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Softility, Inc.

Technical Lead - AI & Data Science

Softility, Inc., Atlanta, Georgia, United States, 30383

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Experience : 7+ Years Required Skills: Master's in Data Science, Machine Learning, or a related field. 7+ years of hands-on experience in applied AI/ML roles, including 3+ years in a technical leadership or architect capacity. Proven success leading projects involving causal modeling, LLMs, intelligent agents, or explainable AI in a telco or large-scale operations setting. Deep knowledge of telecom data and workflows, such as alarm management, OSS/BSS systems, SNMP traps, root cause correlation, or network analytics. Prior experience building production-grade AI services in a telco NOC or network engineering environment Strong programming and architectural skills (Python, SQL, ML frameworks, cloud-native architectures). Experience with modern AI agent stacks (LangChain, AutoGen, CrewAI, or custom-built orchestration layers). Familiarity with vector search, RAG pipelines, embeddings, and knowledge graphs in operational use cases. Excellent communication, mentorship, and stakeholder engagement skills. Preferred : Familiarity with MLOps tools (e.g., MLflow, Vertex AI, Sagemaker) and deployment pipelines Contributions to AI/ML communities or open-source projects in causal reasoning or LLM applications Responsibilities : Lead architecture and design of end-to-end AI solutions, including causal inference models, LLM agents, and NLP systems tailored for telco operations. Oversee the development and integration of AI agents capable of understanding, explaining, and resolving issues using telco alarm data, SNMP traps, logs, traces, and ticket history. Drive experimentation and modeling efforts using advanced techniques in causality, graph analytics, language modeling , and root cause reasoning . Collaborate closely with network engineers, product managers, and executive leadership to translate business challenges into scalable AI applications. Mentor a team of data scientists, promoting best practices in software engineering, experimentation, and model lifecycle management. Own delivery of AI components into production workflows in coordination with MLOps, cloud, and data engineering teams. Stay abreast of the latest advancements in LLMs, generative AI, and domain-specific AI for operations, incorporating relevant breakthroughs into team strategy. #J-18808-Ljbffr