{"id":2881493,"url":"https://alion.io/job/ericsson-master-thesis-agentic-ai-for-secure-and-reliable-telecom-operations","title":"Master Thesis: Agentic AI for Secure and Reliable Telecom Operations","company":{"id":56456,"name":"Ericsson","domain":"ericsson.com","url":"https://alion.io/company/ericsson","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":83,"open_postings":85,"ghost_share":0,"stale_share":0.694,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Stockholm, Sweden"],"countries":["SE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Digital Twin","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-14T09:29:19Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T05:06:43Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Join our Team\nAbout this opportunity\nTelecom networks are becoming more intelligent, automated, and software-defined. Agentic AI could help engineers and operations teams understand network state, investigate incidents, plan actions, and coordinate tools across complex domains. Before these capabilities can be trusted, we need to understand how to design agents that are correct, secure, explainable, observable, and scalable.\nEricsson Innovation Center EMEA is inviting one or two master thesis students to investigate agentic AI for telecom operations. You will compare different agent patterns, including deterministic workflows, probabilistic language-model agents, tool-using agents, multi-agent approaches, and hybrid solutions that combine AI with explicit mathematical models or optimization.\nThe project is intended to produce both an academic contribution and a tangible evaluation environment that can guide future innovation work.\nWhat you will do\nYou will select one representative telecom operations problem and build a controlled environment in which alternative agent designs can be evaluated. You may work with a simulator, digital twin, synthetic network, or sandboxed lab environment.\nYour work may include, but is not limited to:\nDefining a benchmark for troubleshooting, configuration recommendation, incident triage, capacity optimization, or another network task.\nComparing deterministic automation, language-model agents, multi-agent designs, and hybrid architectures.\nInvestigating how mathematical models, constraints, planning, or optimization can improve agent reliability.\nDesigning security controls for prompt injection, tool misuse, privilege escalation, data leakage, unsafe plans, and cascading failures.\nEvaluating task success, correctness, constraint violations, safety, latency, cost, explainability, reproducibility, and recovery behavior.\nStudying human-in-the-loop approval, policy enforcement, auditability, rollback, and observability.\nInvestigating what is required to scale an agent from an innovation prototype to a production-like service.\nCategorizing failures and translating the results into practical architecture and adoption recommendations\nThe skills you bring\nKnowledge in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Software Engineering, or a related field.\nProgramming experience in Python, Java, Scala, TypeScript, or a similar language.\nInterest in generative AI, agentic systems, optimization, cybersecurity, distributed systems, or telecom networks.\nExperience with APIs, containers, evaluation frameworks, or cloud-native development is beneficial.\nInterest in designing experiments and analyzing quantitative results.\nEagerness to learn, challenge assumptions, and communicate findings to both technical and non-technical 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