Technical Product Manager, Trust & Safety
J
JobgetherAI safety
Remote work opportunity within the United States.Full-TimeManager
Salary180,000 - 220,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- At least 5 years of product management experience
- Required Skills
- PythonCybersecurityMachine LearningProduct Management
Requirements
- At least 5 years of product management experience.
- Experience owning technical products in machine learning, AI data, cybersecurity, or trust and safety.
- Practical familiarity with large language model training and evaluation methods, including SFT, RLHF, RLAIF, reward models, verifiers, and benchmark design.
- Working knowledge of agentic AI systems, including tool use, computer-use agents, multi-step planning, and associated failure modes.
- Strong understanding of AI safety concepts such as reward hacking, deceptive alignment, jailbreaks, and prompt injection.
- Technical fluency to read code, review environment specifications with engineers, and make informed technical tradeoffs.
- Experience designing metrics for risk, system performance, and user impact and using data to guide product decisions.
- Demonstrated ability to launch products from 0 to 1 in fast-paced, ambiguous environments.
- Ability to explain complex technical concepts to researchers, customers, and executives.
- Creative and adversarial problem-solving ability, including anticipating how AI systems might exploit weaknesses or bypass safeguards.
- Familiarity with Python and sandboxed environments such as Docker, virtual machines, and browser automation is an advantage.
Responsibilities
- Translate AI research objectives into specifications for safety training data, reinforcement learning environments, and evaluations.
- Design sandboxed, trap-based reinforcement learning environments to test for AI safety failure modes.
- Develop cybersecurity scenarios involving prompt injection, exposed credentials, poisoned tools, and unsafe file or network actions.
- Build behavioral rubrics, verifiers, and reward signals into agentic tasks.
- Define evaluation frameworks and measurable safety metrics, including attack success rates, over-refusal, and task completion under adversarial pressure.
- Identify evaluation gaps, analyze results, and drive continuous product improvements.
- Prioritize product opportunities by evaluating technical and business tradeoffs.
- Collaborate with AI researchers, engineers, red-team specialists, policy experts, and delivery leads.
- Monitor agentic AI risks, alignment research, and emerging attack techniques to inform roadmap priorities.
- Prepare product specifications, customer briefs, and safety reports for technical and executive audiences.
View Full Description & ApplyYou'll be redirected to the employer's site
