Observe AIAI Agent Engineer, Client Facing
Observe AI is hiring an AI Agent Engineer, Client Facing in Redwood City, United States. It pays $108k-$170k a year and Level rates it ; you can apply on Observe AI.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting allows some remote work.
- Tools and skills the posting cites include Claude, Gemini and Copilot.
- Level classifies it as a mid-level role.
- Level lists 8 other open roles at Observe AI.
AI in this role
Build, deploy, and integrate enterprise-grade voice and chat AI agents directly with clients as an AI Agent Engineer.
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
We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization.
You’ll own the end-to-end lifecycle of AI Agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance.
What You’ll Be Doing
- Build & Deploy Agents: Own the implementation of AI Agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks.
- Client Engagement: Act as the primary technical partner for customers—lead regular demos, communicate progress, gather feedback, and guide solutions from concept to production.
- Systems Integration: Configure and connect systems using APIs—handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools.
- Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality.
- Prompt Design & Optimization: Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets.
- Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion.
- Cross Functional Collaboration: Collaborate with product/engineering teams to escalate platform gaps and resolve deep technical fixes and platformization, while independently driving leading client implementations.
What You’ll Bring To The Role
- Bachelor’s degree in Computer Science, Engineering, or a related technical field
- 3+ years in conversational AI, solution engineering, system integration, or delivering AI/LLM-based applications in customer environments, software engineering, or system integration with hands-on delivery of AI/LLM-based solutions.
- Strong ability to communicate and lead customer-facing discussions - from deep technical troubleshooting to weekly project demos. Ability to explain complex technical concepts to non-technical audiences.
- Must have strong hands-on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect, etc.).
- Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.).
- Working knowledge of retrieval-augmented generation (RAG) concepts, implementation patterns and performance optimization.
- Programming experience in Python, JavaScript, or similar for scripting and integrations
- Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems.
- Experience with integration tools and Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficiency in API integrations and data flow management is a plus.
- Familiarity with telephony or voice systems (SIP, CCaaS, PSTN) is a plus.
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 $108 - 170K per year. 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. For more information, visit www.observe.ai.
#LI-Hybrid
How we rate this
AI Agent Engineer, Client Facing at Observe AI rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where prompt design was part of your work. What did you do?
- Tell me about a project where system integration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, Prompt Design, and System Integration. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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