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About This Role
Manhattan, NY · On\-site · Full\-timeCompensation: $200,000–$300,000 \+ 0\.25%–1% equity
About the Company
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Our client is a seed\-stage startup using generative AI to automate consumer debt collection, a $35B market in the US alone. Its AI agents handle the full late\-stage recovery process — asset research, pre\-legal outreach, litigation, credit reporting, and enforcement actions like garnishments and liens — already outperforming human collectors 2x at a fraction of the cost and running 10M\+ calls per month.
Founded 2024 · \~5 people (Seed) · Industry: AI Tools
The Role
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The client needs an AI Agent Engineer to build and own its voice\-AI agent infrastructure end to end on LiveKit — the orchestration layer, the prompting strategy across millions of consumer interactions, and continuous performance improvement through rigorous testing and iteration. It suits a deep voice\-AI engineer or a strong, analytical, business\-minded infrastructure engineer equally well.
Tech stack: LiveKit, Node.js, AWS, SQL; ASR/STT/TTS, real\-time audio pipelines, SIP/telephony.
Requirements
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- 2\+ years in voice AI, conversational AI, prompt engineering, speech systems, or related agentic workflows
- 3\+ years in platform, infrastructure, or backend engineering
- Strong experience with Node.js, AWS, and SQL
- Shipped production systems in a startup or similarly fast\-paced environment
- Experience with voice\-orchestration platforms or agent frameworks such as LiveKit or equivalent
- Strong prompt\-writing instincts and the ability to design resilient conversational flows for real\-world edge cases
- Strong analytical skills and comfort tying technical work directly to business outcomes and ROI
Nice to Haves
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- Voice\-AI experience in production, even from a lesser\-known company or background
- Built AI infrastructure or agentic systems at a startup or AI company, with a real sense of what production\-grade means at scale
- LiveKit or other voice\-orchestration\-framework experience
- Business\-minded: connects technical decisions to liquidation, containment, and conversion metrics, not just engineering metrics
- Strong prompt\-engineering instincts, having designed conversational flows that handle edge cases gracefully under compliance constraints
- Telephony\-infrastructure experience such as SIP trunking
Why Join
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- Own it end to end: build the voice\-AI infrastructure in\-house from scratch on LiveKit — orchestration, prompting strategy, evaluation
- Real scale, real outcomes: millions of consumer interactions a month, tied directly to liquidation, containment, and conversion metrics
- Fast traction: \~$2M annualized run rate in a few months with a team of five, targeting $10M ARR this year
Details
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- Location — Manhattan, NY
- Work policy — On\-site
- Compensation — $200,000–$300,000 \+ 0\.25%–1% equity
- Visa sponsorship — Not available
- Employment type — Full\-time
Salary Context
This $200K-$300K range is above the median for AI Agent Developer roles in our dataset (median: $200K across 33 roles with salary data).
View full AI Agent Developer salary data →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 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At David Joseph & Company, 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 Required
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 $240,000 based on 96 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $200K to $300K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
David Joseph & Company AI Hiring
David Joseph & Company has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer. Positions span San Francisco, CA, US, New York, NY, US. Compensation range: $180K - $300K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 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.
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