Описание
Key
Responsibilities
Building autonomous agents using LLMs, planning algorithms, and decision-making frameworks. Implementing agent architectures that support autonomy, interactivity, and task completion. , copilots, chatbots, automation tools).
Connecting agents to external services via APIs, databases, and cloud platforms. Tuning agent behavior using feedback loops, reinforcement learning, semantic knowledge layer and user interaction. Monitoring performance and implementing safety, reliability, and guardrail mechanisms.
Working cross-functionally with researchers, engineers, and product teams. Maintaining clear documentation of agent logic, designing decisions, and dependencies. Building and maintaining the Enterprise Agents and Tools Registry for metadata and lifecycle management.
Implementing the Agent Communication Gateway with robust security, rate limits, observability, and cost controls. ). Ensuring agent-level security, including authentication, authorization, and data protection.
Optimizing cost, scalability, performance, and reliability of agent operations across cloud and on-prem environments. Familiarity with knowledge graphs for agent reasoning and data integration. , LLM agents, orchestration frameworks).
Integrating AI systems with enterprise APIs, data platforms, and workflows. Solving technical blockers across data ingestion, model deployment, and agent behavior. Designing and refining prompts to ensure clarity, compliance, and contextual accuracy.
Translating business logic into agentic workflows and task trees. Tuning agent behavior to align with real-world expectations. Implementing observability tools to ensure reliability, latency, and trustworthiness.
Maintaining performance metrics and feedback loops for continuous improvement. Building and iterating custom AI solutions tailored to customer needs, leveraging agentic AI frameworks Owning delivery end to end, from scoping to production. Working as part of the customer team to engineer and deploy production-ready solutions that drive adoption and measurable business outcomes.
Actively contributing to the evolution of Kyndryl’s AI platforms through feedback, code contributions, and collaboration with product team Customer Engagement & Solution Integrity: Partn
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