Interested in this AI Agent Developer role at Bolder Apps?
Apply Now →About This Role
We're hiring for our partner company, an early-stage startup building an AI coworker: an agent that lives inside a team's everyday tools and actually gets work done. They need a Head of GTM to take it to market. You'll own the story, the first customers, and the first real revenue. This is a founding role and a hands-on one. You'll write the positioning, run the early sales calls, and build the engine that brings in the next hundred customers. Later, you'll hire the team around it. The role is remote-friendly anywhere in the US, and hours that overlap with Pacific time will make the founder very happy. If you've taken a technical product from zero to paying customers and want to do it again from day one, read on.
About the company
The company is building an AI coworker for teams. It joins the tools a team already uses, picks up context, and handles real work across them. It knows when to act, when to ask, and when to stay quiet. You'll join a seasoned founder and a founding team who spent years building technology in the services world. They watched clients ask for agents long before anyone could deliver them, so they know where the real demand is. The team is small on purpose. The engineers are building fast. Now the company needs one person to own how the product meets the market.
Responsibilities
- Own positioning and messaging. Decide who this is for, what problem it solves, and how we say it
- Define the ICP, then prove it or drop it with real conversations and real data
- Run pricing and packaging experiments. Learn fast from what buyers actually pay for
- Build outbound from scratch: lists, sequences, first calls, and a clean handoff from founder-led sales
- Land the first design partners and turn them into paying customers, references, and product feedback
- Close the first real revenue yourself
- Stand up a demand-gen and content engine: launches, writing, demos, and showing up where buyers already are
- Work side by side with the founder and the founding engineers. Bring what customers say back into the product
- Set up a simple GTM stack and the few metrics that tell us what is working
- Hire and lead the GTM team once the motion is proven
Our Culture & Values (read before applying)
We move fast. We take ownership. We work with AI, not against it. And we expect everyone to bring ideas, not wait for instructions.
There are no daily checklists, no micromanagement, and no corporate politics. You get autonomy, trust, and a small team that's always ready to help you grow. Here, impact matters more than titles, and curiosity matters more than seniority.
If you want to level up fast and see your work in real users' hands, welcome aboard.
Requirements
- You've taken a B2B product from zero, or close to it, to its first paying customers. You closed a real share of those deals yourself
- You've sold technical products: AI, developer tools, APIs, or B2B SaaS bought by technical teams
- You're comfortable with technical buyers. You can run the demo, follow the architecture questions, and know when to bring in an engineer
- You've owned positioning, ICP, and pricing work, not just executed someone else's plan
- You're a player-coach. You write the emails, run the calls, and build the process yourself
- You use AI tools in your own daily work, and you can tell real agent value from hype
- You work well from a fuzzy brief, decide with data, and show results in weeks, not quarters
- Excellent written and verbal communication; you can explain the product to a skeptical buyer and the pipeline to a founder without a slide deck
Nice to have
- You were one of the first GTM hires at a startup that went on to raise or scale
- Experience selling AI agents, automation, or workflow tools
- Product-led growth alongside a sales motion
- You've built a content or community engine that created real pipeline
- A network among engineering leaders, ops leaders, or startup founders
- You've hired and managed SDRs or AEs before
Benefits
- A founding seat. You own go-to-market and shape how the company sells
- Founding equity
- A direct line to the founder and the founding engineers, with no layers in between
- Remote anywhere in the US, ideally keeping hours that overlap with Pacific time
- The tools you need to run real GTM experiments
- A small, experienced team that trusts you to run your own work
- The chance to build and lead the GTM team as the company grows
Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 11,520 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Bolder Apps, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills in Demand for This Role
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $215,000 based on 212 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Bolder Apps AI Hiring
Bolder Apps has 2 open AI roles right now. They're hiring across AI Agent Developer. Based in US.
Location Context
AI roles in Austin pay a median of $208,000 across 317 tracked positions. That's 3% below the national median.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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