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About This Role
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Senior Director, Data Science and AI Agents
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Location: San Mateo preferred (Nashville, TN or Sterling, VA optional)
POSITION OVERVIEW
The Senior Director of Data Science leads the technical vision, strategy, and
execution for AI capabilities that power Asurion's next\-generation customer
experience. Leading a team of approximately 20 highly skilled data scientists and machine learning practitioners, this leader provides deep technical direction
across production AI systems including conversational virtual agents, real\-time
agent assist, and intelligent routing. Beyond delivery, the role serves as the
organization's AI thought leader—continuously evaluating emerging technologies, foundation models, agent architectures, and vendors to shape a three\-year technology roadmap and build\-versus\-buy strategy. The role partners with Product and Engineering to deliver production AI systems while establishing best practices for AI evaluation, LLMOps, governance, and responsible AI. Success is measured by customer outcomes, agent productivity, sales enablement, operational efficiency, and the long\-term technical health of the AI platform.
ESSENTIAL JOB SKILLS/DUTIES
- Define the long\-term AI technology vision and three\-year roadmap across
virtual agents, agent assist, and intelligent routing, including build\-versus\-buy
decisions.
- Provide technical leadership and mentorship to a team of \~20 experienced data
scientists and ML/GenAI practitioners, raising engineering and scientific rigor.
- Lead AI architecture decisions spanning LLMs, RAG, agentic AI, evaluation
frameworks, orchestration, and production deployment.
- Drive customer\-facing virtual agents that gather information, resolve issues,
detect sentiment, avoid hallucinations, and seamlessly escalate with full
conversational context.
- Deliver real\-time AI agent assist capabilities including knowledge retrieval,
next\-best action, desktop guidance, call summarization, and sales recommendations.
- Develop predictive routing and decision intelligence that matches customers to the optimal resource using intent, history, agent skills, and business outcomes.
- Establish standards for AI evaluation, hallucination mitigation, observability,
LLMOps, Responsible AI, and continuous experimentation.
- Continuously evaluate emerging AI research, vendors, and platforms to ensure
Asurion adopts scalable technologies and avoids dead\-end architectures.
- Represent Asurion externally through industry events, technical conferences,
and thought leadership while building relationships across the AI ecosystem.
REQUIRED TECHNICAL SKILLS
- Deep expertise in Large Language Models (LLMs), agentic AI, conversational AI, and voice AI.
- Production experience with RAG, prompt engineering, AI evaluation, guardrails,
hallucination mitigation, and LLMOps.
- Strong background in machine learning, predictive modeling, optimization,
recommendation systems, and intelligent routing.
- Experience evaluating foundation models and AI vendors and making build\-
versus\-buy technology recommendations.
- Cloud AI platforms and modern AI frameworks.
- Production AI architecture, experimentation, monitoring, and governance.
REQUIRED SOFT/LEADERSHIP SKILLS
- Recognized technical thought leader with the ability to communicate complex
AI concepts to executives, customers, and industry audiences.
- Technical coaching and mentorship for senior data scientists and ML practitioners.
- Strategic technology planning and architectural decision making.
- Cross\-functional influence with Product and Engineering organizations.
- Executive presence and public speaking at conferences and customer events.
REQUIRED EDUCATION \& EXPERIENCE
- Advanced degree in Computer Science, AI, Machine Learning, Statistics, or
related field, or equivalent experience.
- 12\+ years leading applied AI, machine learning, or data science teams delivering production systems.
- Experience defining enterprise AI strategies and technology roadmaps.
- Experience partnering with software engineering organizations to deploy AI
products at scale.
PREFERRED EDUCATION \& EXPERIENCE
- PhD or Master's in AI, Computer Science, Machine Learning, or related
discipline.
- Experience leading AI organizations within product development environments.
- Recognized contributions to the AI community through publications, conference presentations, open\-source projects, or industry leadership.
PREFERRED LICENSES/CERTIFICATIONS
- AI/ML certifications from major cloud providers or leading AI platforms.
- Demonstrated expertise in production AI, LLMOps, or Responsible AI
frameworks.
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 Asurion, 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. Director-level AI roles across all categories have a median of $272,150.
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.
Asurion AI Hiring
Asurion has 3 open AI roles right now. They're hiring across AI Software Engineer, AI Agent Developer. Positions span Remote, US, San Mateo, CA, US, Nashville, TN, US.
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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