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Strong Tier-1 brand but senior, niche agentic AI specialization reduces competition.
LLM and AIOps skills are transferable, but banking risk, ITSM, and audit expectations raise domain sensitivity.
Explicit 10+ years, mandatory LLM production experience and safety/ITSM requirements increase filtering stringency.
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Design and implement multi-step agent workflows including planner, executor patterns, and multi-agent coordination.
Build secure integration layers for tool-calling enabling diagnosis and controlled remediation in production environments.
Implement RAG pipelines and integrate LLM models optimizing latency, cost, risk, and ensure AI safety controls with full auditability.
10+ years software engineering experience with at least 2 years building production LLM or agent systems.
Hands-on experience with agent orchestration frameworks like LangGraph or equivalent.
Strong Python engineering skills and practical API-first system integration experience.
Experience with RAG architecture, embeddings, output validation, hallucination controls, incident lifecycle, ITSM, CI/CD, and production risk controls.
Experienced in delivering auditable, risk-controlled automation in high-impact production IT environments.
Proficient in designing AI-driven agent orchestration with emphasis on safety, reliability, and operational integration.
Strategic thinker who can balance technical depth in LLM/agent systems with enterprise ITSM and change management constraints.