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About This Role
About Us
Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI Agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.
Each AI Agent is purpose\-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher\-value work.
Built on a CX\-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.
Why Join Us
As an Engagement Manager for AI Agent deployments, you’ll own how we implement VoiceAI and ChatAI for our enterprise customers \- from strategy through execution. Your job is to make every deployment smooth, high\-impact, and set up for long\-term success.
This role blends program leadership, customer strategy, and value realization. You’ll guide complex rollouts, coordinate across multiple teams, manage risks, and ensure every launch delivers clear, measurable outcomes.
What You’ll Be Doing
- Lead End\-to\-End AI Agent Delivery:
Own AI Agent deployments from kickoff design build testing go\-live hypercare* + optimization.
+ Conduct business and technical discovery to deeply understand customer workflows, KPIs, and success criteria.
- Orchestrate a Cross\-Functional Delivery Pod:
- + Lead a matrixed delivery team including Experience Designers, AI Agent Engineers, and Telephony Engineers.
+ Coordinate with Engineering on feature gaps, technical escalations, and roadmap alignment.
- Drive Customer Outcomes \& Long\-Term Success:
- + Own the success of multi\-phase AI transformation programs.
+ Post–go live, act as the customer’s primary AI Agent program lead \- running QBRs, tracking KPIs, and driving continuous value.
- Establish Scalable Processes \& Governance:
- + Create and refine playbooks, delivery templates, evaluation frameworks, UAT processes, hypercare models, and best practices
+ Ensure compliance with testing, evaluation frameworks, UAT processes, and deployment checklists.
+ Manage timelines, deliverables, documentation, and cross\-functional dependencies for multiple concurrent customer programs.
- Customer Enablement \& Training:
- + Guide customers through operational readiness, change management, and best practices for scaling AI within their contact centers.
- Be the Face of AI Strategy for Enterprise Customers:
- + Present confidently to frontline leaders, IT executives, and C\-suite stakeholders.
+ Translate complex AI/technical concepts into business outcomes and guide customers through AI maturity and transformation journeys.
What You'll Bring To The Role
- 5\+ years in enterprise customer delivery, professional services, program management, or consulting (SaaS, AI, CX, digital transformation, or contact center domains preferred)
- Proven success leading complex enterprise implementations with cross\-functional and executive stakeholders.
- Strong understanding of contact center KPIs like containment, AHT, CSAT, NPS, and how they influence AI Agent projects.
- Comfort leading customer\-facing discussions \- from deep technical troubleshooting to weekly project demos.
- Demonstrated ability to manage multiple projects simultaneously in fast\-paced, evolving environments.
- Excellent communication, training, documentation, and relationship\-building skills.
- Bonus points for:
- + Experience with Conversational AI, VoiceAI, RAG systems, or NLU/NLP platforms.
+ Hands\-on experience to CCaaS platforms (Genesys, NICE, Amazon Connect, Five9, Talkdesk, Zoom Contact Center).
Why You'll Love It Here
- Competitive compensation including equity: Market\-aligned base pay, performance incentives, and meaningful equity ownership
- Excellent medical, dental, and vision insurance options: Comprehensive medical, dental and vision benefits for employees and eligible dependents
- Flexible Paid Time Off: Our unlimited, flexible PTO policy empowers you to take the time you need to recharge, maintain balance, and perform at your best.
- Additional Time to Recharge: 10 company holidays, an annual company\-wide Winter Break, and paid parental leave to fully support life outside of work.
- 401(k) plan: Long\-term financial planning support with tax\-advantaged retirement savings
- Quarterly Lifestyle Spending Account: Flexible quarterly stipend to support wellness, learning and professional development, and personal growth
- Monthly Mobile \+ Internet Stipend: Support for remote and hybrid work connectivity needs
- Pre\-tax Commuter Benefits: Tax\-efficient transit and commuting support for hybrid and in\-office employees
- Autonomy and Agency: Play a meaningful role in scaling a category\-defining GenAI platform transforming the future of customer experience.
Salary Range
The base salary compensation range targeted for this full\-time position is $133,000\-$149,000 Range per annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices.
Our Commitment to Inclusion and Belonging
*Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.*
*We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non\-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.*
*If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply.*
*\#LI\- Hybrid*
Salary Context
This $133K-$149K 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 Observe.AI, 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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($141K) sits 41% below the category median. Disclosed range: $133K to $149K.
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.
Observe.AI AI Hiring
Observe.AI has 1 open AI role right now. They're hiring across AI Agent Developer. Based in Redwood City, CA, US. Compensation range: $149K - $149K.
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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