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About This Role
Company Overview
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At Motorola Solutions, we believe that everything starts with our people. We’re a global close\-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.
Department Overview
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Hyper, a Motorola Solutions Company, a leader in conversational, agentic AI designed to reduce the burden on understaffed public safety answering points (PSAPs) by handling non\-emergency calls. It is revolutionizing emergency response systems through cutting\-edge AI technologies. Our first product is reducing 911 wait times by alleviating administrative work from highly trained 911 telecommunicators.
Job Description
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We’re looking for a Sr Software Engineer to set technical direction for the AI Agent Platform team behind Hyper’s emergency response products (Motorola Solutions announced that it acquired Hyper on April 9, 2026\).
You’ll be a senior technical leader responsible for the architecture of our most critical systems. You’ll shape long\-term technical strategy, mentor engineers across the team, and own the toughest cross\-cutting problems — from real\-time AI pipelines and telephony to backend infrastructure and product surfaces. We expect engineers to use AI agents in their own work. But because this is mission\-critical software, humans still own quality, judgment, and what ships — and as a Sr Engineer, you set the bar for what “good” looks like.
What You’ll Do
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- Lead the design and operation of real\-time voice AI systems that support human 911 telecommunicators at scale.
- Identify and solve the hardest problems in our stack: low\-latency audio, streaming, telephony, LLM orchestration, and human\-in\-the\-loop AI workflows.
- Drive engineering excellence across reliability, availability, security, and performance — defining the standards the team operates by.
- Partner with product, design, and operations leadership to translate ambiguous customer and operational problems into technical strategy.
- Mentor engineers; raise the floor and the ceiling of the team’s technical work through reviews, design feedback, and pairing.
- Build and evolve evaluation, testing, and observability frameworks for AI\-assisted systems.
- Lead incident response and post\-incident reviews; own runbook quality and on\-call health for the systems the team is responsible for.
- Represent engineering in conversations with public safety customers, partners, and Motorola Solutions stakeholders when deep technical credibility is required.
You Might Be a Fit If
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- You have production software engineering experience, with a clear track record of technical leadership.
- You’ve designed, shipped, and operated large, complex systems in high\-stakes domains
- You are comfortable working across backend, infrastructure, AI pipelines, and product surfaces.
- You can turn ambiguous product or operational problems into clear technical plans for the team.
- You use AI tools daily, but you set the standard for how your team uses them responsibly — speed without compromising quality.
- You raise the engineering bar around tests, observability, code review, security, and clean abstractions.
- You mentor effectively. Engineers around you get better because of how you work.
- You have strong product judgment and care deeply about the humans using what you build.
- You thrive in a small, fast\-moving team with high ownership and low ego, and you can scale that culture as we grow.
- You want to work on AI systems that matter beyond demos.
Relevant Experience
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We do not expect every candidate to have all of these. We care more about strong engineering judgment, learning velocity, and ownership than exact keyword matches.
Relevant experience may include:
- Architecting LLM, agentic, or RAG systems in production, including evals and prompt test harnesses at scale.
- Deep expertise in Speech\-to\-Text, Text\-to\-Speech, Voice Activity Detection, endpointing, interruption handling, noise filtering, diarization, or audio streaming.
- Telephony and voice infrastructure: PSTN, SIP trunking, PBX, and call routing.
- Real\-time communication systems using WebRTC, WebSockets, RTP/SRTP, media streaming, or low\-latency audio transport — including operating these systems under production load.
- Real\-time, concurrent, or distributed systems using Elixir, Go, Python, Rust or similar languages.
- PostgreSQL and strong data modeling fundamentals at scale.
- Cloud infrastructure on AWS, Azure, or GCP.
- Containerized application environments operated in production.
- Technical leadership in public safety, govtech, healthcare, defense, infrastructure, fintech, or other high\-trust domains.
Target Base Salary Range: $140,000 \- $160,000 USD
Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job\-related knowledge, skills, and experience. The actual offer will be based on the individual candidate.
\#LI\-RS1
Basic Requirements
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8\+ years of experience in Realtime communication systems with deep expertise in Speech\-to\-Text, Text\-to\-Speech, Voice Activity Detection and a rchitecting LLM, agentic, or RAG systems in production, including evals and prompt test harnesses at scale.
Travel Requirements
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Under 10%
Relocation Provided
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None
Position Type
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Experienced
Referral Payment Plan
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Yes
Our U.S. Benefits include:
- Incentive Bonus Plans
- Medical, Dental, Vision benefits
- 401K with Company Match
- 10 Paid Holidays
- Generous Paid Time Off Packages
- Employee Stock Purchase Plan
- Paid Parental \& Family Leave
- and more!
*EEO Statement*
Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally\-protected characteristic.
We are proud of our people\-first and community\-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.
We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.
Salary Context
This $140K-$160K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $188K across 26 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 3,708 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Motorola Solutions, 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 $238,500 based on 58 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($150K) sits 37% below the category median. Disclosed range: $140K to $160K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Motorola Solutions AI Hiring
Motorola Solutions has 2 open AI roles right now. They're hiring across AI Agent Developer, AI Product Manager. Positions span NC, US, Schaumburg, IL, US. Compensation range: $140K - $160K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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