Engineering Manager, Research
Decagon is hiring an Engineering Manager, Research in San Francisco, United States. It pays $280k-$430k a year and Level rates it ; you can apply on Decagon.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- Tools and skills the posting cites include AI agents, machine learning and research.
- Level classifies it as a lead role.
- Level lists 133 other open roles at Decagon.
AI in this role
Lead and grow an applied conversational AI research team focused on model post-training, evaluation, and safety.
About Decagon
Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.
Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.
We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.
We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.
About the Team
Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs
The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.
Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.
About the Role
We’re looking for a manager to lead and grow a team within Decagon Research. You’ll own the team and technical roadmap for an area spanning model post-training, evaluation, safety, speech, or agent behavior, driving ambitious ideas from research to reliable production impact.
Managers here operate with high ownership and technical depth while helping their teams move quickly and maintain a high quality bar. You’ll create clarity in ambiguous research areas, develop exceptional engineers, and align the team’s work with the product outcomes that matter most to customers.
In this role, you will
Build, manage, and develop a high-performing team of research engineers through hiring, coaching, performance management, and career development
Own the technical direction and roadmap for your area, prioritizing the highest-leverage investments across models, evaluation, safety, speech, and agent systems
Turn open-ended research directions into focused programs with clear hypotheses, milestones, decisions, and measures of production impact
Stay close to the technical work through architecture and experiment reviews, debugging, and individual contribution
Set a high bar for experimental rigor, reproducibility, evaluation quality, engineering execution, and safe model rollouts
Partner across Infrastructure, Agent Platform, Product Engineering, Product, and customer-facing teams to move research into production
Your background looks something like this
5+ years of industry experience building machine-learning systems involving language models, speech, agents, or model infrastructure
1+ years of people management experience, with a strong individual-contributor background
Deep experience post-training, evaluating, deploying, or serving foundation models at scale
Strong technical judgment and a track record of translating ambiguous research ideas into measurable product outcomes
Experience hiring, coaching, and developing technical talent, with clear communication across research, engineering, product, and executive stakeholders
Even better if you have
A record of influential research, open-source contributions, or production ML systems with significant real-world impact
Compensation
$280K – $430K + Offers Equity
This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.
In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.
Benefits
We proudly offer the following benefits for our full-time employees:
Medical, Dental, and Vision benefits for you and your family
Life Insurance and Disability Benefits
Retirement Plan (e.g., 401K, pension)
Parental Leave
Fertility and family building benefits through Carrot
Monthly stipend to support your wellness, lifestyle, and work-life balance
Daily lunches and snacks in the office to keep you at your best
Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
How we rate this
Engineering Manager, Research at Decagon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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 decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where research was part of your work. What did you do?
- Tell me about a project where conversational ai was part of your work. What did you do?
- Tell me about a project where model training was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Machine learning, Research, Conversational AI, and Model Training. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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