Staff PRODUCT ENGINEER (Contract)

Build it. Ship it. Own it.

Location: Argentina, Brazil, Colombia, Chile, Mexico, Dominican Republic, Peru

About Counterpart

Counterpart is an insurtech platform reimagining management and professional liability for the modern workplace. We believe that when businesses lead with clarity and confidence, they become more resilient, more innovative, and better prepared for what's ahead. That's why we built the first Agentic Insurance™ system — where advanced AI and deep insurance expertise come together to proactively assess, mitigate, and manage risk. Backed by A-rated carriers and trusted by brokers nationwide, our platform helps small businesses grow with confidence. Join us in shaping a smarter future, helping businesses Do More With Less Risk®.

The Role

As a Product Engineer at Counterpart, you own problems and drive outcomes. You iron out requirements with stakeholders, partners, and customers. You leverage AI for implementation. You verify the end-to-end result. You iterate until you move the needle.

You run projects with other Product Engineers and AI agents. You know when to delegate to a human, when to delegate to an agent, and when to do it yourself. 

YOU WILL

Own the Problem

• Take accountability for the outcome. 
• Talk directly to your users, stakeholders, and peers to discover the problem. 
• Translate business intents into functional requirements that engineers and agents can build against. Determine where human judgment is non-negotiable and where AI can augment or act autonomously. 
• Own the non-functional technical requirements. Specify the quality bar: performance, scalability, reliability, security, maintainability.

Build with AI

• Write production-quality code across the stack: Python, Django, AWS, React, and PostgreSQL. You are not afraid of any layer.
• Direct agents and review their output with domain depth. Catch what they miss across the functional and non-functional bar: correctness, edge cases, performance, security, testability, readability.
• Evaluate and improve agent output regularly. Track failure modes. Refine the prompts and patterns that lift the quality ceiling over time.
• Run projects that span other Product Engineers and agents. Coordinate work, manage dependencies, and keep things moving without micromanaging.
• Contribute to architectural decisions. Bring options and alternatives, not objections. Know when the elegant solution is the wrong call for a startup moving fast.
• Contribute to and manage the context harness as you build and deliver.

Verify and Iterate

• Surface delivery risks early. Bring solutions, not just problems. Keep your stakeholders informed without turning every risk into a meeting.
• Verify the end-to-end result yourself. Confirm the system does what the requirements say, and that the requirements were right.
• Drive adoption of what you ship. Documentation, enablement, and usage monitoring are part of the job.
• Monitor your services in production. Own the signal. Debug and fix what breaks.
• Participate in support rotations. When users run into issues with what you shipped, you investigate and fix them.
• Iterate until you move the needle. Shipping is not the finish line. Outcome is.

Raise the Bar

• Mentor engineers around you. Give direct, useful feedback. Leave things better than you found them.
• Make deliberate calls on technical debt: when to accumulate it, when to pay it down, when to refactor. Translate trade-offs into language that business leaders can act on.
• Operate to the engineering standards for quality, reliability, and operational excellence.

YOU HAVE

• 10+ years building production web applications across the full stack. The years are the floor, not the bar. What matters is whether you have actually done this: owned a problem end-to-end, written the spec, built the thing, coordinated the work, and shipped it without someone else holding the thread.
• Demonstrated experience gathering requirements directly. You have interviewed users, customers, and partner teams, and turned ambiguous intent into specs that engineers and agents can build against.
• Demonstrated experience owning both functional and non-functional requirements. You have defined what a system must do and held the line on how well it must do it.
• A track record of owning a domain or initiative without close supervision. You have navigated ambiguity, made judgment calls, and been accountable for the outcome.
• Extreme ownership and a bias for action. You do not sit and wait. You chase stakeholders, customers, and answers when you need them.
• Experience coordinating across engineers and AI agents on a shared initiative. You have managed the work without holding a formal management title.
• Strong technical judgment and the depth to catch what AI-generated code gets wrong: not syntax, but correctness, architecture, intent.
• Proficiency with Python and Django. Working knowledge of TypeScript, React, and PostgreSQL.
• Proficiency in developing with AI tools (Claude Code, Cursor, OpenAI Codex, similar) and the drive to stay ahead of how AI development practices are evolving.
• Domain curiosity. You learn the business context your work supports, not just the systems. You understand why the problem matters, not just how to solve it.
• The ability to communicate clearly across engineering, product, and business, translating technical complexity without losing meaning.
• Low ego and high Emotional Quotient (EQ). You influence without authority, take feedback well, and leave your ego out of technical decisions.
• Experience working with distributed, remote teams.

HOW THIS ROLE WORKS

Product Engineering exists to collapse the distance between a problem and a working solution. You own a problem or part of a vision. You shape it with stakeholders. You build it with AI. You verify it end-to-end. You iterate until the metric moves.

You work within the Context Architecture, a shared system of documentation, design patterns, and domain knowledge that gives you the technical context to make autonomous decisions at every step.

This is not a role for engineers who need to be told how. It is a role for engineers who can take a problem, fill in the gaps with good judgment, and ship something that works.

WHO YOU WILL WORK WITH

• Derrick Franco, Principal Engineer: After teaching himself to code at 13, Derrick went on to co-found Jumpstart in addition to building out the technical divisions at InvestorsAlley and Phinaz Media Group. Nowadays Derrick spends his time reading, with his wife, and working on his podcast The Future of Work Project.
• Julian Prokay, Principal Engineer: A veteran of the SaaS space with experience working on both student systems and construction management software. In his free time, he enjoys history podcasts and fantasy literature.
• Tony Nguyen, Engineering Manager: Tony is an engineering and platform leader with 25+ years of leadership experience at companies like Sony PlayStation Network, Intuit TurboTax, and ServiceNow. He thrives at building products, scaling teams, and leading organizations, but more so building people. He believes the best leadership and engineering comes from bringing your full identity to work. For him that's faith, family, and sports! Outside of work, you can catch him on the couch with his 3 adult children watching anime, going to Disneyland, or having game nights.
• Ron Alexessen, Engineering Manager: With experience at Hewlett-Packard, New Relic, Rackspace, and consulting agencies, Ron has built teams and shaped technical culture across different environments. He's passionate about AI-enabled development as a force multiplier and building solutions that create real business impact. Outside work, he boulders, runs, rides gravel bikes, and co-parents active teenagers, embracing structured chaos in all of it.
• Newton Truong, Engineering Manager: Newton joins Counterpart with 7+ years of experience in platform and data engineering. In his last company Thrive Market, he had a hand in building out new microservices and architecting data pipelines with Airflow and Spark. He's vegetarian and loves trying new restaurants when traveling. Nowadays he's busy keeping up with his 2-year-old and doing outdoor activities with his family.
• John Mendez, Engineering Manager: John has experience working at companies of all sizes. He enjoys startups and small-to-medium businesses, where he can wear multiple hats and help deliver solutions. Outside of work, he stays busy with his four kids and their activities. He also makes time to stay active by working out at home and running or walking with his dog.

COUNTERPART'S VALUES

• Conjoin Expectations - it is the cornerstone of autonomy. Ensure you are aware of what is expected of you and clearly articulate what you expect of others.
• Speak Boldly & Honestly - the only failure is not learning from mistakes. Don't cheat yourself and your colleagues of the feedback needed when expectations aren't being met.
• Be Entrepreneurial - control your own destiny. Embrace action over perfection while navigating any obstacles that stand in the way of your ultimate goal. Leverage AI ruthlessly. We measure success by outcomes, not lines of code written. Use every available AI tool to ship faster and think more strategically.
• Practice Omotenashi ("selfless hospitality") - trust will follow. Consider every interaction with internal and external partners an opportunity to develop trust by going above and beyond what is expected.
• Hold Nothing As Sacred - create routines but modify them routinely. Take the time to reflect on where the business is today, where it needs to go, and what you have to change in order to get there.
• Prioritize Wellness - some things should never be sacrificed. We create an environment that stretches everyone to grow and improve, which is fulfilling, but is only one part of a meaningful life.

WE OFFER

1. Work from Anywhere - Counterpart is a fully distributed company, meaning there is no office. We allow employees to work from wherever they do their best work, of course prioritizing meetings that often happen in US time zones.
2. Language Classes - We sponsor up to $100 per calendar year to be used towards language classes to help support your English language skills.
3. Paid Vacation and Time Off
4. Parental Leave - Development Partners will be eligible for unpaid Parental Leave to bond with a newborn, newly-adopted, or newly placed child. Under this policy, development partners and independent contractors will be eligible for up to 8 weeks of unpaid parental leave. Any time off will be subject to approval and must be requested at least 45 days in advance.
5. Computer - We reimburse you for your locally procured MacBook Pro. If you are still with the company after one year, it is yours to keep!

Our estimated pay range for this role is USD $90,000 - $110,000 annually. Contractor compensation is determined by a variety of factors, including but not limited to, market data, location, internal equitability, and experience.

We are committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work, regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.

We are an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation.

Your role
Dialpad’s AI Engineering organization is responsible for building and maintaining customer-facing AI features at scale across all of our cloud-native products and services. Every day, millions of users worldwide leverage our technology to communicate effectively and efficiently.

Dialpad's Agentic Runtime team owns the infrastructure and execution engine that runs AI agents at scale across Dialpad's core product modalities — including voice, messaging, video, and digital engagement. From multi-step task orchestration and tool execution to real-time context management and agent memory, our team builds the foundational platform that powers Dialpad's next-generation intelligent, autonomous experiences. Our teams are highly collaborative and comprise cross-disciplinary professionals, including Product Managers, QA Specialists, and Engineers specializing in Distributed Systems, ML Infrastructure, and Platform Engineering.

This position reports to the Engineering Manager, who is based in Kitchener, CA, and has the opportunity to be based in our Buenos Aires, Argentina office.

What you’ll do

• Contribute to the design, development, and maintenance of agentic runtime systems, including agent orchestration, tool execution pipelines, and multi-step reasoning loops.
• Build and optimize core runtime components, including task planners, action dispatchers, memory managers, and context window management systems.
• Work on agent coordination techniques, including dynamic tool selection, parallel agent execution, state management, and result aggregation across multi-agent workflows.
• Maintain and enhance highly scalable agentic platforms with a focus on low-latency execution, cost efficiency, and deterministic behavior.
• Ensure high availability, reliability, and fault tolerance in agent runtime services, including graceful degradation when LLM or tool calls fail.
• Collaborate with cross-functional teams — including ML researchers, product, and platform engineers — to translate agentic product requirements into robust runtime infrastructure.
• Develop and optimize real-time distributed systems, microservices, and event-driven architectures powering agentic task execution.
• Design and implement sandboxed execution environments for safe agent use of tools, code execution, and external API calls.
• Implement and maintain monitoring, alerting, and performance metrics covering agent run success rates, token consumption, latency, and cost attribution.
• Evaluate and integrate emerging agentic frameworks, LLM APIs, and tooling ecosystems to continuously improve platform capabilities.
• Write clean, modular, and well-tested code while following best engineering practices in a rapidly evolving problem space.
• Participate in code reviews to ensure the quality, maintainability, and scalability of runtime components.
• Provide mentorship and technical guidance to junior engineers navigating the unique challenges of agentic systems.

Skills you’ll bring

• 3–6 years of experience in distributed systems, platform engineering, or ML infrastructure, with exposure to LLM-based or agentic systems strongly preferred.
• Strong understanding of agent architectures, including ReAct, plan-and-execute, and multi-agent coordination patterns.
• Deep knowledge of context management, prompt lifecycle, tool-call protocols (e.g., function calling, MCP), and agent memory strategies (short-term, episodic, and long-term).
• Experience integrating and managing external tool ecosystems, including web search, code interpreters, databases, and third-party APIs.
• Familiarity with retrieval-augmented generation (RAG) and how retrieval fits into broader agentic pipelines.
• Understanding of LLM output reliability challenges — hallucination, non-determinism, and retry/fallback strategies at runtime.
• Proficiency in Go and Python 3 (experience with Rust or TypeScript is a plus).
• Strong understanding of distributed systems, microservices, and event-driven architectures suited to long-running agent tasks.
• Passion for real-time performance optimization, including streaming responses, async execution, and parallel tool invocation.
• Experience with API design using OpenAPI, Swagger, or equivalent, with an eye toward agentic interaction patterns.
• Knowledge of gRPC or equivalent RPC protocols for inter-service communication within agent runtimes.
• Experience with Docker and Kubernetes, including managing long-running or stateful agent workloads in containerized environments.
• Familiarity with cloud platforms (GCP preferred, AWS/Azure optional), including managed services relevant to agentic workloads such as queuing, secrets management, and compute autoscaling.
• Hands-on experience with Infrastructure as Code tools like Terraform or Ansible.
• Knowledge of CI/CD frameworks and continuous delivery practices, with comfort shipping infrastructure in a fast-moving research-adjacent environment.

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 
• Our borderless, global framework, which enables seamless collaboration 

The role  

As an Agentic AI Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring solid senior-level experience, a growth mindset and a drive to make a lasting impact.

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

We are building a new AI capability for our client focused on designing and delivering agentic AI systems that materially improve seller productivity and decision‑making. The first major initiative is a chat‑based seller assistant that integrates enterprise data, surfaces insights, and guides sellers before and during customer interactions—reducing time spent in spreadsheets and increasing the quality of face‑to‑face sales conversations. 

This role is ideal for an engineer excited by early‑stage AI system design, ambiguity, and hands‑on experimentation with large language models. While deep prior experience with agentic systems is rare, we are especially interested in candidates who have built, prototyped, or meaningfully experimented with modern LLM‑driven applications. 

Role responsibilities 

• Design and build agentic AI systems that facilitate conversational workflows for seller enablement 

• Develop a chat‑based seller assistant that:  

• Answers seller questions using enterprise data 

• Provides insights on ordering, pricing, and customer behavior 

• Generates pre‑visit one‑pagers to guide sales conversations 

• Integrate large language models (e.g., Claude, ChatGPT) with internal data sources and APIs 

• Apply prompt engineering, context engineering, and agent orchestration techniques to improve reliability and usefulness 

• Build and evolve the platform using LangChain and LangGraph (initially in Python) 

• Design persistence and data access layers using Mongo or other data stores 

• Collaborate closely with product, analytics, and engineering partners to shape both technical direction and use cases 

• Serve as a champion for modern AI coding assistant tools (e.g., Cursor) within the team 

• Help define standards and best practices as this AI capability scales 

Must have qualifications 

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

• Experience as a full‑stack or backend engineer building production systems 

• Strong foundation in software engineering fundamentals (APIs, data modeling, system design) 

• Familiarity with databases, data stores, and data modeling concepts (experience with MongoDB is a plus, but not required) 

• Hands‑on experience working with LLMs (via OpenAI, Anthropic, or similar), including prompt design and evaluation 

• Experience integrating applications with enterprise data sources (APIs, databases, analytics platforms) 

• Comfort working in early‑stage, ambiguous problem spaces where patterns are still emerging 

• Ability to communicate clearly with technical and non‑technical stakeholders 

• Willingness to work on a Mac‑based development environment 

• Experience using AI‑assisted development tools (Cursor, Copilot, etc.) as part of daily workflow 

• Advanced English skills 

Nice to have qualifications   

• Experience building or experimenting with agentic AI systems or multi‑step LLM workflows 

• Familiarity with LangChain, LangGraph, or similar orchestration frameworks 

• Python experience (Node.js / TypeScript also valued) 

• Experience with MongoDB or similar NoSQL data stores 

• Experience with enterprise platforms such as Salesforce, Snowflake, or similar 

• Exposure to Google AI / Google Cloud services 

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. 

The benefits  

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts
• Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

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.

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 
• Our borderless, global framework, which enables seamless collaboration 

The role  

As an Agentic AI Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring solid senior-level experience, a growth mindset and a drive to make a lasting impact.

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

We are building a new AI capability for our client focused on designing and delivering agentic AI systems that materially improve seller productivity and decision‑making. The first major initiative is a chat‑based seller assistant that integrates enterprise data, surfaces insights, and guides sellers before and during customer interactions—reducing time spent in spreadsheets and increasing the quality of face‑to‑face sales conversations. 

This role is ideal for an engineer excited by early‑stage AI system design, ambiguity, and hands‑on experimentation with large language models. While deep prior experience with agentic systems is rare, we are especially interested in candidates who have built, prototyped, or meaningfully experimented with modern LLM‑driven applications. 

Role responsibilities 

• Design and build agentic AI systems that facilitate conversational workflows for seller enablement 

• Develop a chat‑based seller assistant that:  

• Answers seller questions using enterprise data 

• Provides insights on ordering, pricing, and customer behavior 

• Generates pre‑visit one‑pagers to guide sales conversations 

• Integrate large language models (e.g., Claude, ChatGPT) with internal data sources and APIs 

• Apply prompt engineering, context engineering, and agent orchestration techniques to improve reliability and usefulness 

• Build and evolve the platform using LangChain and LangGraph (initially in Python) 

• Design persistence and data access layers using Mongo or other data stores 

• Collaborate closely with product, analytics, and engineering partners to shape both technical direction and use cases 

• Serve as a champion for modern AI coding assistant tools (e.g., Cursor) within the team 

• Help define standards and best practices as this AI capability scales 

Must have qualifications 

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

• Experience as a full‑stack or backend engineer building production systems 

• Strong foundation in software engineering fundamentals (APIs, data modeling, system design) 

• Familiarity with databases, data stores, and data modeling concepts (experience with MongoDB is a plus, but not required) 

• Hands‑on experience working with LLMs (via OpenAI, Anthropic, or similar), including prompt design and evaluation 

• Experience integrating applications with enterprise data sources (APIs, databases, analytics platforms) 

• Comfort working in early‑stage, ambiguous problem spaces where patterns are still emerging 

• Ability to communicate clearly with technical and non‑technical stakeholders 

• Willingness to work on a Mac‑based development environment 

• Experience using AI‑assisted development tools (Cursor, Copilot, etc.) as part of daily workflow 

• Advanced English skills 

Nice to have qualifications   

• Experience building or experimenting with agentic AI systems or multi‑step LLM workflows 

• Familiarity with LangChain, LangGraph, or similar orchestration frameworks 

• Python experience (Node.js / TypeScript also valued) 

• Experience with MongoDB or similar NoSQL data stores 

• Experience with enterprise platforms such as Salesforce, Snowflake, or similar 

• Exposure to Google AI / Google Cloud services 

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. 

The benefits  

This is a Full time position based in Colombia. The offered salary range is $20,000,000 COP - $26,000,000 COP monthly, depending on experience and location. 

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts
• Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

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.

The Role

AI is no longer a roadmap item — it's the operating system for how modern growth teams win. We're hiring a AI Native Engineer, Growth Marketing to be the hands-on builder who embeds AI into every corner of how our Growth team works: performance marketing, creative production, CRM, landing pages, growth ops, and beyond.

This is a rare hybrid role. You're equal parts engineer and growth practitioner — someone who can write a Python script in the morning, ship a Braze-connected AI workflow by afternoon, and explain the business impact to a non-technical stakeholder by EOD. You don't need to have done this at scale before — you need to be obsessed with building at the frontier of what's possible and have the technical chops to make it real.

You'll report directly to the Head of Growth and work across every subteam in the Growth org as their embedded AI engineer.

Responsibilities:

• Performance Marketing: Build AI-powered tools to automate bid strategy analysis, budget pacing alerts, creative performance scoring, and anomaly detection across paid channels (SEM, Meta, Affiliate, YouTube, etc.)
• Creative Studio: Develop AI workflows for ad copy generation, creative brief automation, image asset variation at scale, and creative performance feedback loops between analytics and the studio team
• CRM & Lifecycle: Implement AI-driven personalization and send-time optimization across email, SMS, push, and in-app channels; build agentic workflows that pull Snowflake data, generate segment logic, and trigger Braze campaigns with minimal manual intervention
• Landing Pages & Conversion: Automate LP variant generation, headline testing ideation, and personalization logic by audience segment or traffic source
• Growth Ops: Build internal AI tools — dashboards, Slack bots, report generators — that reduce repetitive analytical work and accelerate decision-making across the team
• Growth Product: Partner with Product and Engineering to identify where AI-powered features (recommendations, dynamic content, smart nudges) can accelerate funnel conversion and retention
• Tooling & Infrastructure: Evaluate, implement, and maintain the AI/ML toolstack that powers Growth — from LLM APIs to workflow orchestration tools to data pipelines

What Success Looks Like

• A measurable reduction in manual hours across mundane Growth through AI-driven automation
• At least 5-10 production-grade AI tools or workflows live and actively used by the team within the first 4 months
• CRM campaigns that are more personalized, faster to launch, and higher-performing because of AI assist
• Creative output volume increases without a proportional increase in headcount
• The Growth team thinks of you first when they want to do something smarter, faster, or at scale

Qualifications:

• 2–5 years of engineering or technical experience, with meaningful hands-on work applying AI/LLMs to real business problems (side projects count — we care about what you've built, not just where)
• Proficiency in Python or Typescript and comfort working with APIs (OpenAI, Anthropic, or similar LLM providers)
• Build repeatable skills or plugins for popular LLM clients to empower your team
• Educate and mentor team members to become more AI-Native
• A builder's mentality: you'd rather ship a working prototype than write a spec about one
• Ability to work cross-functionally and translate between technical and non-technical stakeholders

Preferred requirements:

• Experience with workflow orchestration tools (Agent SDK, n8n, Make, Zapier, or custom Typescript/Python pipelines)
• Prior work at a DTC subscription company or growth-stage startup
• Familiarity with prompt engineering, RAG architectures, or fine-tuning
• Experience building internal tools used by non-technical teams
• Familiarity with marketing platforms and data infrastructure — ideally some combination of Braze, Google Ads, Meta Ads Manager, Snowflake, or equivalent
• Strong enough understanding of growth marketing to ask the right questions and build tools that practitioners actually want to use

Technologies You'll Use

• LLM APIs: OpenAI, Anthropic, and/or open-source models
• CRM & Marketing: Braze, Google Ads, Meta Ads Manager
• Data: Snowflake, SQL, Tableau, dbt, Hex
• Orchestration: Typescript, Agent SDK, Vercel AI SDK, Python, n8n, Make, or similar
• Collaboration: Slack, Notion, Jira, Google Workspace

Benefits

 🩺 Health Insurance coverage (Canada Life)

⛱ Flexible Paid Time Off

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave.

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly.

🧘🏽‍♀️ Wellness perks: fitness subsidies to build a healthy lifestyle

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

The Role

AI is no longer a roadmap item — it's the operating system for how modern growth teams win. We're hiring a AI Native Engineer, Growth Marketing to be the hands-on builder who embeds AI into every corner of how our Growth team works: performance marketing, creative production, CRM, landing pages, growth ops, and beyond.

This is a rare hybrid role. You're equal parts engineer and growth practitioner — someone who can write a Python script in the morning, ship a Braze-connected AI workflow by afternoon, and explain the business impact to a non-technical stakeholder by EOD. You don't need to have done this at scale before — you need to be obsessed with building at the frontier of what's possible and have the technical chops to make it real.

You'll report directly to the Head of Growth and work across every subteam in the Growth org as their embedded AI engineer.

Responsibilities:

• Performance Marketing: Build AI-powered tools to automate bid strategy analysis, budget pacing alerts, creative performance scoring, and anomaly detection across paid channels (SEM, Meta, Affiliate, YouTube, etc.)
• Creative Studio: Develop AI workflows for ad copy generation, creative brief automation, image asset variation at scale, and creative performance feedback loops between analytics and the studio team
• CRM & Lifecycle: Implement AI-driven personalization and send-time optimization across email, SMS, push, and in-app channels; build agentic workflows that pull Snowflake data, generate segment logic, and trigger Braze campaigns with minimal manual intervention
• Landing Pages & Conversion: Automate LP variant generation, headline testing ideation, and personalization logic by audience segment or traffic source
• Growth Ops: Build internal AI tools — dashboards, Slack bots, report generators — that reduce repetitive analytical work and accelerate decision-making across the team
• Growth Product: Partner with Product and Engineering to identify where AI-powered features (recommendations, dynamic content, smart nudges) can accelerate funnel conversion and retention
• Tooling & Infrastructure: Evaluate, implement, and maintain the AI/ML toolstack that powers Growth — from LLM APIs to workflow orchestration tools to data pipelines

What Success Looks Like

• A measurable reduction in manual hours across mundane Growth through AI-driven automation
• At least 5-10 production-grade AI tools or workflows live and actively used by the team within the first 4 months
• CRM campaigns that are more personalized, faster to launch, and higher-performing because of AI assist
• Creative output volume increases without a proportional increase in headcount
• The Growth team thinks of you first when they want to do something smarter, faster, or at scale

Qualifications:

• 2–5 years of engineering or technical experience, with meaningful hands-on work applying AI/LLMs to real business problems (side projects count — we care about what you've built, not just where)
• Proficiency in Python or Typescript and comfort working with APIs (OpenAI, Anthropic, or similar LLM providers)
• Build repeatable skills or plugins for popular LLM clients to empower your team
• Educate and mentor team members to become more AI-Native
• A builder's mentality: you'd rather ship a working prototype than write a spec about one
• Ability to work cross-functionally and translate between technical and non-technical stakeholders

Preferred requirements:

• Experience with workflow orchestration tools (Agent SDK, n8n, Make, Zapier, or custom Typescript/Python pipelines)
• Prior work at a DTC subscription company or growth-stage startup
• Familiarity with prompt engineering, RAG architectures, or fine-tuning
• Experience building internal tools used by non-technical teams
• Familiarity with marketing platforms and data infrastructure — ideally some combination of Braze, Google Ads, Meta Ads Manager, Snowflake, or equivalent
• Strong enough understanding of growth marketing to ask the right questions and build tools that practitioners actually want to use

Technologies You'll Use

• LLM APIs: OpenAI, Anthropic, and/or open-source models
• CRM & Marketing: Braze, Google Ads, Meta Ads Manager
• Data: Snowflake, SQL, Tableau, dbt, Hex
• Orchestration: Typescript, Agent SDK, Vercel AI SDK, Python, n8n, Make, or similar
• Collaboration: Slack, Notion, Jira, Google Workspace

Benefits

🩺  Health Insurance coverage

🌅 401k Plan

⛱ Unlimited PTO 

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

🧘🏽‍♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

Are you an experienced geospatial professional eager to shape the future of AI? We’re developing a geospatial reasoning agent focused on Crisis Response—helping AI systems understand, assess, and predict real-world events where data is uncertain or incomplete. Your expertise will guide model development and evaluation, laying the foundation for future geospatial reasoning and forecasting applications.

We’re looking for experts with deep experience in geospatial analysis, crisis response, or related domains such as damage assessment, agriculture, site selection, supply chain optimization, or forecasting. You’ll evaluate AI-generated outputs, identify analytical weaknesses, and design metrics and test cases that advance model understanding and predictive accuracy.

On a typical day, you’ll review geospatial scenarios, validate model outputs, define and refine reasoning frameworks, and collaborate with our team to improve data-driven evaluations.

Ideal candidates bring professional experience in geospatial analysis, GIS systems, or spatial modeling within industries such as crisis management, logistics, or environmental planning. Proficiency with geospatial tools and libraries (e.g., QGIS, ArcGIS, GDAL, PostGIS) is preferred. Strong reasoning, attention to detail, and the ability to communicate complex spatial relationships clearly are essential.

Ready to apply your geospatial expertise to the frontier of AI? Apply today and help design intelligent systems capable of supporting real-time global decision-making.

We offer a pay range of $24 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor, you’ll supply a secure computer and high-speed internet connection; company-sponsored benefits such as health insurance and PTO do not apply.

Job title: Geospatial Reasoning Specialist – AI Trainer
Employment type: Contract
Workplace type: Remote
Seniority level: Senior Level