Architect, Applied AI Engineering
Icertis
Icertis is the global leader in AI-powered contract intelligence. The Icertis platform revolutionizes contract management, equipping customers with powerful insights and automation to grow revenue, control costs, mitigate risk, and ensure compliance - the pillars of business success. Today, more than one third of the Fortune 100 trust Icertis to realize the full intent of millions of commercial agreements in 90+ countries.
Who we are: Icertis is the only contract intelligence platform companies trust to keep them out in front, now and in the future. Our unwavering commitment to contract intelligence is grounded in our FORTE values—Fairness, Openness, Respect, Teamwork and Execution—which guide all our interactions with employees, customers, partners, and stakeholders. Because in our mission to be the contract intelligence platform of the world, we believe how we get there is as important as the destination.
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We’re hiring an AI Solutions Architect to design, lead and productionize complex business software and durable agentic systems built in Python. You will architect LLM-driven multi-agent workflows (durable orchestration using Temporal), productionize models on Azure AI / Azure OpenAI, and own LLMOps, RAG, safety, observability and governance for business-critical applications.
- Expert Python (production systems) and strong software architecture (DDD, microservices, event-driven, transactional patterns).
- Hands-on LLM/agent experience: Autogen, LangGraph, or equivalent agent frameworks.
- Proven experience building durable workflows with Temporal.
- Experience deploying/operating LLMs on Azure AI / Azure OpenAI.
- RAG, embeddings and vector DB experience.
- Familiarity with function-calling / tool integration patterns and secure API adapters.
- Strong leadership, communication and system-design skills.
Preferred Qualifications: - Advanced degree in CS/AI/ML or related.
- Experience in NLP, RL, or production model optimization (quantization, distillation, batching).
- Experience with enterprise security, privacy and compliance for AI.
- Architect and implement enterprise-grade LLM/agent systems in Python using frameworks such as Autogen, SemanticKernel, and LangGraph.
- Design durable agentic workflows and orchestration using Temporal (workflows, activities, signals, retries, long-running transactions).
- Build complex business software integrations (transactional flows, auditability, RBAC, idempotency) that agents operate within and act upon.
- Deploy and manage LLMs on Azure AI / Azure OpenAI: inference, scaling, cost/latency SLAs, caching, model routing.
- Design Retrieval-Augmented Generation (RAG) pipelines, embedding stores and vector DB integrations (Elasticsearch).
- Implement safe tool/function-calling patterns and secure adapters to external systems (APIs, DBs, messaging).
- Ensure model & agent safety, hallucination mitigation, bias controls, data governance and compliance.
- Mentor teams; conduct architecture reviews, design docs and runbooks for production readiness.