{"id":1940264,"url":"https://alion.io/job/woodfrog-software-engineer-nlpllm-reasoning","title":"Software Engineer - NLP/LLM Reasoning","company":{"id":1323161,"name":"Woodfrog","domain":"woodfrog.ca","url":"https://alion.io/company/woodfrog","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["Pune, India"],"countries":["IN"],"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":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"AI Agents","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GCP","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-06T00:54:17Z","employer_posted_date":null,"last_verified_at":"2026-10-06T00:54:17Z","board_verified":false,"closed_at":null,"days_open":15,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":15},"description":"About the RoleWoodfrog is hiring Software Engineers – NLP/LLM Reasoning for one of our deep-tech clients building advanced reasoning models for enterprise applications using Large Language Models (LLMs). This is an opportunity to work at the intersection of cutting-edge AI research and production engineering, developing intelligent systems that solve complex real-world business problems.\nAs a Software Engineer, you will be responsible for designing, developing, and optimizing enterprise-grade reasoning models while researching innovative NLP techniques and integrating them into scalable production systems. You will collaborate with cross-functional teams to deliver high-quality AI solutions, maintain clean and efficient code, and continuously improve model performance.\nThis role is best suited for engineers who enjoy solving challenging problems, thrive in fast-paced startup environments, and are passionate about advancing the capabilities of LLMs and reasoning systems.\nKey ResponsibilitiesDesign, develop, and optimize foundational reasoning models for enterprise applications.\nResearch and implement advanced NLP techniques and reasoning paradigms.\nBuild, maintain, and improve production-ready AI systems powered by Large Language Models.\nWrite clean, efficient, scalable, and well-documented Python code.\nCollaborate with product, engineering, and research teams to define technical solutions.\nMonitor, troubleshoot, and improve model performance and system reliability.\nStay up to date with the latest developments in NLP, LLMs, and AI research, and apply them to real-world products.\nRequired Skills & QualificationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Linguistics, or a related field.\nStrong programming skills in Python.\nHands-on experience with Natural Language Processing (NLP) and Large Language Models (LLMs).\nExperience with TensorFlow, PyTorch, or similar deep learning frameworks.\nGood understanding of transformer architectures, prompt engineering, embeddings, and reasoning techniques.\nStrong analytical, debugging, and problem-solving skills.\nExcellent communication and collaboration abilities.\nAbility to work independently in a high-ownership, fast-paced environment.\nPreferred QualificationsExperience with Retrieval-Augmented Generation (RAG), Vector Databases, or Agentic AI.\nFamiliarity with LLM fine-tuning, evaluation, and optimization.\nExperience deploying AI models in production environments.\nKnowledge of cloud platforms such as AWS, Azure, or 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