{"id":3585686,"url":"https://alion.io/job/cpl-software-engineer","title":"Software Engineer","company":{"id":2268173,"name":"Cpl","domain":"cpl.com","url":"https://alion.io/company/cpl-com","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":77,"open_postings":49,"ghost_share":0,"stale_share":0.918,"repost_share":0.02,"time_to_fill_p50_days":29,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Limerick, Ireland"],"countries":["IE"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":70000,"max":null,"currency":"EUR","period":"year","gross":null,"usd_annual":78166},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"Time Series","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"C++","optional":true},{"name":"Docker","optional":true},{"name":"Go","optional":true},{"name":"Linux","optional":true},{"name":"Machine Learning","optional":true},{"name":"Rust","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-29T13:01:54Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-01T15:23:48Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Role Summary\nParticipate in the development, maintenance, and operation of analytics and optimisation software within the energy technology domain.\nThe role requires strong technical thinking, reliability, and the ability to work independently without excessive supervision.\nCore Responsibilities\nContribute to the design and implementation of software modules and data-processing components.\nPerform analytical tasks involving mathematical models, time-series data, and optimisation workflows.\nConduct research on algorithms, data structures, and mathematical concepts as needed.\nAssist in troubleshooting, debugging, and improving system performance.\nCollaborate effectively with senior staff, engineering experts, and a wide range of customers, whilst managing tasks with minimal guidance.\nMaintain clear, concise technical documentation.\nDegree in Computer Science, Software Engineering, Mathematics, Electrical Engineering, or a related technical field (where coursework must involve some degree of software development).\nSolid grounding in programming fundamentals (control flow, data structures, complexity) and practical Python development experience.\nAbility to write, read, test, debug, and maintain Python code for analytics, data processing, automation, APIs, and prototype/R&D software.\nExperience with some additional high-level language is desirable\nFamiliarity with Linux environments and command line tooling, experience with using them within a commercial, or academic, environment.\nStrong problem solving skills and the ability to reason effectively and creatively with algorithms and software systems in general.\nAbility to work methodically and think independently, with the capability and confidence to defend views when challenged, explain concepts clearly to non-technical collaborators, and not be afraid to speak up in what can often be highly technical discussions.\nUnderstanding of time-series data, analytics workflows, and basic statistical methods.\nExposure to database paradigms including relational databases, NoSQL/document or key-value databases, and time-series databases. Specific products are less important than understanding how these paradigms are used and where each is appropriate.\nWorking knowledge of SQL and relational data modelling is expected; exposure to time-series storage and query patterns is a distinct advantage.\nExperience working with APIs, data streams, or messaging/queueing systems.\nOptional exposure to Rust, C/C++, or Go/Golang would be useful, particularly for performance-sensitive, systems, or integration work, but these are not mandatory requirements.\nFamiliarity with the concept of containerisation with Docker\nSome knowledge of cloud based computing such as AWS, Azure, or GC\nPractical aptitude for debugging and diagnosing issues across software layers.\nAn interest in mathematics along with a conceptual understanding of the workings of machine learning, large language models, and trends in the “AI” industry. Mathematical or programmatic understanding would be an advantage, but is not essential.\nAble to learn quickly, without repeated instruction.\nA curious, open minded attitude to continual learning.\nCommunicate clearly and concisely.\nEssential Qualifications\nDegree in Computer Science, Software Engineering, Mathematics, Electrical Engineering, or a related technical field (where coursework must involve some degree of software development).\nSolid grounding in programming fundamentals (control flow, data structures, complexity) and practical Python development experience.\nAbility to write, read, test, debug, and maintain Python code for analytics, data processing, automation, APIs, and prototype/R&D software.\nExperience with some additional high-level language is desirable\nFamiliarity with Linux environments and command line tooling, experience with using them within a commercial, or academic, environment.\nStrong problem solving skills and the ability to reason effectively and creatively with algorithms and software systems in general.\nAbility to work methodically and think independently, with the capability and confidence to defend views when challenged, explain concepts clearly to non-technical collaborators, and not be afraid to speak up in what can often be highly technical discussions.\nDesired Skills & Experience\nUnderstanding of time-series data, analytics workflows, and basic statistical methods.\nExposure to database paradigms including relational databases, NoSQL/document or key-value databases, and time-series databases. Specific products are less important than understanding how these paradigms are used and where each is appropriate.\nWorking knowledge of SQL and relational data modelling is expected; exposure to time-series storage and query patterns is a distinct advantage.\nExperience working with APIs, data streams, or messaging/queueing systems.\nOptional exposure to Rust, C/C++, or Go/Golang would be useful, particularly for performance-sensitive, systems, or integration work, but these are not mandatory requirements.\nFamiliarity with the concept of containerisation with Docker\nSome knowledge of cloud based computing such as AWS, Azure, or GC\nPractical aptitude for debugging and diagnosing issues across software layers.\nAn interest in mathematics along with a conceptual understanding of the workings of machine learning, large language models, and trends in the “AI” industry. 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Docs: https://alion.io/developers"}}