Senior AI Engineer

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Occupation tasks (O*NET)

Public-domain labor data — prepare examples for 2–3 of these.

• Analyze problems to develop solutions involving computer hardware and software.
• Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
• Assign or schedule tasks to meet work priorities and goals.
• Meet with managers, vendors, and others to solicit cooperation and resolve problems.
• Design computers and the software that runs them.
• Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
• Evaluate project plans and proposals to assess feasibility issues.
• Participate in multidisciplinary projects in areas such as virtual reality, human-computer interaction, or robotics.

O*NET source

Company facts (cached)

Website: talkspacecorporate.com

Public cache only — not an employee review.

Role overview (listing rewrite)

Talkspace Corporate is hiring a remote Senior AI Engineer to lead the creation of the autonomous AI agents powering our behavioral health platform. If you're driven to put quality mental healthcare within reach of millions, this is your chance to shape technology that genuinely changes lives. About the Role As a Senior AI Engineer at Talkspace Corporate, you will serve as a hands-on technical leader, owning the full lifecycle of our multi-agent systems—from cognitive architecture and interaction design through resilient production deployment and continuous learning. The work draws on Large Language Models for reasoning, planning, and goal setting, alongside Reinforcement Learning methods used to safely and ethically model human behavior. Because behavioral health is deeply personal, this remote role places extraordinary weight on safety, transparent autonomy, ethical decision-making, and data privacy. This position is fully remote and operates within Eastern Standard Time; Talkspace's headquarters are located in New York City. Key Responsibilities Architect and build the core agents behind Sentia, including planning modules, memory and retrieval layers, goal-setting logic, and tool-use orchestration. Apply Reinforcement Learning, Inverse RL, and control-theory techniques to craft adaptive, long-horizon intervention strategies that lift user outcomes while reducing risk. Select, fine-tune, and ship foundation models that drive empathetic, context-aware, and accurate agent communication. Model human-agent interaction using insights from cognitive science and behavioral economics so agents stay trustworthy and aligned with therapeutic protocols. Build simulation environments to pre-train and stress-test agent policies across diverse psychological scenarios. Tune deployment for low-latency, high-resilience multi-agent orchestration. Evaluate and champion emerging agentic frameworks and system patterns that keep Sentia ahead of the field. Design end-to-end evaluation and observability pipelines—trace-level analysis, offline scoring against golden datasets, live drift monitoring, guardrails, and human-in-the-loop review—plus metrics for reasoning quality, task completion, and safety compliance. Qualifications Bachelor's or Master's in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, or another rigorous quantitative discipline. 5+ years in production software engineering, with 3+ years dedicated to building and deploying complex ML or autonomous systems. Advanced Python skills, including its scientific ecosystem. Proven MLOps experience: CI/CD pipelines for ML models within service-oriented architectures. Practical command of agentic AI—Reinforcement…

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• What does success look like in the first 90 days for this role?
• How is the team structured, and who would I work with most?
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• Is the work primarily based in Remote, hybrid, or fully remote?