About this role.
Sierra is seeking a Software Engineer to design, deploy, and continuously improve production AI agents for enterprise customers. The role owns the full Agent Development Life Cycle, from pilots and customer discovery through deployment, evaluation, and iteration. Work spans scalable AI/LLM systems, agent frameworks, RAG and prompt-engineering workflows, and integrations such as voice models. This is a customer-facing, high-agency engineering position in a primarily in-person Munich setting, with strong emphasis on speed, reliability, and business outcomes.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Sample interview questions
I would outline the user problem, architecture, rollout plan, evaluation suite, and operational metrics. I would emphasize combining offline task-quality evaluations with production measures such as successful resolution rate, latency, escalation rate, and incident trends, then using those signals to drive iterations.
I would use a constrained workflow with clear tool permissions, retrieval from approved support content, explicit confidence thresholds, and escalation paths for uncertain or safety-sensitive cases. I would test it against representative and adversarial conversation sets, monitor live outcomes, and continuously refine prompts, tools, and policies.
I would distinguish underlying workflow pain points from requested features, validate the problem with usage data and additional stakeholders, and define a measurable desired outcome. I would then prioritize reusable platform capabilities over one-off customizations where possible, while communicating scope, tradeoffs, and expected impact clearly.
I would create a labeled evaluation set covering cancellation reasons, policy constraints, difficult objections, and personalization opportunities. Key measures would include policy compliance, factuality, resolution quality, customer sentiment, retention impact, appropriate handoff behavior, and latency; all changes would be tested through versioned offline and controlled production evaluations.
I would explain how I identified the smallest safe release, documented assumptions and risks, added observability and rollback capability, and used staged deployment to learn quickly. I would also describe how I converted immediate learnings into follow-up engineering work so speed did not create unmanaged reliability debt.
About us
At Sierra, we’re building a platform to enable every company in the world to build better, more human customer experiences with AI. We partner with industry leaders such as SoftBank, Uber, Rivian, CLEAR, and Sutter Health. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia.
We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are committed to upholding them in everything we do.
Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google’s earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace.
What you’ll do
Design and deliver production-grade AI agents: You’ll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra’s growth. These aren’t prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce.
Drive the Agent Development Life Cycle (ADLC): You’ll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You’ll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way.
Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You’ll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency.
Build the future of the platform: Your direct work with customers will guide the evolution of Sierra’s core platform. You’ll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra’s product.
Example projects
These are some examples of projects that engineers on our team have worked on recently:
Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn
Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations
Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog!
Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development
Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers
What you’ll bring
Experience building and scaling end-to-end production systems
Strong technical problem-solving skills, especially in fast-changing, ambiguous environments
A builder and tinkerer’s mindset with high agency – you find creative ways to overcome obstacles and ship
Comfort working directly with customers to understand their needs and solve real-world problems
Excellent communication skills – clear, direct, and persuasive across technical and non-technical audiences
Even better…
Experience building or deploying AI/LLM systems in production
Have been a founder or founding engineer – you know what it means to balance craft, ownership, and speed
Familiarity with tools that power today’s AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering
Prior experience with React, TypeScript, and/or Go
Previous roles where you interfaced with customers or led technical projects with external stakeholders
Our values
Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.
Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.
Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.
Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.
Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.
What we offer
We want our benefits to reflect our values and offer the following to full-time employees:
Flexible (unlimited) paid time off
Medical, dental, and vision benefits for you and your family
Life insurance and disability benefits
Retirement plan dependent on country of employment
Parental leave
Fertility and family building benefits through Carrot
Lunch, as well as delicious snacks and coffee to keep you energized
Discretionary benefit stipend giving people the ability to spend where it matters most
Free alphorn lessons
These benefits are further detailed in Sierra’s policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra’s equity plans subject to the terms of the applicable plans and policies.
Be you, with us
We’re working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn’t precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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