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Salary: USD 200,000 - 400,000 / annual
Decagon is a conversational AI platform enabling enterprises like Avis, Block, Chime, and Oura Health to deploy AI agents for customer support and operations across voice, chat, email, SMS, and other channels. The company is backed by a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.
The Research team develops the model and decision-making stack powering Decagon's conversational agents. They research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation to make agents more accurate, robust, and efficient in real-world deployments.
As a Senior Research Engineer focused on Safety, you will be responsible for making Decagon's AI agents safe, reliable, and controllable from evaluation through production. You'll identify real-world failure modes and build the models, evaluations, and safeguards that prevent them.
Key responsibilities include:
- Research and build safeguards against prompt injection, unsafe tool use, sensitive-data disclosure, policy violations, and hallucinated commitments
- Build adversarial evaluations, simulations, red-team datasets, and regression suites informed by production failures
- Develop and deploy classifiers, judges, reward signals, post-training methods, and runtime safeguards for safer agent behavior
- Analyze production traces and incidents to identify root causes, test mitigations, and measure their impact
- Partner with Security, Product, Infrastructure, Legal, and customer-facing teams to turn enterprise requirements into scalable safeguards and rollout practices
Required qualifications:
- 4+ years of experience in AI/ML engineering, research, or AI safety
- Hands-on experience evaluating, post-training, or deploying language models or agentic systems
- Experience with modern post-training techniques (reinforcement learning, preference optimization, distillation, model routing, synthetic-data generation)
- Experience with adversarial testing, model red teaming, prompt injection, policy enforcement, privacy, or safe tool use
- Fluency in Python and modern ML tooling with strong experimental judgment and engineering depth to ship production systems
- Comfort owning ambiguous, high-stakes technical problems and making clear risk and product tradeoffs
Preferred qualifications include experience building safeguards for high-stakes or regulated enterprise workflows, and familiarity with human-in-the-loop review, incident response, or responsible rollout frameworks for ML systems.
Decagon is an in-office company driven by shared commitment to excellence and velocity. The company offers competitive benefits including medical/dental/vision, life insurance, disability, 401K, parental leave, fertility benefits, wellness stipend, daily lunches, and flexible vacation.
About Decagon
AI / Data / Infrastructure; SaaS / Enterprise Software — AI agents for customer support and enterprise operations.
