Interested in this AI Agent Developer role at HireNow Staffing?
Apply Now →Skills & Technologies
About This Role
##### Real\-Time Voice AI Agent Systems Engineer
##### Company: HireNow Staffing (Direct Placement Partner)
##### HireNow Snapshot
##### HireNow Staffing is actively recruiting a highly skilled Real\-Time Voice AI Agent Systems Engineer to join one of our valued client partners. This is a high\-ownership engineering opportunity for someone capable of building production\-grade voice AI infrastructure and conversational agent systems from the ground up.
##### The selected engineer will own the technical foundation behind millions of real\-world AI voice interactions—from LiveKit architecture and orchestration to prompting, speech performance, testing, reliability, and continuous optimization.
##### This position requires more than traditional backend development. The successful candidate must understand how infrastructure, conversational logic, speech systems, latency, and business outcomes intersect. The engineer will have significant ownership over how AI agents communicate, respond, recover from edge cases, and perform at scale.
##### Key Responsibilities
- Build and own production voice AI infrastructure using LiveKit.
- Architect real\-time voice\-agent systems covering orchestration, state management, reliability, latency, and conversational execution.
- Develop the prompting architecture governing conversation flows, tone, guardrails, compliant phrasing, exception handling, and agent behavior.
- Create scalable testing and evaluation frameworks incorporating A/B testing, regression testing, conversation QA, benchmarking, and KPI measurement.
- Analyze production interaction data and translate findings into measurable improvements in agent performance.
- Optimize ASR, STT, TTS, turn\-taking, interruption handling, state transitions, and real\-time conversational responsiveness.
- Build infrastructure capable of reliably supporting millions of voice interactions.
- Develop migration tooling and processes for transitioning customers from legacy voice infrastructure while preserving required customizations.
- Identify and resolve performance bottlenecks, reliability issues, conversational failures, and production edge cases.
- Partner closely with Product, Operations, and leadership to translate commercial objectives into technical systems and effective agent behavior.
- Continuously expand conversational coverage as new customer scenarios and operational requirements emerge.
##### Required Qualifications
- 3\+ years of platform, infrastructure, backend, or comparable production engineering experience.
- 2\+ years of experience involving voice AI, conversational AI, speech systems, prompt engineering, or related agentic workflows.
- Strong hands\-on development experience with Node.js.
- Strong experience with AWS and SQL.
- Experience designing and shipping production systems within a startup or similarly fast\-moving engineering environment.
- Hands\-on experience with LiveKit or a comparable voice orchestration/agent framework.
- Strong understanding of real\-time system architecture, state management, reliability, and performance optimization.
- Demonstrated ability to design clear, resilient, and effective conversational prompts and agent flows.
- Strong analytical ability with experience connecting engineering decisions to measurable operational or business outcomes.
- Excellent written and verbal English communication skills.
- High degree of technical ownership and ability to execute with limited oversight.
- Must reside in or be willing to relocate to the New York City area.
- Must be able to work onsite in Manhattan 4–5 days per week.
- Must be permanently authorized to work in the United States.
- No visa sponsorship is available.
##### Preferred Qualifications
- Production experience with SIP trunking and telephony infrastructure.
- Experience developing real\-time audio pipelines.
- Knowledge of call routing, telephony carriers, and communication integrations.
- Experience operating speech infrastructure at significant production scale.
- Advanced knowledge of ASR/STT, TTS, interruption management, latency optimization, and conversational turn\-taking.
- Experience building evaluation frameworks for production AI agents.
- Background in debt collection, financial services, fintech, or regulated consumer communications.
- Experience working in an early\-stage or Seed\-stage startup environment.
- Experience connecting agent\-performance metrics to conversion, containment, satisfaction, or other commercial KPIs.
##### HireNow Package
##### Compensation:$200,000–$300,000 annually \+ equity
##### Employment Type: Full\-Time \| Direct Placement
##### Experience Level: 3–10 years, with required relevant engineering experience.
##### Work Location: Manhattan, New York \| In\-Person 4–5 Days Per Week
##### Equity: Equity participation included.
##### Applicant Requirements: Candidates must be based in or willing to relocate to the New York City area and able to meet the in\-person requirement.
##### Work Authorization: Permanent U.S. work authorization required. No visa sponsorship available.
##### HireNow Checklist
##### HireNow Staffing is recruiting a Real\-Time Voice AI Agent Systems Engineer who:
- Combines strong backend/infrastructure engineering with meaningful voice AI, conversational AI, speech, or agentic\-system experience.
- Has hands\-on expertise with Node.js, AWS, SQL, and LiveKit or comparable technology.
- Can architect real\-time production systems rather than focusing exclusively on application\-level development.
- Understands prompting as an engineering discipline involving conversational logic, guardrails, testing, edge cases, and measurable performance.
- Can optimize speech\-agent behavior across latency, turn\-taking, interruptions, state transitions, and reliability.
- Has successfully shipped production technology in a fast\-moving environment.
- Uses data and testing to connect technical improvements directly to business results.
- Can work onsite in Manhattan 4–5 days per week without requiring employment sponsorship.
##### HireNow Standout Candidates
##### Candidates will receive the strongest consideration if they demonstrate:
- Direct experience building production voice AI infrastructure from the ground up.
- Deep hands\-on LiveKit experience.
- Proven experience supporting voice or conversational systems operating at significant interaction volume.
- Expertise spanning real\-time infrastructure, speech technology, prompting, evaluation, and performance optimization rather than only one discipline.
- Experience with SIP, telephony carriers, real\-time audio pipelines, and production call infrastructure.
- Strong experimentation skills using A/B tests, regression testing, benchmarking, and conversation\-quality analysis.
- Demonstrated improvements to measurable AI\-agent KPIs or business outcomes.
- Experience operating successfully within small, highly technical startup teams.
- Knowledge of regulated financial\-services or consumer\-communications environments.
- Stable employment history demonstrating increasing engineering ownership.
##### HireNow Disqualifiers
##### The following will prevent candidates from moving forward:
- Jumpy resumes will not be accepted or interviewed.
- Less than three years of relevant platform, infrastructure, backend, or comparable engineering experience.
- No meaningful voice AI, conversational AI, speech\-system, prompt\-engineering, or related agentic\-workflow experience.
- No experience shipping production\-grade systems.
- Insufficient hands\-on experience with Node.js, AWS, or SQL.
- No exposure to LiveKit or comparable voice\-agent/orchestration frameworks.
- Candidates whose experience is limited to prompt writing without sufficient production engineering expertise.
- Candidates unable to work onsite in Manhattan 4–5 days per week or relocate accordingly.
- Applicants requiring current or future visa sponsorship.
- Candidates who do not meet the core qualifications.
##### HireNow Staffing Disclaimer
##### HireNow Staffing is acting as a direct placement partner for this Real\-Time Voice AI Agent Systems Engineer opportunity. All candidate information is handled confidentially and evaluated against defined requirements. This job description outlines the general scope of responsibilities and qualifications. Duties may evolve based on client needs and business growth. Only candidates meeting the core qualifications will be considered for interview. Client\-specific information will be shared only with qualified candidates during the interview process.
##### https://www.careers\-page.com/hirenow\-staffing\-inc/job/Y6867RY5
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 HireNow Staffing, 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.
HireNow Staffing AI Hiring
HireNow Staffing has 3 open AI roles right now. They're hiring across AI Agent Developer, AI/ML Engineer. Based in 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.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.