Land Acquisition Manager

🏢 Summary: The offer is for a Lead Real Estate Analyst responsible for driving financial and strategic analysis for critical AI infrastructure real estate decisions, including site evaluation, deal structuring, and portfolio performance monitoring. The role partners with development, finance, and operations teams to lead underwriting, market analysis, and transaction execution across multiple concurrent projects. It is a high-visibility, onsite position with direct impact on site selection and investment strategy. 🗂️ Requirements: 3–5 years of experience in real estate transactions, development, or related transaction-oriented role, Proficiency in Microsoft Excel or Google Sheets, Strong knowledge of real estate development fundamentals (title, surveys, permits, lease structures, cap rates, DCF, return on cost, development economics), Ability to synthesize large datasets and present actionable recommendations to senior stakeholders, Experience with complex, multi-party real estate transactions in a fast-paced environment, Bachelor’s degree in Finance, Real Estate, Economics, or related field 📃 Skills: Excel, GoogleSheets, DCF, FinancialModeling, Underwriting, CapRates, ReturnOnCost, MarketAnalysis, Zoning, Entitlements 🏢 Description: Why join Giga The Pace: We're building at a speed most companies talk about but never actually operate at. If you've been bored somewhere else, you won't be here. The Impact: Every person at Giga touches the work that matters. No layers, no waiting for approval chains. You'll see your fingerprints on what we ship. The Team: A team of operators defining the future of AI infrastructure. We recruit A-players from the most innovative companies in the world, and they choose Giga because the work here means more. The Moment: AI doesn't run without power, and that's us. Giga is the picks and shovels behind the AI revolution. This industry is about to explode, and you'll be in the room where it's already happening. What you'll do As Land Acquisition Manager at Giga, you will own the land acquisition, surface rights negotiation, and lease analysis that drives some of the most critical real estate decisions in AI infrastructure. You'll work directly with landowners, surface holders, and third-party brokers to secure the sites that power our development pipeline — while partnering with legal, finance, and operations to structure deals and keep projects moving. This is a high-visibility role where your work directly shapes where and how Giga builds. Where you'll work We are an in-office culture — velocity matters when you're building physical infrastructure, and the best decisions happen in the room. This role is ideally based in our Houston offices, with full-time onsite expectations outside of bi-weekly WFH Fridays. That said, we will make exceptions for truly exceptional talent if you live outside one of our hubs. If you're the right person for this role, we'll have a conversation about what works. Responsibilities Track and manage an active pipeline of real estate and land opportunities, maintaining deal status, key milestones, and financial summaries across multiple concurrent transactions Identify, contact, and negotiate directly with surface owners and landowners to secure access agreements, ROW/easements, ground leases, and purchase contracts Review, interpret, and summarize lease and contract language — identifying provisions that impact site access, development rights, operational constraints, and financial obligations Conduct market research and comparable analyses to evaluate site values, rental rates, and land market dynamics in target geographies Lead financial modeling and underwriting for land acquisitions, ground leases, and build-to-suit developments across Giga's site pipeline Support site selection by synthesizing zoning, entitlement risk, infrastructure constraints, and financial feasibility into clear investment recommendations Coordinate third-party surveyors, field brokers, and contractors; accompany teams to the field as needed to support site assessment and due diligence Collaborate with legal, development, and operations teams to review LOIs, PSAs, surface use agreements, and lease agreements, ensuring economic terms align with underwriting assumptions Maintain accurate land and lease records, deal documentation, and pipeline reporting Serve as a point of contact for landowner relationships, resolving issues and managing ongoing obligations on Giga's active asset base Requirements Demonstrated ability to negotiate and draft land agreements, surface use agreements, ROW/easements, or similar instruments Strong working knowledge of real estate and land fundamentals: lease structures, title, surveys, permits, access rights, development economics, and contract interpretation Experience reviewing and analyzing complex contractual language, identifying key obligations and risk provisions Demonstrated ability to synthesize large amounts of data and present clear, actionable recommendations to senior stakeholders Comfortable coordinating third parties in the field and managing multiple concurrent workstreams under time pressure Proficiency in Microsoft & Google suites Bonus Points Experience in data center, industrial, or energy development Familiarity with power infrastructure, utility coordination, or site feasibility analysis for high-load facilities Background in oil and gas land, surface rights, or mineral rights work Benefits Subsidized health, dental, and vision insurance Equity (options) in a rapidly growing startup 401(k) with 4% employer match Unlimited PTO Parental leave Healthcare and Dependent Care Flexible Spending Accounts (FSA) or Health Savings Account (HSA) Commuter benefits Who we hire We hire people who thrive in chaos and get sharper under pressure. You don't wait to be told what to do, you spot the gap and fill it. When there's work to be done, you do it. You make decisions with the information you have, move fast, and adjust along the way. We're not looking for perfect; we're looking for people who get things done. Equal Opportunity Employer Statement Giga Energy is an equal opportunity employer and is committed to fostering an inclusive and diverse workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Giga Energy complies with all applicable labor laws, including the California Fair Employment and Housing Act (FEHA) and other relevant state and federal regulations. We provide reasonable accommodations for qualified individuals with disabilities and encourage applicants who require accommodations during the hiring process to contact us.

🏢 Summary: Hands-On Engineering Manager role focused on building and shipping AI-native, agentic banking products that operate across voice, chat, and digital channels. The position involves architecting low-latency distributed backend systems, orchestrating multi-agent LLM workflows, and leading a high-performance engineering team while remaining deeply hands-on. The goal is to deliver production-grade AI systems that autonomously power real-time financial customer experiences. 🗂️ Requirements: 8+ years backend engineering experience, Experience building distributed systems, Experience with low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating systems with LLMs, 2+ years engineering management or technical leadership experience, Experience designing and orchestrating agentic workflows, Proficiency in Typescript and/or at least two backend languages, Strong understanding of distributed systems, concurrency, reliability, Experience deploying AI systems in cloud environments, Experience building high-concurrency, fault-tolerant systems, Experience implementing observability, monitoring, and testing for production systems, Experience ensuring security and safe handling of financial data 📃 Skills: Typescript, Node.js, Go, Java, Rust, LLM, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, Chat, APIs, Cloud, Observability, Monitoring, Testing, Security, ReinforcementLearning, MultiAgentSystems 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Hands-On Engineering Manager role focused on building and orchestrating AI-native, agentic systems for real-time voice and chat in banking. The position combines deep backend distributed systems expertise with LLM-driven multi-agent architectures to deliver low-latency, production-grade AI products. You will lead a high-performance team while remaining hands-on in architecting and shipping scalable, reliable AI systems. 🗂️ Requirements: 8+ years backend engineering experience in distributed systems, Experience building low-latency systems (voice, telephony, streaming, chat), 3+ years working with LLM-powered or AI-driven systems in production, Hands-on experience integrating and orchestrating LLMs, 2+ years engineering management or technical leadership experience, Strong proficiency in TypeScript and/or at least two backend languages (Node.js, Go, Java, Rust), Deep understanding of distributed systems, concurrency, and reliability, Experience deploying AI systems in cloud environments, Experience designing agentic workflows and multi-agent systems 📃 Skills: TypeScript, Node.js, Go, Java, Rust, LLMs, AgenticAI, DistributedSystems, Concurrency, Telephony, Streaming, APIs, Cloud, ReinforcementLearning, Monitoring, Observability 🏢 Description: Banking is being reimagined—and customers expect every interaction to be easy, personal, and instant. We are building a universal banking assistant that millions of U.S. consumers can use to transact across all financial institutions and, over time, autonomously drive their financial goals. Powered by our proprietary BankGPT platform, this assistant is positioned to displace age-old legacy systems within financial institutions and own the end-to-end CX stack, unlocking a $200B opportunity and potentially replacing multiple publicly traded companies. Ultimately, our mission is to drive financial well-being for millions of consumers. With over two-thirds of Americans living paycheck to paycheck, 50% holding less than $500 in savings, and only 17% financially literate, we aim to put financial well-being on autopilot to help solve this problem.About the Role We are building AI-native, agentic products that redefine how customers interact with financial institutions across voice, chat, and digital channels. We are looking for a Hands-On Engineering Manager – Agentic AI Products who operates with an AI-first mindset, has deep backend systems experience, and is comfortable orchestrating multiple AI agents to ship production-grade systems. This role requires someone who: Has built complex distributed backend systems Understands low-latency architectures (voice, telephony, streaming, chat) Is fluent in modern agentic AI engineering Thinks like a founder Leads by building Raises the engineering bar You will architect, review, code, debug, and ship along with building your high performance engineering team. What You'll Do 1. Lead with an AI-First Engineering Mindset Drive AI-first thinking across product architecture and execution. Embed LLMs, multi-agent systems, and structured reasoning into customer-facing workflows. Champion agentic engineering principles across your team. Evaluate and adopt emerging AI capabilities pragmatically and responsibly. Raise the quality bar for AI-generated and human-written code alike. 2. Build and Orchestrate Agentic Systems Architect and implement systems that coordinate multiple AI agents with memory, planning, reflection, and tool use. Be hands-on in coding, agent loop design, evaluation, and reinforcement strategies. Actively participate in the code base Design orchestration layers that convert AI reasoning into reliable execution. Build control frameworks around LLMs for grounding, safety, and deterministic behavior. Develop evaluation pipelines to ensure agents meet production standards. 3. Own Low-Latency, High-Concurrency Backend Systems Design distributed backend systems serving real-time voice and chat interactions. Optimize latency-sensitive systems across telephony, streaming, and API layers. Build event-driven architectures that handle high concurrency and fault tolerance. Implement state management and memory layers for conversational agents. Drive reliability, failover, and graceful degradation strategies. 4. Ship Production-Ready AI Products Ensure AI-generated outputs translate into robust, testable, production-quality code. Maintain high standards for observability, monitoring, and debugging. Build automation and testing strategies for agent-based systems. Ensure security, compliance, and safe handling of financial data. Create durable systems that scale with increasing AI complexity. Lead by example in adopting AI tooling (Cursor, Claude Code, LLM automation) to improve engineering velocity and code quality 5. Operate Like a Founder Demonstrate extreme ownership across product, architecture, and delivery. Drive clarity in ambiguous problem spaces. Move quickly without compromising engineering rigor. Build and grow a high-performance team with bias to action. Set culture around accountability, urgency, and craftsmanship. Required Qualifications 8+ years of backend engineering experience building distributed systems. Strong experience with low-latency systems such as: Voice / telephony platforms Real-time streaming systems Chat or messaging architectures 3+ years working with LLM-powered or AI-driven systems in production Hands on experience building systems that interface with LLMs. 2+ years experience in engineering management or technical leadership with a proven ability to grow and mentor engineers Hands-on experience designing and orchestrating agentic workflows. Strong proficiency in Typescript and/or at least two backend languages (Node.js, Go, Java, Rust etc) Deep understanding of distributed systems, concurrency, and reliability. Experience managing engineers while remaining deeply hands-on. Experience deploying AI systems in cloud environments. Product Mindset: You care deeply about the product experience Strongly Preferred Experience building AI-native customer-facing products. Experience in Fintech or regulated environments. Familiarity with multi-agent architectures and reasoning frameworks. Experience with reinforcement learning or adaptive optimization loops. Experience building structured evaluation and monitoring for AI agents. Who You Are You care deeply about engineering quality and raise the bar for everyone around you. You demonstrate AI-first approaches when solving problems. You move fast and take ownership beyond your scope. You operate with founder-level urgency and accountability. You build teams that execute with discipline and craftsmanship. You are comfortable orchestrating multiple AI agents to produce production-ready outcomes. What Makes This Role Matters? Agentic engineering is changing how products are built. This role defines how: AI systems reason in real time Voice and chat agents operate under latency constraints Financial workflows become autonomous yet safe Multiple AI agents collaborate to produce deterministic, high-quality outcomes You will lead the engineering effort that transforms AI from an assistant into a production-grade system embedded deeply into customer experiences. We value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Palo Alto or San Francisco office hub and this is an -site role. Compensation: Base Salary is expected to be between $200,000 - $240,000, plus performance bonus and equity options Exact compensation may vary based on skills and location. The base salary range represents the minimum and maximum of the salary range for this position based at our Palo Alto headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of out competitive total rewards package, which also includes equity awards (a new hire grant), competitive health and wellness benefits. What We Offer 100% paid health, dental & vision care 401(k) match & financial wellness perks Discretionary PTO + paid parental leave Mental health, wellness & family benefits A mission-driven team shaping the future of banking At Interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.

🏢 Summary: Engineering leadership role to build and scale an AI Labs team developing autonomous AI agents for enterprise commerce. Responsible for defining the architecture, shipping production-grade agentic AI systems, and driving AI-assisted development at startup speed within a pre-IPO environment. The role combines hands-on technical direction with ownership of infrastructure, quality, and engineering execution. 🗂️ Requirements: Proven experience building and scaling high-performing engineering teams, Hands-on expertise in software architecture and system design, Experience shipping AI or LLM-based products to production, Deep knowledge of LLM orchestration and agent architectures, Experience with AI-assisted development tools in engineering workflows, Ownership of infrastructure efficiency, reliability, and product quality metrics, Ability to operate at startup pace with rapid release cycles, Onsite presence in Mountain View, CA 📃 Skills: LLMs, GPT-4, Claude, AgenticAI, Architecture, Orchestration, AIDevelopment, Cursor, OpenSource, Infrastructure, DistributedSystems 🏢 Description: CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week. 2,200+ Customers 10 of Top 12 CPG Companies 900+ Retailers Connected $200M+ Raised Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO.The Problem: We have thousands of enterprise users, proven product-market fit across digital shelf analytics, retail media, and sales operations, and the Fortune 100 running on our platform. That part works. Now we are building something new: autonomous AI agents that are already in customer hands and scaling fast. This is a 0-to-1 build inside a company that has the distribution, the data, and the customers to make it real. The AI Labs team operates as a startup within the company. It needs its own engineering leader. Someone who can recruit a world-class team in Mountain View, set the technical direction for agentic AI in commerce, and ship at a pace that matches the opportunity. We have engineering teams across the US, India, Canada, and the UK. Mountain View is the center of gravity for AI leadership. This role reports directly to the Founders. We ship with Claude, GPT-4, and open-source models in production. Our engineers already write the majority of code with AI. Some things are great. Some things need to be rebuilt. The next leader will know the difference. What You'll Do: Build the Future of Commerce AI Architect and evolve the platform for the agentic era. The technical foundation needs to support agents that operate autonomously across content, media, and sales. You will decide what gets built, how it gets built, and what gets thrown away. Push the frontier on AI-assisted development. We already lead most companies in AI code contribution. Claude Code, Cursor, and the next generation of agentic dev workflows should be standard across the org. As a startup, we should be ahead of everyone else on this. Ship AI agents into production with speed and reliability. Our agents are already in Fortune 100 workflows and scaling fast. Engineering needs to deliver new capabilities on a weekly cadence. Be the technical face of the company externally. Our AI Brand positioning depends on engineering leaders who can speak credibly about what we are building. Conference talks, blog posts, recruiting events. Build the Team Recruit and retain world-class engineering talent, starting with Mountain View. You will be measured on the quality of people you bring in and the quality of people you develop. Build a strong engineering leadership bench. We need senior leaders who can independently own large surface areas and represent engineering with authority across the company. Create an environment where the best engineers want to stay, grow, and recruit their friends. Every hire should raise the average. Own Engineering Execution Own product quality, infrastructure efficiency, and engineering velocity. You set the metrics, you hit them. Drive continuous improvement in margins and cost structure. We have already made dramatic improvements in infra costs and product reliability. You will own the next chapter. What You'll Bring: This is not a caretaker role. We need a builder. Here is what matters: You have built and scaled engineering teams. You have taken a team from good to great. You know how to hire senior talent, develop middle managers, and create a culture where A-players attract more A-players. Ideally you have done this at a pre-IPO company scaling through a similar inflection point. You are technical and hands-on. You can go deep on architecture discussions, review technical designs, and earn the respect of senior engineers. You do not need to write code every day, but you need to be able to tell when code is good and when it is not. You are AI-native. You personally use AI development tools. You have opinions about LLM orchestration, agent architectures, and how AI changes the software development lifecycle. You are excited about a world where AI writes most of the code and engineers focus on architecture, judgment, and customer impact. You operate with urgency. Startup pace. Weekly shipping cadence. You do not tolerate multi-month planning cycles for things that should take days. You bias for action and course-correct fast. You are a talent magnet. The best engineers you have worked with want to work with you again. You have a network of strong technical leaders you can bring in. You know the difference between hiring for pedigree and hiring for signal. You want to be in the room. This is an onsite role in Mountain View. You will work closely with the Founders, product, and customer success. Our best decisions happen face-to-face. Compensation and Benefits: Base: Competitive with top-tier Silicon Valley companies. Commensurate with experience. Equity: Significant pre-IPO stock options. This is a leadership seat and the equity reflects that. We are at a stage where senior hires still get meaningful ownership. Benefits: Full medical, dental, vision. 401(k). Unlimited PTO. Location: Mountain View, CA. Onsite. 15 minutes from Stanford campus. Why Join Now: The window is now. The company has product-market fit, revenue, and customers. The AI Labs team is being built right now. In 12 months this team will be set. The founding members will define the culture, the architecture, and the trajectory. This is that moment. Real AI, not AI theater. Most companies are bolting AI onto legacy products and calling it innovation. We are rebuilding the entire platform around autonomous agents. Our agents are already in production, already in customer workflows, already making decisions. If you want to lead a team doing real AI, this is it. Fortune 100 scale. Your decisions will directly affect how 2,200+ brands run their ecommerce. The Fortune 100 uses our platform to manage billions of dollars in commerce. This is not a sandbox. Equity upside. Pre-IPO. $200M+ raised from tier-one investors. The economics of joining at this stage, in this role, are compelling. Check out our LinkedIn page to learn more about what it’s like to work at CommerceIQ!We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law.

🏢 Summary: Executive technical leadership role to scale and evolve a global AI-driven brand compliance platform built on cloud-native architecture. The position focuses on defining technical vision, overseeing scalable and resilient systems on GCP, and integrating AI/ML into production-grade products. The mission is to transform the engineering organization into a high-performance team while maintaining startup agility. 🗂️ Requirements: Proven experience as CTO, VP Engineering, or Head of Tech in startup environment, Expert knowledge of Java, Python, and React, Strong experience with cloud-native architectures on GCP, Experience building data-intensive platforms, Experience integrating AI/ML into production systems, Experience designing scalable microservices architectures, Experience with event-driven systems, Ability to define and execute technical strategy, Experience leading and scaling cross-functional engineering teams 📃 Skills: Java, Python, React, GCP, Microservices, GraphQL, AI, ML, NLP, DevOps, QA, Cloud, Architecture, Event-driven 🏢 Description: What’s at stake? We’re changing the rules of the game in global brand compliance. Our product is in an extremely dynamic phase of development, and the largest e-commerce platforms on the market are already taking a direct interest in our innovative approach. What gives us a massive advantage is access to unique datasets—powerful fuel for building advanced AI-based solutions. We’re looking for a leader who will step up and take our product to the very top! Your mission and challenge : We need a technological visionary who will take the helm and transform our product and engineering organization into a high-performance machine. You must know how to scale processes and architecture without losing the agility and startup spirit that drives us. Our Tech Stack We build on a robust and modern foundation: Backend: Java (modern frameworks, microservices architecture). Frontend: React (building intuitive, data-rich management dashboards). AI/ML Module: Python (dedicated models for natural language processing of regulations and automated decision-making). Infrastructure: Google Cloud Platform (GCP). Engineering Philosophy: High focus on "Compliance by Design," high availability, and seamless integration with global regulatory data sources. Key Responsibilities Technical Strategy: Define the long-term technical vision and roadmap, ensuring the platform remains "right by design" and scalable for global markets. Architecture Oversight: Oversee the evolution of the GCP and Event-driven infrastructure, ensuring high resilience and security. Team Leadership: Scale and mentor a cross-functional engineering team (Software, Data, AI, DevOps, QA), fostering a culture of high velocity and low ego. Product-Tech Alignment: Collaborate with stakeholders to translate complex burdens into elegant, automated digital products. Innovation: Drive the integration of AI/ML and GraphQL layers. Requirements Leadership: Proven experience in executive technical leadership (CTO, VP Engineering, or Head of Tech) in a fast-paced startup environment. Deep Technical Roots: Expert knowledge of modern stacks (java, python, react) and cloud-native architectures (GCP). Data & AI Vision: Experience building data-heavy platforms and integrating AI/ML into production workflows. Business Acumen: Ability to align technical decisions with commercial goals and regulatory requirements. Mindset: A pragmatic leader who stays "close to the code," values ownership, and thrives on solving high-impact problems.