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Location: Armenia Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Brazil Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Argentina Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Serbia Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Uruguay Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: (Multiple States), United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the role The Account Executive uncovers business pains, articulates ROI, and builds the business case that helps prospects modernize how their marketing data works. You'll own a territory end to end — from first outreach to signed contract. Your buyers are marketing leaders, marketing ops and RevOps, and the data and analytics teams behind them. Some come to us; many you'll go and find yourself. It's a consultative, multi-stakeholder sale with a technical validation stage, so you'll work closely with our Sales Engineers along the way. Responsibilities Achieve a quarterly revenue quota across new business and expansion in your territory. Proactively generate new pipeline — you'll be expected to self-source at least 35% of your own opportunities, not just work inbound. Own the full sales cycle: discovery, demo, technical validation with a Sales Engineer, business case and ROI, executive presentation, negotiation and close. Build multi-threaded relationships — bring the technical evaluator, the budget owner, and your champion into the process early rather than running a deal through a single contact. Qualify with discipline. Confirm budget, decision path, and the real cost of doing nothing before pulling in technical resources — and walk away early from deals that aren't a fit. Become an expert at using Improvado's software, and at the marketing problems it solves. Coordinate the internal resources needed to win — Sales Engineering, Marketing, Customer Success — and keep every deal moving. Keep the CRM accurate and forecast honestly. Use AI in your day-to-day workflow — account research, call prep, follow-ups, first drafts. We'll expect you to work the way the company works. Leverage your creativity, intellect, and attitude in order to win new business. Qualifications 5+ years in a quota-carrying, full-cycle SaaS Account Executive role. 2+ years of experience in the MarTech/AdTech space. A track record of carrying and hitting a significant annual quota — you can walk through your numbers year by year with real examples. Experience selling to large enterprise organizations with multiple stakeholders and formal buying processes. Real outbound prospecting experience — you've built pipeline from scratch, not only worked inbound. Familiarity with ad platforms and the digital marketing funnel, and the metrics marketers are measured on. Comfortable in a technical sale — you can hold a credible conversation with a data team and then reframe it for a marketing leader. Experience in successfully initiating sales cycles with C-level executives. Ability to thrive in a constantly changing and evolving work environment. Emotional intelligence, natural curiosity, strong listening skills, and coachability. Superior communication and organizational skills. Comfortable with a modern sales stack (CRM, call recording and coaching tools, prospecting and enrichment tools, LinkedIn Sales Navigator) and with using AI tools in your own workflow. Experience working in a startup. Nice to have Experience selling to or working inside agencies. Formal training in a qualification methodology (MEDDIC / MEDDPICC or similar). What We Offer: Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: Serbia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Georgia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Armenia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Brazil We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Argentina We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Marketing Analyst's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations. Manage and enhance data transformations with dbt where necessary. Support clients directly — understand their requirements, translate them into data solutions, and deliver clear insights. Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness. Use Git for version control and collaboration. Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly. Leverage AI tools to be 10x more productive than the average analyst. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Senior Marketing Analytics Consultant's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations. Manage and enhance data transformations with dbt where necessary. Support clients directly — understand their requirements, translate them into data solutions, and deliver clear insights. Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness. Use Git for version control and collaboration. Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly. Leverage AI tools to be 10x more productive than the average analyst. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: Serbia AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: Argentina AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: Georgia AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: Brazil AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: Mexico About Improvado Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like Genentech, T-Mobile, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role We are looking for a technical specialist who owns the performance of the Improvado website end to end: how it is found (SEO and GEO), how fast and healthy it is, and how well it converts visitors into pipeline. This is an analytics-driven, hands-on role for someone who is as comfortable in Google Search Console, GA4, and the browser dev tools as in a keyword report. Because the website is our main product-facing marketing surface, you will also shape how the product is presented on it. In practice, the role covers part of what product marketing would otherwise do. What You Will Do Technical SEO and GEO Own the technical health of the site: crawlability, indexation, Core Web Vitals, page speed, structured data and schema, rendering, redirects, internal linking, and site architecture. Optimize the site for AI search (generative engine optimization): make Improvado understandable, citable, and recommended in ChatGPT, Perplexity, Google AI Overviews, and similar engines. Monitor visibility in both classic and AI search, and turn the findings into prioritized fixes. Website optimization and conversion Continuously improve page performance, UX, templates, and key conversion paths (demo requests, sign-ups, high-intent pages). Plan and run experiments (A/B tests, template and layout changes, messaging tests) and measure their impact on conversions and pipeline. Work with engineering, design, and external contractors to ship improvements to the website stack (CMS, CDN, caching, tracking). Analytics and measurement Build and maintain dashboards that connect organic and on-site behavior to leads, pipeline, and revenue. Own tracking quality: events, attribution, and data accuracy across GA4, Search Console, and related tools. Analyze data to find growth opportunities, and report findings in clear, decision-ready form. Product and messaging input Use search demand, AI-visibility, and on-site behavior data to guide positioning, messaging, and landing page strategy. Work with stakeholders so website content reflects ICP needs and the product’s value propositions. What We Are Looking For Must have 3+ years in SEO and/or website optimization, with measurable results in organic growth or conversion. Strong technical SEO skills and a good understanding of how websites are built, served, and rendered. Ability and willingness to work in the Eastern Time (EST) time zone, with working hours aligned to the US East Coast. Hands-on experience with GEO or AI search optimization, or a clear, demonstrable track record of working on it. Strong analytics experience: GA4, Google Search Console, and BI or dashboard tools (Looker Studio, Superset, or similar). You build your own reports and draw conclusions from the data. Proficiency with SEO tooling (Ahrefs, Semrush, Screaming Frog, or equivalents). Ability to work effectively with developers, designers, and marketers in a distributed team. Nice to have B2B SaaS or marketing technology background. Experience with Webflow or a similar CMS, plus basic HTML/CSS and JavaScript. SQL or advanced spreadsheet skills; experience with AI-assisted or automated workflows. Experience with CRO and experimentation platforms. Exposure to product marketing, positioning, or messaging. You are Analytical, curious, and driven by measurable outcomes. Self-directed and comfortable owning a channel without heavy supervision. A clear communicator across time zones. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement