is motivated by impact, comfortable with ambiguity, and driven to turn ideas into systems that improve how public institutions serve people.

Core Responsibilities.

This is a contractor role embedded within small, high-performing delivery teams, where product ownership and execution are tightly integrated. In this role, you will:

• Build functional AI-powered functional prototypes in 2–4 week cycles
• Design and implement agentic workflows using LLM APIs, structured tool use, multi-step orchestration, and MCP integrations
• Own the stack end to end: React/Next.js frontend, Python/Node.js backend, Supabase/PostGIS data layer, cloud deployment
• Work with messy, real-world government datasets — structure them, clean them, make them queryable
• Build systems that drive frontline action and institutional decisions
• Set architecture standards, review code, and guide a Full-Stack Developer on implementation patterns
• Create reusable component libraries and architecture templates that compound across government engagements

Mindsets.

We work well with people that are:

• Adaptable: Public sector work is dynamic. Our people are, too.
• Analytical: We identify, dissect, and solve complex problems.
• Accountable: We are a remote team. We work collaboratively but self-sufficiently; oversight is often minimal.
• Driven: Our work is important, so it’s important we do it well.
• Curious: We never stop learning from our clients, colleagues, and partners.

Required Skills/Experience.
 

• 8+ years of professional software development experience, with a track record of building and shipping production systems
• Strong experience designing and implementing AI-powered applications using modern LLM stacks, including prompt engineering, structured outputs, tool use, and function calling
• Hands-on experience integrating LLMs into real workflows (not just prototypes), ensuring reliability, controllability, and usability of outputs
• Experience building end-to-end AI systems, including agentic or multi-step workflows, and Retrieval-Augmented Generation (RAG) pipelines with external data sources
• Proficiency working with leading AI tools and ecosystems such as OpenAI API, Claude API, Hugging Face, and orchestration frameworks like LangChain or LlamaIndex
• Ability to design and deploy ML pipelines end-to-end, including data ingestion, preprocessing, model integration, and basic monitoring
• Experience deploying and scaling applications in cloud environments (e.g., AWS, Azure, or Google Cloud)
• Demonstrated ability to move quickly from ambiguous problem to working prototype, making strong scoping and prioritization decisions
• Sound technical judgment under uncertainty, with a bias toward simple, reliable, and maintainable solutions over unnecessary complexity
• Professional English and Portuguese required
• Must be based in and have work authorization in Brazil

What Will Set You Apart.

• Cloud certifications: Azure AI Engineer, AWS ML Specialty, or GCP Professional ML Engineer
• Previous work with government or public sector clients in Latin America
• Data & geospatial systems: experience working with geospatial data and tools (e.g., PostGIS, GeoJSON pipelines, mapping APIs), and the ability to incorporate spatial analysis into practical applications.
• Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS, or similar) to support Retrieval-Augmented Generation (RAG) workflows is highly valued, including designing pipelines for embedding, storage, and retrieval in real-world use cases.

What We Offer.

• Meaningful work that contributes to solving complex social challenges around the world
• Ongoing learning and growth through mentorship and leadership opportunities
• Opportunity to shape a new model of delivery at the intersection of consulting, product, and AI

Our Values.

These values serve as an anchor, enabling us to stay true to who we are and what we stand for.

• Passion: It is all about impact.
• Excellence: Delivering to the highest standards.
• Humility: Pride without ego.

About Delivery Associates:

We help governments, foundations, and social impact organizations all over the world turn big ideas, campaign promises, and ambitious goals into everyday reality for the people they serve. With over ten years of experience and expert staff guiding our work, Delivery Associates has delivered impact in areas ranging from education reform in the US to microfinance in South America to agricultural reform in Africa and the Middle East. We approach every problem with a strong bias towards implementation, an open mind to possibilities, empathy for governments and residents, and a strong values system. We are always asking ourselves, our partners, and our clients: What would it take to make change happen?

To learn more about Delivery Associates please visit deliveryassociates.com/our-work or contact our talent team at talent@deliveryassociates.com for more information on opportunities to join our team.

#LI-MG1 #LI-REMOTE

Este papel é central na transformação de pesquisa de ponta em aplicações concretas de inteligência artificial, com robustez e escalabilidade. A pessoa nesta função contribuirá para acelerar o ciclo de desenvolvimento científico-tecnológico da Kunumi, encurtando o intervalo entre hipóteses e validações práticas com impacto real.

Esse propósito se traduz, na prática, nos seguintes Jobs to Be Done:

Traduzir hipóteses de pesquisa em artefatos concretos: transformar ideias e hipóteses em construções tangíveis (como modelos, algoritmos, ferramentas ou experimentos) que permitam validar conceitos, gerar aprendizados e produzir impactos no mundo real.

O foco está menos em “prototipar” e mais em viabilizar materializações práticas da pesquisa, conectando o campo teórico a aplicações relevantes, mesmo que em estágios iniciais ou experimentais.

Autorar publicações científicas e fortalecer a presença da Kunumi na comunidade de pesquisa: liderar ou coautorar artigos relevantes, buscar ativamente oportunidades de publicação e colaboração acadêmica, e representar a empresa em fóruns científicos, consolidando a Kunumi como referência em pesquisa aplicada no Sul Global.

Importante: a gente não mede impacto pela quantidade de publicações. O que importa é estar em diálogo com a comunidade científica, acompanhando e contribuindo para o avanço do conhecimento de forma genuína.

Desenvolver infraestrutura para experimentação científica: criar ferramentas, ambientes e pipelines que facilitem a condução de experimentos, a análise de dados e a replicabilidade dos resultados.

Otimizar desempenho e eficiência de modelos: ajustar arquiteturas e fluxos computacionais para garantir que os modelos de IA sejam treinados e executados com o melhor equilíbrio entre custo computacional e performance.

Conectar teoria e aplicação: apoiar os times de pesquisa na adaptação de ideias teóricas para contextos práticos, considerando limitações reais de dados, hardware e integração com sistemas existentes.

Atuar em colaboração com múltiplas frentes da Kunumi: interagir com áreas técnicas e não técnicas, contribuindo para que o conhecimento gerado em pesquisa se traduza em soluções aplicáveis para produtos, negócios ou iniciativas estratégicas.

Promover a melhoria contínua da base técnica da Kunumi: propor soluções mais elegantes, compartilhar boas práticas e apoiar a evolução sustentável da infraestrutura usada nos labs.

O que é esperado de você

Experiência sólida com programação em Python e frameworks como PyTorch ou TensorFlow

Conhecimento aprofundado em matemática aplicada (álgebra linear, cálculo, estatística)

Domínio de algoritmos de aprendizado de máquina e deep learning

Experiência com sistemas distribuídos e pipelines de dados em larga escala

Familiaridade com versionamento (Git), testes de código e práticas modernas de engenharia de software

Capacidade de trabalhar em colaboração com pesquisadores e times multidisciplinares

Experiência com escrita de artigos científicos publicados em anais de congressos e periódicos reconhecidos na área da computação

O que pode ser um diferencial

Experiência prévia em pesquisa aplicada em IA, machine learning ou áreas correlatas

Histórico de publicações em eventos da computação Qualis A1

Contribuições relevantes em projetos open source ou publicações técnicas

Vivência com otimização de modelos para ambientes de produção

Interesse em atuar na interseção entre ciência e impacto social

The Mission

We are seeking an Engineering Manager for our Cloud Data Engineering Practice. The right candidate is someone who is technically strong, can manage a team of Architects and Engineers, oversee data delivery engagements and is passionate about working with our customers, partners and employees to drive the business forward.

Your Assignment

• Manage a team of 5 - 8 cloud engineers and architects
• Interface with clients and internal teams to propose technical improvements using your cloud and engineering knowledge
• Take on hands-on technical responsibilities, including technical tasks in sprints 
• Lead technical discussions with customers
• Handle code reviews and pull request management
• Manage task assignments within sprints
• Perform technical leadership activities like roadmap and vision checks, best practices implementation, and risk identification
• In-project mentoring (understand people on project & creation of growth opportunities) and sharing feedback for team members on the project
• Technical accountability on the delivery
• Kickoff new client engagements and act as a point of technical escalation
• Develop and review proposals and contracts and present these to clients
• Perform technical interviews for Architect and Engineer candidates
• Perform weekly 1:1s with your direct reports and guide their career development
•  

Your Qualifications

• Strong experience in AWS data landscape
• Expertise in at least two major areas of Cloud Data Engineering:
  • Relational database design, optimization and migration
  • Big data processing using Spark, Hadoop, EMR etc
  • Machine Learning and MLOps
  • Advanced analytics using time series forecasting, descriptive and inferential statistics
  • BI dashboards and visualizations
  • Data Governance and MDM
• Experience with most of these:
  • Infrastructure as Code tools
  • CI/CD pipelines
  • Application modernization and migration with a strong focus on databases
• Excellent written and verbal communication skills

Benefits

• 100% remote work
• Flexible Time Off
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Caylent is a place where everyone belongs.  We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.   

We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.

The Opportunity

This is a senior technical client leadership role that blends deep hands-on ML expertise with strategic advisory and consulting skills. You will be the most experienced ML voice across a diverse and expanding book of customer engagements — from early-stage companies bringing ambitious ML ideas to market, to established enterprises modernizing how they build and operate AI systems on AWS.

You will shape strategy, influence architecture, and leave every team you touch better than you found it. You bring the scientific depth to design and evaluate models rigorously, the engineering depth to architect production ML systems at scale, and the consulting instincts to translate both into business value for customers.

If you have led the hard conversations, shaped the architecture decisions that mattered, and built the things others benchmark against — and you are looking to do that across a growing portfolio of varied and interesting customers — this is the role for you.

What You'll Do

• Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement.
• Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work.
• Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities.
• Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative.
• Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain.
• Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers.
• Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership content.

What You Bring

The non-negotiables

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether traditional ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards and decisions that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization (quantization, vLLM), and distributed training (DeepSpeed, FSDP) — combined with RAG and agentic system design, including multi-agent architectures, event-driven workflows, MCP integration, and human-in-the-loop patterns on AWS. Technical authority to prescribe the right approach and set architectural standards that teams can execute against.
• Proven ability to operate independently in complex customer environments — navigating ambiguity, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Hands-on experience designing and deploying SRE agents and AI-driven operations workflows in production — spanning automated incident detection, triage, and remediation — with the ability to integrate across observability platforms and translate AI operations outcomes into measurable business value.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI

AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)

Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts

AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly

Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue

Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate

Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama

MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness

LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation

Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

Benefits

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers.  We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference.  You will develop solutions designed by an architect.

You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer.  Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.

Your Assignments

• Work with a team to deliver machine learning solutions on AWS for customers
• Participate in and contribute to daily standup meetings
• Develop and implement ML models, MLOps, and analytics
• Big data processing and preparation of training data for models

Your Qualifications

• Strong experience in building ML models for real world applications
• Strong experience in at least one of these:
• AWS ML Services/SageMaker
• ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
• MLOps tools such as MLflow, Kubeflow, Airflow
• Advanced analytics using time series forecasting and/or inferential statistics
• Strong experience in one or more of these data processing solutions:
• Big data processing platforms like Spark, Hadoop, or streaming platforms
• Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
• Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
• Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
• Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
• Excellent written and verbal communication skills

Benefits 

• 100% remote work
• Generous holidays and flexible PTO
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

AE Studio is an LA-based company focused on increasing human agency, primarily by making the imminent AGI future go well. Our team consists of the best developers, data scientists, researchers, and founders. We do all sorts of projects, always of the quality that makes our clients sing our praises. 

We’ve worked with Samsung, Walmart, Berkshire Hathaway, and other large, important entities you’ve probably heard of.  Our work environment is fantastic for aspiring coders, calculators, and entrepreneurs.  Also, we have neither VC, nor PE, nor other acronyms funding us.  We have a weird business model where we sell our work for a profit and use those profits to pay people (I told you it was weird!). We then reinvest those profits into our promising research on AI alignment and our ambitious internal skunkworks projects. We previously sold one of our skunkworks for some number of millions of dollars.

We have made a name for ourselves in cutting-edge brain computer interface (BCI) R&D, and we are making a name for ourselves in our research and policy efforts on AI alignment. We want to optimize for human agency, if you feel similarly, please apply to support our efforts. Data scientists will have the opportunity between client projects to work on important alignment research, with the opportunity to potentially have your research project prioritized if particularly promising.

ABOUT YOU

• Experience with ML or alignment research
• You care about AI alignment, and are optimistic in humanity’s capacity to problem solve and safely navigate accelerating AI capabilities and have an awesome future
• Eager to use AI and automate everything you do
• Comfortable working in a fast-paced, startup-like environment
• Proven data science experience–primary or equal contributor, multiple smaller projects, management of stake-holders.
• Experience working with / building / training deep learning-based computer vision or NLP models or LLMs
• Lots of experience with Python
• Experience calling AI models’ APIs via REST or client libraries
• Growth mindset. Excited about learning new things and solving difficult problems
• Demonstrated ability to work independently/autonomously
• Track record for breaking down complex problems into manageable chunks for individual or team execution
• Full-time availability–but if you have cool side projects that increase human agency, we totally want you to keep working on it...we’ll even help!
• Ability to communicate effectively and work exclusively in English and communicate complex technical concepts clearly to a non-technical audience

BONUS POINTS FOR

• Experience with self-managed data science projects - show us your cool side hustles, especially if they increase human agency
• Experienced with software engineering best practices/software development background
• Agile experience (worked with Kanban, Scrum, Extreme Programming)
• JavaScript / Node.js experience
• Experience managing clients and client relationships
• Experience in startups
• Being in LA to work in person from our amazing office

Salary range is from $120K to $220K per year for people based in California. 

Not in the range? That's fine, you can still apply, and our team may fit you in a more senior position that we're not actively hiring right now, but we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

We believe in the power of our product. We continue to execute and build momentum as we develop our customer base with the world's top banks; we work with four of the five largest banks in the US, acquirers, processors, and merchants. In our fast-paced and open environment, you will be working with a collaborative team spanning across the globe and delivering exceptional results. We are committed to building something extraordinary. Join Us!

You: 

As a Senior Solutions Consultant at Feedzai, you will play an integral role in the sale of our leading RiskOps platform to high-profile Financial Institutions. You will partner with Feedzai’s sales team to understand clients, prospects and partners’ business, functional and technical needs and demonstrate how those can be achieved through the capabilities of our platform. You not only support effective qualification, but also own the technical dimension that addresses the business needs - you will successfully employ a combination of communication and soft skills, compelling storytelling, solution design and collaboration with a strong solutions design mindset to act as the trusted advisor with the clients. As needed you’ll also be a bridge to our product and development teams, distilling sales engagement feedback for them to help guide our roadmap. Finally you’ll have the organizational skills to do all this, and be able to lead multiple RFP proposals.

Your Day to Day: 

• Provide product demonstrations and lead technical sales discussions both remote and onsite across Europe. 
• Assist the sales team in leading tailored value driven pitches (market to technology), strongly focused in financial crime.
• Understand client business needs and offer solution designs to address those needs, in a continuous education mode and problem-solving mindset.
• Manage (orchestrate, complete, review, submit) formal Tenders (ie, RFPs, RFIs).
• Build formal proposals and own its life cycle throughout the sales process to ensure crisp translation of business needs into technical requirements.
• Engage with multiple stakeholders, from Product to Delivery, to ensure not only the right staffing for client engagements is in place but also to ensure market insights are shared across teams

You Have, You Know-how, You are: 

• BS or Masters in Computer Science or equivalent proven experience in Enterprise Software sales and strong technical acumen.
• 5+ years of professional experience as Solution Consultant in complex environments, supporting teams to land and expand client’s portfolio.
• Proven experience in the Financial Services industry - Financial Crime
• Relevant commercial / sales experience, with a track record working as a Solution Consultant / Pre-sales Engineer, supporting quota carriers in selling enterprise-level software in complex and mission-critical environments.
• Experience at a growth-stage Enterprise software SaaS company.
• Ability to understand and determine an enterprise's client’s needs and how Feedzai’s products might best fit through a consultative approach.
• Strong business acumen with executive presence, strong presentation skills and excellent listening skills
• Must be organized and a self-starter, able to deliver high-quality work without a tactical oversight in a fast-paced environment.
• Highly driven, organized, ambitious and tenacious. A natural problem solver with a strong student mentality, work ethic and positive mental attitude.
• Willingness to travel up to 30% - this is a remote role, with travel as required.
• Fluency in Portuguese and English required, professional level Spanish is desirable 

• You will ensure new customers have an excellent experience by providing technical assistance early in their journey
• You will become an expert on the Databricks Platform and guide customers in making the best technical decisions
• You will work directly with multiple customers concurrently to provide technical solutions.

• Undergraduate degree or higher in Computer Science, Information Systems, or relevant experience
• 3+ years experience in a customer-facing technical role in pre-sales, professional services, consulting or customer success.
• Experience in one or more of the following:
• Solid understanding of the end to end data analytics workflow
• Excellent time management and prioritization skills
• Knowledge of public cloud platforms AWS, Azure or GCP would be a plus
• Knowledge of a programming language - Python, Scala, or SQL
• Knowledge of end-to-end data analytics workflow
• Hands-on professional or academic experience in one or more of the following:
• Data Engineering technologies (e.g., ETL, DBT, Spark, Airflow)
• Data Warehousing technologies (e.g., SQL, Stored Procedures, Redshift, Snowflake)
• Excellent time management and prioritization skills
• Excellent written and verbal communication, in English and Portuguese
• Bonus
  • Knowledge of Data Science and Machine Learning (e.g., build and deploy ML Models).
  • Databricks certification(s)

P-993

Mission 

As a Data & AI Technical Solutions Engineer, you play a critical role by helping customers debug and maintain stable production data pipelines, AI workflows, and more using the Databricks platform.  You will develop product expertise in a couple of areas by advising a broad set of customers and use cases across those technologies.  You will collaborate with other teams at Databricks to deliver an excellent customer experience - whether that’s product engineering teams or technical account team members.  TSE’s have proven production troubleshooting and optimization experience to help our customers’ workloads run smoothly and to achieve their strategic objectives using the Databricks’ platform.  Reporting to a TSE manager - you will be part of a world class global support engineering organization for Databricks, known for your technical depth and delivering impeccable customer service.

The impact you will have:

• Be the first point of contact for customer production issues - provide initial analysis, troubleshooting, and resolution for data engineering and AI workloads. 
• Deep Dive into code-level analysis of customer workloads to address issues related to Databricks products - including Spark core internals, Spark SQL, Delta, DLT, and Model Serving.
• Provide excellent customer support - be knowledgeable and empathetic in customer communications over email and video, act with a sense of urgency to find mitigations and solutions, diffuse escalations during incidents and be proactive at helping prevent future customer problems.   
• Help make the Databricks products simpler to use and customer production environments more stable - such as through coordinating with Engineering and Backline Support teams to identify areas for product improvements. 
• Develop expertise in productionizing systems in Databricks and share your knowledge by contributing to wikis and other technical documentation to be used internally or externally by customers and partners.

What we look for: 

• Minimum of 6 years of experience in designing, building, testing, and maintaining Python/Java/Scala based applications in typical project delivery and consulting environments. 
• Experience with SQL databases or data warehouses (such as Oracle, Teradata, SQL Server, MySQL) and ETL technologies (such as Informatica, DataStage, Talend, Fivetran). 
• 3 years of hands-on experience in developing two or more Big Data technologies such as Spark & Hadoop, Lakehouse architecture - such as Delta, Data Ingestion, Data Streaming applications, or ML/AI applications for industry use cases. 
• Hands-on experience in performance tuning and troubleshooting of Data and AI applications at production scale - including query optimization, memory management, garbage collection, and heap/thread dump analysis. 
• Prior Support or customer facing experience is not required for this role, but the ability and desire to develop excellent customer service skills is.
• Preferrable: Hands-on experience with public cloud (AWS or Azure or GCP).
• Technical degree or the equivalent experience.

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Estamos em busca de um(a) Machine Learning Engineer com foco em NLP e processamento de documentos para atuar no desenvolvimento de soluções inteligentes voltadas à automação e análise de dados, especialmente em contextos financeiros. O(a) profissional será responsável por construir pipelines de dados, desenvolver modelos de machine learning e implementar soluções escaláveis em ambiente cloud.

O que você fará:

• Desenvolver soluções de machine learning e NLP para extração e processamento de informações de documentos
• Trabalhar com OCR, parsing de PDFs e extração de dados de Excel
• Implementar algoritmos de fuzzy matching (ex: Levenshtein, record linkage)
• Construir e manter pipelines de dados e processos de ETL
• Desenvolver, treinar e validar modelos de machine learning (supervisionados e não supervisionados)
• Realizar deploy de modelos utilizando APIs REST, Docker e serviços Azure
• Integrar soluções com sistemas externos e aplicações corporativas
• Colaborar com times multidisciplinares para entrega de soluções escaláveis

O que você precisa ter:

• Forte experiência em Python (Pandas, NumPy, scikit-learn)
• Experiência com bibliotecas de NLP (spaCy, NLTK ou Transformers)
• Conhecimento em processamento de documentos (OCR, PDFs, Excel)
• Experiência com deploy de modelos (APIs REST, Docker, Azure ML)
• Entendimento de técnicas de machine learning supervisionado e não supervisionado
• Experiência com pipelines de dados e ETL
• 2 a 5 anos de experiência em Machine Learning, com foco em NLP ou dados financeiros
• Inglês avançado/fluente

Diferenciais

• Experiência no setor financeiro/fintech (reconciliação, contabilidade)
• Conhecimento em Azure Machine Learning e Cognitive Services
• Experiência com frameworks de deep learning (TensorFlow, PyTorch)
• Experiência com LLMs para entendimento de documentos (OpenAI, Azure OpenAI)

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros. Nossas oportunidades são trabalhadas para todos(as)!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

About us 

Nubank was founded in 2013 with the mission of fighting complexity to empower people in their daily lives by reinventing financial services. Today, we are one of the largest digital banking platforms in the world, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our careers page: https://international.nubank.com.br/careers/ 

About the team 

The Governance, Risk and Compliance (GRC) team enables Nubank to remain compliant with legal, regulatory, and internal requirements, while continuously identifying, classifying, and monitoring risks and providing strategic insights and performance evaluation to leadership.

The GRC squad collaborates with multidisciplinary teams to align our technology security strategy with Nubank’s overall business objectives, ensuring that identified risks are mitigated and that risk-based decision-making is enabled within and beyond the IT & Security Business Unit.

About the role

You will be responsible for acting as a technical reference in security, certifications, and internal controls, serving as a bridge between engineering, risk, audit, and business stakeholders.
You will define strategies, support risk-based decision-making, and ensure that security and compliance requirements are effectively embedded into processes, systems, and products.

Key responsibilities

• Act as a senior technical and governance reference across security, certifications, risk, and internal controls, influencing strategy.
• Identify control gaps and improvement opportunities in technical procedures required for certification and recertification processes  (e.g., ISO 27001, PCI-DSS).
• Develop and maintain strong partnerships with business and technical leaders to orchestrate audits, assessments, and remediation plans in a risk-based and scalable way.
• Collaborate with technical teams to define action plans that ensure adherence to regulatory requirements and internal policies.

• Conduct assessments of internal controls, ensuring adherence to internal policies, legal requirements, and industry standards.
• Identify gaps and improvement opportunities in the internal controls landscape and lead control reviews, ensuring timely resolution of issues.
• Work closely with Risk teams to align on the mitigation of identified risks.
• Support responses to audit requests, regulatory inquiries, and due diligence from business partners.

• Partner with Engineering, Product, IT, and global teams to integrate compliance and security requirements into processes and systems.

• Define and monitor KRIs and KPIs, delivering forward-looking, data-driven insights to senior management and Committees.
• Drive continuous improvement and scale, simplifying processes and strengthening Nubank’s Security Maturity as the company grows globally.

Qualification Requirements

• Solid experience in information security, with strong knowledge of frameworks such as PCI-DSS, ISO 27000 family, NIST, and similar.
• Prior experience with security certification processes and/or internal controls, compliance, and audit support.
• Excellent executive communication skills, capable of translating complex topics into clear, actionable insights for senior leadership and committees.
• Experience operating in regulated and global environments, including interaction with auditors and regulators.
• Bachelor’s degree in Engineering, Technology, Security Information, Risk Management or related fields.
• Familiarity with using AI and automation (e.g., machine learning, generative AI, or LLM-based tooling) to enhance security compliance use cases.
• Knowledge of the regulatory landscape relevant to financial services, such as SOx, BACEN, CVM, CNBV, ANBIMA, SEC, and related regulations.
• Hands-on experience with cloud environments (e.g., AWS, GCP) and implementing security controls in these contexts.
• Advanced English (written and verbal) required.

Nice to have Requirements

• Relevant certifications such as CRISC, CISA, Security+, CISSP, or CISM are considered a strong plus.

International experience is highly desirable.

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

About us

AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.

About AB InBev Growth Group

Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.

In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft.

We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities.

What you'll do:

• Drive BEES AI’s mission, vision, and ML strategy into concrete technical roadmaps and align architecture and standards with long-term goals.
• Own technical end-to-end delivery of ML pipelines—from architecture and data/feature pipelines through model development, deployment, and production scaling—in partnership with data, platform, and product teams.
• Design and standardize the ML model development framework (project structure, experimentation, versioning, reproducibility) to improve consistency and reuse across teams.
• Build and implement observability across the model lifecycle (training and production) via monitoring, logging, and alerting for performance, quality, and drift.
• Ensure optimized deployments that minimize cost and maximize quality (e.g., scaling, resource allocation, inference optimization) while meeting SLAs.

What you'll need:

• Bachelor's degree in computer science, engineering, mathematics, or any quantitative field. A master's degree is a plus.
• Relevant experience with ML platform architecture (e.g., feature stores, model registries, training and inference pipelines).
• Systems thinking (scalability, reliability, latency, cost)
• Software design patterns for building maintainable, production-ready ML systems.
• Python, PySpark, and SQL. Java, Rust, and NodeJS are a plus
• Kubernetes, Databricks, Terraform, Azure Devops (Git), Azure Cloud, ML Frameworks (BentoML, Kedro, Seldon, KServe, Triton Inference Server, etc.) and ML Libraries (Scikit Learn, Pytorch, Tensor Flow, ONNX, etc.)

More about you:

• You´re motivated by building up world-class solutions that impact millions of users all over the world;
• You´re creative when solving problems and is continuously seeking improvements for processes and solutions;
• You can communicate clearly with your team and the company to identify issues and demands;
• You have the autonomy to recognize the current and new priorities, evaluating the impact of their outcomes in the final result.

What We Offer:

• Performance based bonus*
• Attendance Bonus* 
• Private pension plan
• Meal Allowance
• Casual office and dress code
• Days off*
• Health, dental, and life insurance
• Medicines discounts
• WellHub partnership
• Childcare subsidies
• Discounts on Ambev products*
• Clube Ben partnership
• Scholarship*
• School materials assurance
• Language and training platforms
• Transport allowance

*Rules applied

Equal Opportunity & Affirmative Action:

AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.

The following fields are optional, but anticipate the information for your registration*.

Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. 

For more information: www.abinbev.com 

About AB InBev

AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.

About ABI Growth Group

Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.

About BEES

As a technology cell of our organization, we have a simple goal: grow. Grow as people, as professionals, as a company. To achieve this, we use technology to create digital solutions that simplify our customers' lives, make their decisions smarter and their businesses more profitable. With offices in São Paulo and Campinas, we encourage our team to participate in major events and significant meetings throughout the year.

Responsibilities:

• Leads efforts within the organization to drive the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools and platforms used across BEES.
• Design efficient data models and understand concepts such as normalization, denormalization, and dimensional modeling.
• Implement improvements in architecture and processes to improve the performance, monitoring, and evolution of data products.
• Develop and maintain data ingestion, processing, control/security, and data provisioning processes for different consumers (services, front-end, among others).
• Contribute to obtaining knowledge in the business context and creating new data products to meet their strategic and operational needs.

Requirements and qualifications:

• Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis or similar;
• Advanced English;
• Assess scalability, reliability, security, and compliance implications of data pipeline designs.
• Understand cloud computing platforms and services offered by providers like AWS, Azure, and Google Cloud.
• Evaluate programming solutions in Python, PySpark, Scala, and SQL for data processing and analysis.
• Evaluate data quality processes and controls to ensure accuracy and completeness.
• Apply debugging techniques to identify and resolve cross-module issues.
• Implement monitoring, alerting, and failure handling mechanisms in architecture designs.
• Assess effectiveness of CI/CD principles and practices in automated pipelines.
• Design, develop, and maintain APIs for data exchange between applications.
• Apply Agile practices to plan, execute, and deliver data engineering tasks and projects.

Soft Skills:

• Logical reasoning and analytical skills;
• Meeting deadlines and quality of work;
• Effective and transparent dialog with other areas and co-workers;
• Ability to communicate and interpersonal relationships to to present cases and discuss them with other areas involved;
• Being independent in activities;
• Work as part of a team, promoting a good relationship with the team;

Differentials:

• Evaluate data pipeline solutions for latency, throughput and accuracy.
• Analyze data requirements and business needs to inform data modeling decisions.
• Understand the principles and assumptions of different machine learning capabilities.
• Integrate data sets with visualization tools to create insightful reports and dashboards

What We Offer:

• Performance based bonus*
• Attendance Bonus* 
• Private pension plan
• Meal Allowance
• Casual office and dress code
• Days off*
• Health, dental, and life insurance
• Medicines discounts
• WellHub partnership
• Childcare subsidies
• Discounts on Ambev products*
• Clube Ben partnership
• Scholarship*
• School materials assurance
• Language and training platforms
• Transport allowance

*Rules applied

Equal Opportunity & Affirmative Action:

AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.

The following fields are optional, but anticipate the information for your registration*.

Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. 

For more information: www.abinbev.com 

About us 

Nubank was founded in 2013 with the mission of fighting complexity to empower people in their daily lives by reinventing financial services. Today, we are one of the largest digital banking platforms in the world, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our careers page: https://international.nubank.com.br/careers/ 

About the team 

The Governance, Risk and Compliance (GRC) team enables Nubank to remain compliant with legal, regulatory, and internal requirements, while continuously identifying, classifying, and monitoring risks and providing strategic insights and performance evaluation to leadership.

The GRC squad collaborates with multidisciplinary teams to align our technology security strategy with Nubank’s overall business objectives, ensuring that identified risks are mitigated and that risk-based decision-making is enabled within and beyond the IT & Security Business Unit.

About the role

You will be responsible for acting as a technical reference in security, certifications, and internal controls, serving as a bridge between engineering, risk, audit, and business stakeholders.
You will define strategies, support risk-based decision-making, and ensure that security and compliance requirements are effectively embedded into processes, systems, and products.

Key responsibilities

• Act as a senior technical and governance reference across security, certifications, risk, and internal controls, influencing strategy.
• Identify control gaps and improvement opportunities in technical procedures required for certification and recertification processes  (e.g., ISO 27001, PCI-DSS).
• Develop and maintain strong partnerships with business and technical leaders to orchestrate audits, assessments, and remediation plans in a risk-based and scalable way.
• Collaborate with technical teams to define action plans that ensure adherence to regulatory requirements and internal policies.

• Conduct assessments of internal controls, ensuring adherence to internal policies, legal requirements, and industry standards.
• Identify gaps and improvement opportunities in the internal controls landscape and lead control reviews, ensuring timely resolution of issues.
• Work closely with Risk teams to align on the mitigation of identified risks.
• Support responses to audit requests, regulatory inquiries, and due diligence from business partners.

• Partner with Engineering, Product, IT, and global teams to integrate compliance and security requirements into processes and systems.

• Define and monitor KRIs and KPIs, delivering forward-looking, data-driven insights to senior management and Committees.
• Drive continuous improvement and scale, simplifying processes and strengthening Nubank’s Security Maturity as the company grows globally.

Qualification Requirements

• Solid experience in information security, with strong knowledge of frameworks such as PCI-DSS, ISO 27000 family, NIST, and similar.
• Prior experience with security certification processes and/or internal controls, compliance, and audit support.
• Excellent executive communication skills, capable of translating complex topics into clear, actionable insights for senior leadership and committees.
• Experience operating in regulated and global environments, including interaction with auditors and regulators.
• Bachelor’s degree in Engineering, Technology, Security Information, Risk Management or related fields.
• Familiarity with using AI and automation (e.g., machine learning, generative AI, or LLM-based tooling) to enhance security compliance use cases.
• Knowledge of the regulatory landscape relevant to financial services, such as SOx, BACEN, CVM, CNBV, ANBIMA, SEC, and related regulations.
• Hands-on experience with cloud environments (e.g., AWS, GCP) and implementing security controls in these contexts.
• Advanced English (written and verbal) required.

Nice to have Requirements

• Relevant certifications such as CRISC, CISA, Security+, CISSP, or CISM are considered a strong plus.

International experience is highly desirable.

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Xometry is looking for a Machine Learning Engineer II who is excited about advancing machine learning capabilities and bringing models into production at scale. In this role, you’ll design, deploy, and maintain robust statistical and machine learning models, working closely with data scientists to translate research and experimentation into reliable, high-impact systems. You’ll apply strong data intuition and engineering judgment to improve model performance, reliability, and observability, while building predictive models that support pricing, cost estimation, and sourcing recommendations.

What You'll Do:

• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations.
• Analyze large datasets to extract meaningful patterns and insights.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Learn and apply best practices in model evaluation, performance tuning, and deployment.
• Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture.
• Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals.
• Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks.
• Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Experience deploying and maintaining machine learning models in production environments.
• 4+ years of experience in machine learning, focusing on data engineering and/or data science.
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

#LI-Remote

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Xometry is seeking a Senior Machine Learning Engineer to join our growing organization. The right person will help move our machine learning capabilities to the next level. You’ll be working in an organization where AI is the enabler and center of its core business strategy. You want to be part of a small, intensely skilled team, who feel total ownership of their work, and can’t imagine a day without learning & coding.  You will play a crucial role in the Xometry platform and everything you do will matter.

Responsibilities:

• At Xometry, you will play a crucial role in exploring new machine learning opportunities, researching and performing proof of concepts, and bringing new machine learning and AI solutions into Xometry’s platform
• Develop and implement machine learning models that improve Xometry’s ability to predict cost, price, and sourcing options for our customers and suppliers.
• You will be responsible for leading the evaluation of emerging technologies, identifying areas for improvement, and developing new features while ensuring the reliability and scalability of Xometry’s platform
• Lead the exploration of emerging AI and machine learning technologies and develop proof-of-concepts to assess their potential impact on Xometry’s platform
• Collaborate with cross-functional teams to gather requirements, prioritize features, and define technical solutions based on the latest innovations
• Monitor machine learning models and AI performance and troubleshoot issues as they arise
• Contribute to the documentation and knowledge base to help other teams understand and use Xometry’s AI effectively

Qualifications:

• Experience with state of the art ML modeling techniques and approaches like transformers, self supervised pre-training, generative modeling, LLMs, etc
• Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow)
• Successful candidates in this role need to be able to bridge state of the art approaches to real world impact
• A cloud-native software craftsperson with hands on experience with containers, container orchestration, and distributed systems
• An engineer with a self-driven attitude who can own problems and deliver solutions
• Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing
• A cloud practitioner who values the “shift-left” mentality by building systems with Infrastructure as Code, not console clicking
• Data’s at the heart of our systems, we hope it's yours too. You’re comfortable working with SQL and/or NoSQL, understand database design, and data analysis
• Experience building and consuming CI/CD pipelines
• Someone who knows their way around the command line and has experience working with *nix systems
• 5+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
• 3+ years experience leading cross-team engineering efforts
• Strong execution skills in project management

#LI-Remote

Xometry is seeking a Senior Machine Learning Engineer to join our growing organization. The right person will help move our machine learning capabilities to the next level. You’ll be working in an organization where AI is the enabler and center of its core business strategy. You want to be part of a small, intensely skilled team, who feel total ownership of their work, and can’t imagine a day without learning & coding.  You will play a crucial role in the Xometry platform and everything you do will matter.

Responsibilities:

• At Xometry, you will play a crucial role in exploring new machine learning opportunities, researching and performing proof of concepts, and bringing new machine learning and AI solutions into Xometry’s platform
• Develop and implement machine learning models that improve Xometry’s ability to predict cost, price, and sourcing options for our customers and suppliers.
• You will be responsible for leading the evaluation of emerging technologies, identifying areas for improvement, and developing new features while ensuring the reliability and scalability of Xometry’s platform
• Lead the exploration of emerging AI and machine learning technologies and develop proof-of-concepts to assess their potential impact on Xometry’s platform
• Collaborate with cross-functional teams to gather requirements, prioritize features, and define technical solutions based on the latest innovations
• Monitor machine learning models and AI performance and troubleshoot issues as they arise
• Contribute to the documentation and knowledge base to help other teams understand and use Xometry’s AI effectively

Qualifications:

• Experience with state of the art ML modeling techniques and approaches like transformers, self supervised pre-training, generative modeling, LLMs, etc
• Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow)
• Successful candidates in this role need to be able to bridge state of the art approaches to real world impact
• A cloud-native software craftsperson with hands on experience with containers, container orchestration, and distributed systems
• An engineer with a self-driven attitude who can own problems and deliver solutions
• Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing
• A cloud practitioner who values the “shift-left” mentality by building systems with Infrastructure as Code, not console clicking
• Data’s at the heart of our systems, we hope it's yours too. You’re comfortable working with SQL and/or NoSQL, understand database design, and data analysis
• Experience building and consuming CI/CD pipelines
• Someone who knows their way around the command line and has experience working with *nix systems
• 5+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
• 3+ years experience leading cross-team engineering efforts
• Strong execution skills in project management

#LI-Remote

ABOUT THE ROLE

We’re looking for a Senior Technical Product Manager to lead key initiatives within our Cloud & SRE organization. This role is critical to defining the long-term vision of our Core Infrastructure Platform, elevating reliability, efficiency, and Developer Experience (DevEx). You will work at the intersection of engineering, leadership, and product to transform complex infrastructure challenges into scalable solutions that directly impact cost-per-order and customer trust.

WHAT YOU WILL DO

• Define and evolve the strategic vision for our Core Platform, expanding the management of critical resources such as RDS, SQS, and Serverless applications;
• Lead the vision for Safe Releases, integrating CI/CD, Feature Flags, and AI/ML for predictive analytics, anomaly detection, and automated orchestration;
• Drive the adoption of AI/ML to improve the software development lifecycle, focusing on automated setup (Golden Paths), documentation, and testing;
• Define and implement a "System Maturity" model to help engineering teams prioritize non-functional initiatives (security, reliability, and efficiency) based on data-driven health metrics;
• Redefine the FinOps solution vision to provide visibility into efficiency opportunities and reduce the infrastructure cost-per-order across the company;
• Collaborate with Customer Excellence teams to translate internal observability metrics into external health dashboards, improving transparency and trust;
• Actively participate in the Incident Lifecycle Program, using incidents as a source of truth to identify reliability gaps and roadmap opportunities;
• Conduct ongoing discovery to understand developer pain points through interviews, ceremony participation, and collaboration with technical leads;
• Shield engineering teams from unplanned demands, lead Quarterly Business Reviews (QBRs), and align the roadmap with executive leadership.

WHO YOU ARE

• Degree in Software Engineering, Computer Science, or a related field;
• Previous hands-on experience as a Software Engineer is essential to understand our internal users' challenges;
• Strong track record as a Technical Product Manager in platform/infrastructure teams, with deep knowledge of Cloud, SRE, or DevOps environments;
• Strong ability to connect technical KPIs (MTTR, availability, latency) with business outcomes;
• Experience with FinOps, observability tools (e.g., Datadog, Grafana), and a strong interest in applying AI to improve engineering workflows;
• Experience in stakeholder management, with the ability to navigate complex technical discussions and executive alignments;
• Fluent English.

ABOUT VTEX 

VTEX (NYSE: VTEX) is the composable and complete commerce platform that delivers more efficiency and less maintenance to organizations seeking to make smarter IT investments and modernize their tech stack. Through our pragmatic composability approach, we empower brands, distributors, and retailers with unparalleled flexibility and comprehensive solutions, enabling them to invest solely in what provides a clear business advantage and boosts profitability. VTEX is trusted by 2,600 global B2C and B2B clients, including Carrefour, Colgate, Motorola, Sony, Stanley Black & Decker, and Whirlpool, having 3,500 active online stores across 43 countries (as of FY ended on December 31, 2023). For more information, visit www.vtex.com.

BENEFITS 

• Annual profit-sharing program and equity eligibility
• Health, dental, and life insurance with national coverage provided by VTEX
• Annual budget for professional development in Tech
• Language development incentive program (English, Spanish, Portuguese)
• Flexible meal allowance
• Extended parental leaves
• Child-care assistance
• Flexible work schedule and remote-first culture
• Financial assistance to build your work-from-home setup
• Wellness program
• Free shipping on 1000+ VTEX stores

Why this Role Exists

At Blip, data doesn’t just inform decisions, it powers experiences. Every message, transaction, and insight flows through our data ecosystem, and we’re scaling it to handle billions of daily events with sub-second intelligence.

We’re looking for a Staff Data Engineer to shape and evolve the backbone of our real-time data processing layer, someone capable of designing and building data-intensive systems that serve as the foundation for analytics, AI, and intelligent automation at global scale.

Your Mission

You’ll design and implement streaming and batch data systems that move and transform information reliably, efficiently, and transparently across Blip’s platform.

You’ll champion data modeling excellence, ensuring the data we produce is high-quality, discoverable, and ready for real-time consumption — by both humans and machines.

Key Responsibilities

Data Engineering & Pipeline Architecture

• Design, implement, and optimize high-throughput, low-latency data pipelines capable of processing billions of events per day.
• Build scalable data ingestion and transformation frameworks leveraging Kafka, Flink, Spark, Airflow, Beam, and/or GCP related data engineering technologies.
• Ensure fault-tolerance, exactly-once semantics, and replayability in all event processing flows.
• Establish reusable patterns and accelerators for pipeline development, deployment, and monitoring.

Modeling & Storage Design

• Design data models across streaming, analytical, and serving layers (Bronze/Silver/Gold, event sourcing, CDC, and dimensional schemas).
• Partner with Data Architects to evolve domain-driven data models ensuring semantic alignment and traceability from source to consumption.
• Implement optimal partitioning, clustering, and indexing strategies for performance and cost efficiency across Databricks, BigQuery and other storage & processing engines.
  
  

Reliability, Quality & Observability

• Embed observability, lineage, and data quality validations into every pipeline.
• Define and enforce SLAs and SLOs for data delivery, freshness, and accuracy.
• Collaborate with Platform Engineers to integrate metrics, alerts, and self-healing mechanisms for critical data flows.

Collaboration & Leadership

• Act as a technical leader within the Data Engineering team: leading design reviews, conducting architecture spikes, and mentoring engineers.
• Work closely with AI, Platform, and Product teams to deliver event-driven capabilities that power intelligent products in real time.
• Promote craftsmanship, performance, and simplicity as core engineering values.

What We’re Looking For

Experience

• 6+ years in Data Engineering, Software Engineering, or Distributed Systems roles.
• Proven experience building and operating data-intensive and streaming systems in production.
• Hands-on experience with Apache Kafka, Flink, Spark Streaming, Databricks & GCP related data engineering technologies.
• Strong understanding of event-driven architectures, change data capture (CDC), and real-time data modeling patterns.
  
  

Technical Foundations

• Proficiency in Python or PySpark, and solid command of SQL.
• Experience with cloud-native data services (GCP, Azure, or AWS) and workflow orchestration (Airflow/Composer).
• Deep understanding of data modeling and storage formats (Delta, Parquet, Avro).
• Experience with CI/CD for data pipelines, testing frameworks, and infrastructure automation (Terraform).
  
  

Bonus Points

• Experience with event sourcing or CQRS-style systems for transactional and analytical data flows.
• Knowledge of feature store architectures, real-time machine learning serving, or agentic data pipelines.
• Contributions to open-source streaming frameworks or performance optimization initiatives.

Informações adicionais

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Engenheiro de Inteligência Artificial

Responsabilidades:

• Projetar, desenvolver e aprimorar aplicações baseadas em foundation models (ex.: LLMs, modelos multimodais) para necessidades específicas de negócio;
• Implementar e experimentar técnicas de IA generativa, incluindo, mas não se limitando a, Retrieval-Augmented Generation (RAG) e prompt engineering;
• Liderar a implementação de agentes autônomos inteligentes e sistemas multiagente capazes de tomada de decisão complexa, execução de tarefas e interação com sistemas externos;
• Utilizar e contribuir para frameworks de IA agentic (ex.: LangChain, AutoGen, Semantic Kernel, Crew AI) para construir agentes robustos e escaláveis;
• Desenvolver e integrar soluções de Model Context Protocol (MCP) para padronizar como aplicações de IA acessam e utilizam fontes de dados externas, ferramentas e informações em tempo real;
• Liderar o desenvolvimento de aplicações full-stack que integrem modelos de IA generativa e sistemas agentic, garantindo experiências de usuário fluidas;
• Trabalhar com tecnologias de front-end (ex.: React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) e back-end (ex.: Python com Flask/Django/FastAPI, Node.js, Go);
• Projetar e implementar APIs RESTful escaláveis e microsserviços para expor funcionalidades de IA;
• Implantar, gerenciar e otimizar cargas de trabalho de IA/ML e aplicações full-stack em pelo menos uma grande plataforma de nuvem (AWS, Azure ou GCP);
• Implementar práticas de LLMOps/MLOps e DevOps para integração contínua, entrega contínua (CI/CD), implantação de modelos, monitoramento e gestão de ciclo de vida;
• Manter-se atualizado sobre os avanços mais recentes em IA generativa, sistemas agentic, foundation models e áreas relacionadas por meio de pesquisa e experimentação contínuas;
• Colaborar de forma eficaz com equipes multifuncionais, incluindo gerentes de produto, cientistas de dados, pesquisadores e outros engenheiros;
• Orientar engenheiros juniores, compartilhar conhecimento e promover uma cultura de excelência técnica.

Requisitos:

• Bacharelado ou Mestrado em Ciência da Computação, Inteligência Artificial, Machine Learning ou área quantitativa relacionada;
• 5+ anos de experiência em desenvolvimento de software com forte foco em IA/ML;
• Experiência comprovada na construção e implantação de modelos de IA generativa (ex.: LLMs, modelos de difusão) em ambientes de produção;
• Expertise demonstrada em projetar e implementar sistemas de IA agentic e arquiteturas multiagente;
• Sólido entendimento e experiência prática com Model Context Protocol (MCP) para integração de sistemas de IA;
• Experiência consistente em desenvolvimento de aplicações full-stack;
• Ampla experiência com plataformas de nuvem (AWS, Azure ou GCP) para implantações de IA/ML e hospedagem de aplicações em geral;
• Experiência com ferramentas e práticas de LLMOps (ex.: Langfuse, Langsmith, etc.);
• Excelentes habilidades de resolução de problemas, análise e comunicação;
• Capacidade de trabalhar de forma independente e colaborativa em um ambiente ágil e dinâmico;
• Inglês avançado.

Diferenciais:

• Experiência anterior com sistemas de conhecimento baseados em grafos.

• Familiaridade com ferramentas e frameworks de GenAI (LangChain, LlamaIndex, OpenAI APIs).

• Experiência em projetos do setor de seguros ou serviços financeiros.

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros.
Nossas oportunidades são trabalhadas para todos(as)!!!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

About Us

Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world’s largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia.

About the role

At AI Core, we are scaling the impact of our AI initiatives to become the primary driver of Nubank’s most critical decision systems. We are seeking an Lead Machine Learning Engineer (Applied AI Scientist) to lead high-impact research projects that bridge the gap between state-of-the-art AI and production-grade financial systems. You will be responsible for solving complex, ambiguous problems using Deep Learning and Foundation Models, ensuring our architectures are scalable, efficient, and driving measurable business results.

As an Applied AI Scientist (MLE), you’re expected to:

1. Research Execution & Technical Leadership (Complexity & Autonomy)

• Lead and execute complex applied research initiatives independently, focusing on building and optimizing architectures (e.g., Transformers, GNNs) that can be deployed across critical use cases like Credit, RecSys, GenAI, and real-time inference.
• Address difficult and ambiguous modeling problems that require coordination across various stakeholders (Data, Infra, Product), delivering innovative solutions with a clear focus on medium-term impact.
• Bridge the gap between research and production by designing architectures that respect MLOps constraints, ensuring models are optimized for latency, interpretability, and cost-efficiency.

1. Strategic Impact & Collaboration (Impact)

• Develop and deliver innovative solutions that address project-level challenges, focusing on pushing the latest platform and AI research improvements into downstream production models.
• Actively participate in cross-functional collaborations, ensuring that research outputs are seamlessly integrated into Nubank's decision-making engines.
• Establish technical standards within the AI Core team for experimentation, model evaluation, and code quality, inspiring peers to raise their performance.

1. Mentorship & Function Contribution (Function Contribution)

• Serve as a technical mentor for senior engineers and researchers, providing guidance on deep learning fundamentals, problem formulation, and research methodology.
• Actively contribute to the function's growth by participating in mandatory activities like hiring (interview panels) and leading internal task forces to improve our ML lifecycle.
• Contribute to thought leadership by participating in research collaborations or internal papers that align with Nubank’s strategic goals.

What are we looking for?

• Professional Experience: 5-7+ years in applied AI/ML, with a proven track record of delivering research-driven systems into production environments
• Technical Mastery:
  • Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs).
  • Strong coding skills in Python and proficiency with frameworks like PyTorch, JAX, or TensorFlow.
  • Solid understanding of MLOps and the constraints of deploying models at scale.
• Problem Solving: Sophisticated skills in ML problem formulation and the ability to navigate uncertainty when data is messy or unavailable.
• Communication: Ability to communicate complex technical concepts to both technical peers and cross-functional stakeholders, ensuring alignment and buy-in.
• Analytical Capacity: Experience with large-scale experimentation and A/B testing to validate research hypotheses.

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/