Bolder Apps

Role Description We're placing a Senior Backend & Infrastructure Engineer with a confidential AI-powered FinTech client approaching enterprise rollout. This is a pure infrastructure and security role — you own the architecture that keeps sensitive financial data secure, the systems that stay up when enterprise clients depend on them, and the integrations that connect LLM pipelines to ERP data without leaking either. The platform is past the prototype stage. They need someone who's built production-grade backend systems at scale, not someone who will learn on the job. Responsibilities - Define and own the high-level infrastructure strategy on AWS — uptime, scalability, and performance are your metrics. - Architect secure, resilient backend workflows capable of supporting enterprise-level client deployments on a platform handling sensitive financial data. - Implement and enforce security frameworks across all system layers — encryption, network isolation, access controls, compliance boundaries. - Design and lock down secure data flows between MCP servers and third-party ERP integrations. - Own the Postgres infrastructure — schema design, query optimization, scaling strategy, and backup integrity. - Integrate directly into the client engineering team with full support from Bolder's design, DevOps, and QA network. Qualifications - Senior backend track record. You've architected distributed, enterprise-grade backend systems in production — not prototypes, not internal tools. You can point to something that ran at scale, stayed up, and handled real data without incident. - Deep AWS expertise. You provision, scale, and secure infrastructure in AWS hands-on. VPCs, IAM, ECS or EKS, RDS, Secrets Manager, CloudWatch — you've used them in anger, not just in tutorials. You know what the AWS Well-Architected Framework says and where to deviate from it. - PostgreSQL at scale. Expert-level fluency with Postgres — schema design, indexing strategy, query optimization, migrations, connection pooling, replication. You don't write queries you haven't profiled. - Security specialist. Secure communication protocols, data encryption at rest and in transit, network isolation, multi-server environment management. In a FinTech context, you treat security as architecture, not an afterthought bolted on before launch. - MCP and integration security. You understand how Model Context Protocol servers communicate and where the attack surface lives. You've thought about securing LLM-to-system boundaries, not just API-to-API ones. - AI and data integration fluency. Exposure to LLM orchestration pipelines, automated code generation systems, or ERP data sync tooling. You don't need to have built a custom LLM harness, but you need to understand what's happening inside one well enough to secure it. - Proactive communicator. You flag infrastructure risks before they become incidents. You document decisions. You don't go quiet between check-ins and resurface with surprises. Requirements - Fully remote. - Target start date of early August 2026 — defined scope, no ambiguity on timing. - Direct access to engineering leadership with no PM layers between you and the decisions. - Tooling budget for infrastructure, security tooling, and monitoring. - A peer network of senior engineers and agentic builders across Bolder's client portfolio.

Role Description We're hiring a C# developer who can architect and ship production-grade backend systems from day one. This starts as a contract engagement with the explicit intent to convert to full-time. You'll design scalable APIs, manage Azure infrastructure, and integrate AI capabilities directly into the product — not as a side feature, as core architecture. If you've built serious .NET systems on Azure and you've worked with LLMs beyond the tutorial level, we want to talk. Responsibilities - Design, build, and maintain high-performance Web APIs using C# and .NET Core — clean architecture, no shortcuts, built to last. - Architect and manage cloud infrastructure on Azure: App Services, Functions, SQL Database, Service Bus, Key Vault, and Entra ID. - Integrate LLMs and AI features directly into the application ecosystem — Azure OpenAI, semantic search, vector databases, embeddings. - Participate in foundational system design decisions with an eye on long-term maintainability, not just the current sprint. - Document codebase logic and API endpoints clearly enough that the next engineer doesn't need to ask you how anything works. - Communicate architectural and AI trade-offs to non-technical stakeholders in plain language, in writing, without being asked twice. Qualifications - C# and .NET mastery. Advanced proficiency in C# on .NET 6/8+. You write async code naturally, use LINQ without abusing it, and your Entity Framework Core usage won't embarrass you in a code review. You understand OOP and SOLID well enough to apply them, not just cite them. - Azure ecosystem. You've deployed and managed real applications on Azure — not just followed a tutorial. App Services, Functions, Key Vault, Azure Active Directory/Entra ID. You know what breaks at scale and how to design around it before it does. - API architecture. Deep understanding of RESTful design, microservices, API gateways, rate limiting, and performance tuning. OAuth2 and JWT aren't concepts you look up — they're things you've implemented, debugged, and secured in production. - AI integration. Practical experience with LLMs in production: OpenAI API, Azure OpenAI, prompt engineering, semantic search, embeddings, or vector databases like Pinecone or Azure AI Search. You've built intelligent features into a real product, not a demo. - Product ownership mindset. You build for the long haul. You think about what happens six months after you ship, not just whether the PR passes CI. This is a contract-to-hire role — we're evaluating fit for a permanent position from day one. - Documentation discipline. You document as you build. API endpoints, architectural decisions, data flows — clear enough that the codebase can be handed off without a knowledge transfer call. - Proactive communicator. You flag blockers early, explain trade-offs clearly, and don't disappear between check-ins. Async, in writing, with enough context that nobody needs to follow up. Requirements - Contract engagement with a defined path to full-time conversion — not "maybe someday," a real track. - Fully remote, US timezone. - Direct access to decision-makers — no PM layers between you and the people who own the product. - Real architectural ownership from day one — you're not implementing tickets, you're making design decisions. - Tooling budget for APIs, infrastructure, and whatever you need to do the job well. - A peer network of senior engineers and agentic builders working on overlapping projects.

Role Description We're hiring a Performance Marketing Lead to own paid acquisition end-to-end. You'll run the channels, write the copy, build the landing pages, and defend your numbers in weekly pipeline reviews with the founders. No team underneath you — you'll build AI agents to handle the ops that don't need a human. We don't need someone to set up from scratch. We need someone to own, optimize, and scale what's already working. OTE is $110–135K, and you'll know your bonus math on day one. Responsibilities - Own all paid acquisition channels — directory listings, pay-per-lead programs, paid search, paid social — and their ROI - Track CAC, LTV, and payback period for every paid source; report against pipeline and revenue targets weekly in front of the founders - Build and run landing page tests to improve conversion on paid traffic - Manage the experimentation budget — propose the test, ship it, kill it or scale it based on data - Build AI agents to automate bid management, creative iteration, and reporting so the repetitive ops don't live on your plate - Take over an active HubSpot instance with lead source attribution and contact-level qualification tracking; improve it - Operate across a modern measurement stack (HubSpot, GA4, GSC, custom MCP integrations) with a defined ICP and a backlog of experiments ready to ship Qualifications - Paid acquisition track record. 3+ years running paid for B2B services, agencies, or high-ticket SaaS. Bring the dashboards, the before/after screenshots, and the actual numbers — spend, leads, revenue, time period. Assertions without evidence don't move the conversation forward. - Budget discipline. You've managed five- and six-figure annual ad budgets and spent like it was your own money. You know the difference between a test worth running and a budget burn. - Attribution skepticism. You distrust attribution data before you trust it. You understand the gaps in last-click, the limits of GA4, and why a "good" ROAS number sometimes lies. You don't optimize for what's easy to measure. - HubSpot and reporting fluency. You can build the pipeline report yourself. HubSpot, GA4, ad platform dashboards — you pull the data, spot the problem, and come to the weekly review with a point of view, not a status update. - AI-native operator. You've built workflows around Claude, automation platforms, or similar tools — not as experiments, as daily infrastructure. Bid management, creative testing, reporting pipelines. You know which parts of the job the agent can own. - Hands-on. You write the ad copy. You build the landing page. You do not wait for a designer or a copywriter to unblock you. - Proactive communicator. Async, in writing, with numbers. When a channel is underperforming, you say so before the pipeline review — not during it. Requirements - Base $70–90K depending on experience, plus a quarterly performance bonus tied to qualified pipeline and blended CAC targets. - OTE $110–135K. Bonus math is defined on day one — no mystery comp. - $10–25K/month in paid media spend under your direct control, with budget that grows with proven ROI. - Direct founder access — leadership is in the pipeline review every week, not in a boardroom. - Fully remote, EST/CST hours, async-friendly. - Clean data and a working measurement stack from day one — no 0-to-1 setup tax. - Tooling budget for AI platforms and automation infrastructure.

Role Description We're hiring a Senior Marketing Manager to run the day-to-day of a marketing function that's already built and operating. The CMO owns strategy, revenue ops, and what's next. You own execution — content, SEO, HubSpot, directories, reporting, and the AI agents we've built to support all of it. This is a shipping role, not a strategy role. If you want to see the impact of your work every morning and make real decisions inside a defined scope, we want to hear from you. Base is $70–90K with OTE up to $130K+. Responsibilities - Ship daily content across blog, social, case studies, and sales enablement — this is the core of the role. - Run SEO execution: on-page updates, technical fixes, link-building outreach, and content briefs based on an existing keyword strategy. - Manage directory channel ops: keep profiles current, leads flowing, and reviews compounding. - Own HubSpot day-to-day — workflow maintenance, lead routing, sequence management, list hygiene. - Run the weekly pipeline contribution report, monthly channel review, and quarterly trends summary. - Operate the AI agents already in production and flag when they need to be rebuilt, retrained, or replaced. - Take over a clean HubSpot instance with solid attribution and qualification tracking, a defined channel taxonomy, and a backlog of content briefs and channel experiments ready to ship. Qualifications - B2B marketing execution experience. 3+ years in B2B marketing, agency or dev services strongly preferred. You've owned a channel or function completely, not just contributed to one. You can point to something you inherited, improved, and measured. - HubSpot fluency. You build workflows without watching a tutorial. Lead routing, sequences, list segmentation, attribution reporting — you know where to click and why. You don't need a RevOps consultant to make it do what you need. - Strong writer. You can ship a case study, a LinkedIn post, and an email sequence in the same afternoon without sacrificing quality on any of them. Writing is how you think, not a task you schedule. - SEO competence. You've written for search, understand on-page fundamentals, and can read GSC without panicking. You're not doing keyword research from scratch — you're executing against a strategy that exists. - AI-native operator. You use Claude, GPT, and automation platforms to multiply your output, not as occasional helpers. You've built at least one workflow or agent that runs without you touching it daily. - Async-first communicator. You write things down. You document decisions. You don't ask for a meeting when a message will do. The CMO and founders see your updates in writing, not in standups. - Executor by identity. You're proud of owning a specific scope completely. You act without permission inside your lane, ask questions clearly when you're outside it, and ship every week regardless. Requirements - Base $70–90K depending on experience, plus a quarterly bonus tied to pipeline contribution and channel-specific KPIs. - OTE $105–130K+. Bonus math is transparent on day one. - Direct daily collaboration with the CMO and weekly visibility with the founders. - A clean, working marketing stack from day one — HubSpot, GA4, GSC, custom MCP integrations — with full onboarding from the CMO. - Fully remote, EST/CST hours, async-friendly. - Real ownership of a defined scope with the autonomy to make decisions inside it. - Tooling budget for AI platforms and automation.

• Own all paid acquisition channels — directory listings, pay-per-lead programs, paid search, paid social — and their ROI • Track CAC, LTV, and payback period for every paid source; report against pipeline and revenue targets weekly in front of the founders • Build and run landing page tests to improve conversion on paid traffic • Manage the experimentation budget — propose the test, ship it, kill it or scale it based on data • Build AI agents to automate bid management, creative iteration, and reporting so the repetitive ops don't live on your plate • Take over an active HubSpot instance with lead source attribution and contact-level qualification tracking; improve it • Operate across a modern measurement stack (HubSpot, GA4, GSC, custom MCP integrations) with a defined ICP and a backlog of experiments ready to ship

Role Description We're hiring a VP of Marketing to own client acquisition for Bolder Apps. You'll build the entire system (SEO, GEO, paid, outbound, brand, content ops) and run it yourself. No team of humans underneath you. You'll architect and operate AI agents to scale your output. We need someone who's actually moved B2B pipeline numbers and knows how to make AI do the heavy lifting, not a strategist who needs a team to execute. Base is $100K–$150K plus performance bonus tied to pipeline, with a $10–20K/month marketing budget you control. Responsibilities - Own SEO and GEO. Organic is already working. Your job is to scale it and make sure we show up in ChatGPT, Perplexity, and whatever comes next. - Fix paid acquisition. It hasn't worked yet. Diagnose why, rebuild the approach, and prove it can. - Build and operate AI agents for content production, outreach, reporting, and campaign ops. Not as a side project, as core infrastructure. - Run outbound that books meetings with US-based founders and VPs of Engineering, not generic blast lists. - Track CAC, LTV, and pipeline contribution weekly. Kill what isn't working. - Shape brand perception so Bolder is known as the AI-native agency, not another dev shop. - Own the budget. Every dollar tied to CAC and pipeline impact. - Report numbers weekly with the rigor you'd expect from a CFO. - Demonstrable B2B pipeline numbers you personally moved somewhere defensible. Fluency in CAC, payback, LTV, and channel-level conversion without checking a dashboard. - AI agent workflows in production for real marketing work (content, outbound, research, reporting), not Zapier toys. A clear point of view on where AI helps and where it produces slop. - Track record growing organic traffic on a B2B site, plus opinions and active experiments on GEO. This is new ground and we expect curiosity, not playbooks. - Hands-on experience fixing paid acquisition that wasn't working. Ability to diagnose whether the problem is targeting, creative, landing page, offer, or product-market fit. Google, LinkedIn, and Meta at minimum. - Cold outbound that booked meetings with senior US buyers, plus experience selling dev work, design work, or consulting to US tech buyers. - Writing taste. No "synergize," no "transformative AI solutions" on our homepage. - GA4, attribution modeling, and SQL when the dashboard lies. - Founder-adjacent operating style. Problems flagged early, bad numbers surfaced not buried, no decks required for strategy conversations. Qualifications - $100K–$150K base salary - $10–20K/month marketing budget under your direct control - Fully remote, async-friendly - Real autonomy — no brand committee, no approval chains for experiments - Direct access to the founder and decision-makers - Tooling budget for AI platforms, automation, and whatever you need to run efficiently - A company that's actually building with AI — not just talking about it

• Own inbound leads end-to-end: first call, discovery, scoping, proposal, negotiation, close • Run discovery with founders and CTOs - get past what they asked for and understand what they're actually trying to build • Partner with our scoping and delivery team to translate buyer goals into proposals that are honest, profitable, and shippable • Quarterback the deal across our team - pulling in scoping, design, finance, and exec at the right moments without dropping balls • Handle the inevitable curveballs: late-stage objections, competitive poaching, scope creep, founder cold feet. Don't panic. Reset the conversation. • Keep CRM clean and pipeline reviews honest. If a deal is slipping, you say so before anyone asks. • Feed signal back to marketing and delivery: which ICPs convert, where we're losing, what objections keep coming up

Role Description We're hiring closers to bring in more business for our core offering: AI-native product development and AI implementation for U.S. companies. This is a 1099 role with no base, no W-2 - a recoverable bridge against commissions and a structure that pays real money to people who can actually close. Our AEs average $150K–$250K per year, with top performers going higher. We don't care where you went to school or whether you've sold AI before. Our best person on this team came from outside the industry and was running scoped deals within months. We want more of him. Responsibilities - Own inbound leads end-to-end: first call, discovery, scoping, proposal, negotiation, close. - Run discovery with founders and CTOs to understand their actual goals. - Partner with our scoping and delivery team to create honest, profitable, and shippable proposals. - Quarterback the deal across our team, coordinating scoping, design, finance, and exec without dropping balls. - Handle late-stage objections, competitive poaching, scope creep, and founder cold feet calmly. - Maintain a clean CRM and provide honest pipeline reviews. - Feed signal back to marketing and delivery regarding which ICPs convert and common objections. - Demonstrate a track record of selling consultative services and closing real deals. - Exhibit sharp written communication, particularly in email and Slack follow-ups. - Maintain composure under pressure and keep deals moving despite challenges. - Read people effectively to adjust your approach based on buyer priorities. - Coordinate well across a team, briefing engineers, designers, and ops efficiently. - Exhibit process discipline and manage your own calendar effectively. - Be comfortable with a 1099 + commission-only structure. - Quickly absorb knowledge about AI agents, LLMs, product engineering, and pricing models. - Be U.S.-based and work during U.S. hours, plugged into the U.S. startup and tech ecosystem. Requirements - Comfortable with 1099 + commission-only structure. - Ability to pick things up fast and talk credibly about AI and related topics within 60 days. - Fully remote work capability. - Steady deal flow for closers who deliver. Benefits - $150K–$250K/year average earnings with uncapped commission. - Recoverable bridge against commissions for financial stability while deals close. - 1099 structure providing real upside and autonomy. - Inbound pipeline that is full and growing. - A category where buyers are actively trying to spend. - Direct line to founders and delivery without intermediaries. Company Description Bolder Apps is a product development studio that partners with U.S.-based startups and established companies to build and scale innovative digital products. We specialize in AI-powered development, full-cycle product creation, and engineering team augmentation. Our mission: build bolder, faster, and smarter. Our culture emphasizes: - Moving fast and taking ownership. - Working with AI, not against it. - Encouraging ideas and autonomy without micromanagement. - Valuing impact over titles and curiosity over seniority.

• Take projects from spec to deployed software, with Claude Code (and other coding agents where they fit) doing most of the typing • Author CLAUDE.md files, skills, and prompt systems that produce consistent output • Manage context, sub-agents, memory, and tokens across long-running tasks • Drive TDD with agents using hooks, sub-agents, and verification patterns, and don't let the agent cheat • Set up CI/CD, deployments, databases, secrets, and monitoring properly • Be the final quality gate. Review what the agent produced, refactor what's wrong, ship what works

Role Description We're hiring engineers to build production software with Claude Code on a per-project basis. You won't write much code by hand. You'll orchestrate the agents, design the skills, manage context and memory, and ship working apps. We need people who've actually mastered this and understand what's happening under the hood, not vibe-coders. If you've shipped real things with Claude Code and you can handle Git, deployments, databases, security, and the rest, we want to talk. You'll get a fixed pay per each project. Our average builders make more than $10k per month. Responsibilities - Take projects from spec to deployed software, with Claude Code (and other coding agents where they fit) doing most of the typing. - Author CLAUDE.md files, skills, and prompt systems that produce consistent output. - Manage context, sub-agents, memory, and tokens across long-running tasks. - Drive TDD with agents using hooks, sub-agents, and verification patterns, and don't let the agent cheat. - Set up CI/CD, deployments, databases, secrets, and monitoring properly. - Be the final quality gate. Review what the agent produced, refactor what's wrong, ship what works. Qualifications - Real, demonstrable Claude Code experience. You've shipped apps with it — not POCs, not toys. - Multi-agent fluency. You've worked across at least one other coding agent (Cursor, Codex, Copilot, Amp, Cline, or similar) and can articulate the trade-offs. - Skill authoring. You've written reusable skills (SKILL.md, system prompts, agent definitions) that produce consistent output, not one-off prompts that need re-tuning every session. - Context engineering. You manage the context window deliberately. You know when to summarize, when to spawn a sub-agent, when to clear and restart. - Memory management. External memory, RAG, file-system memory, structured handoffs across sessions and days. - Token economy. You optimize for cost. You know which model to use for which task. You're not burning Opus tokens on jobs Haiku would handle. - Git. Branches, rebases, worktrees, conflict resolution, clean commits. You don't panic when something goes sideways with origin/main. - Deployments. You can ship a Next.js app to Vercel, a backend to Fly or Railway, a container to AWS — and you can debug it when it breaks at 11pm. - Databases. Postgres-class fluency. You've worked with Supabase or equivalent (Neon, RDS, PlanetScale). You understand schemas, indexes, migrations, foreign keys, transactions, and Row Level Security. You don't write SELECT * in production code. - Security. Secrets management, env vars, auth flows (OAuth, JWTs, sessions), input validation, CORS, prompt injection in agent contexts, scoped tool permissions, the OWASP Top 10. You don't ship credentials to GitHub. - Networking and infra basics. DNS, HTTPS, environment isolation (dev/staging/prod), basic observability (logs, error tracking, uptime monitoring). - Reading code. When the agent produces something subtle, you catch it. You can debug across files, languages, and stacks. - TDD with agents. You can make a coding agent actually do test-first development. You know it doesn't do this naturally — and you have your guardrails. - Unit and integration testing. pytest, Jest, Vitest, Playwright, or whatever your stack demands. Meaningful coverage, not theater. - Eval frameworks for agent quality, not just deterministic tests. - Code review reflex. You don't merge what you haven't read. - Honest communication. When something is harder than expected, you flag it early. You don't disappear and resurface with surprises. Benefits - $10,000+ per month (paid per project). Uncapped upside for top operators who can ship multiple projects. - Per-project structure. Defined scope, defined deliverables, no fake urgency. - Fully remote, async-friendly. Work where and when you do your best work. - Real autonomy. You pick the agent architecture, the skills, the workflow. We don't micromanage process. - Steady pipeline. For engineers who consistently deliver, repeat work is the default. - Direct line to decision-makers. No PM layers between you and the people who own the outcome. - Tooling budget for model APIs, plugins, and infrastructure required to do the job well. - A peer network of other top-tier agentic operators we work with on overlapping projects. How to Apply - A real project you shipped where AI agents wrote most of the code under your direction. Live URL preferred. Repo if it's open. Tell us what the agent got right, what it got wrong, and what you did about it. - A skill, CLAUDE.md, MCP server, or hook setup you're proud of. Show us your taste and your standards. - Your TDD-with-agents approach. Briefly: how do you make a coding agent actually do test-first development without cheating? - Something that proves you operate under the hood. A war story about a deployment that went sideways. A Supabase schema you're proud of. A security issue you caught. A migration you executed without drama. Something that shows you're not just driving the agent — you understand the road.