{"id":3266038,"url":"https://alion.io/job/toppanecquaria-ai-engineer","title":"AI Engineer","company":{"id":183822,"name":"Toppanecquaria","domain":"toppanecquaria.com","url":"https://alion.io/company/toppanecquaria","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":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":5000,"max":8000,"currency":"SGD","period":"month","gross":true,"usd_annual":75120},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BERT","optional":false},{"name":"CrewAI","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-26T00:00:00Z","board_verified":false,"closed_at":null,"days_open":9,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":9},"description":"Responsibilities\nDesign, develop, and implement scalable AI and generative AI solutions for enterprise use cases.\nContribute to AI solution architecture, including the selection of appropriate models, frameworks, APIs, cloud services, and technologies.\nCollaborate with business stakeholders, domain experts, and clients to understand requirements and translate them into practical technical solutions.\nDevelop and integrate AI solutions leveraging LLMs, generative AI, AI agents, and open-source models.\nIntegrate AI solutions with APIs, enterprise applications, databases, and platforms such as Azure OpenAI and Hugging Face.\nDevelop and optimise end-to-end AI pipelines covering data processing, model development, deployment, and monitoring.\nImplement RAG, vector databases, similarity search, and other techniques to improve AI application performance and information retrieval.\nConduct research, proof-of-concepts, and evaluations of emerging AI technologies for enterprise applications.\nEstablish appropriate evaluation methods to assess the quality, accuracy, relevance, and performance of AI solutions.\nEnsure AI solutions adhere to appropriate security, privacy, scalability, and responsible AI practices.\nPrerequisites\nBachelors Degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related discipline.\nMinimum 2–3 years of experience in Data Science, Machine Learning, Artificial Intelligence, or related fields.\nExperience designing, developing, integrating, and deploying AI solutions, including LLMs, generative AI, AI agents, and/or open-source AI models.\nStrong knowledge of machine learning, deep learning, NLP, generative AI, and Transformer-based models such as GPT and BERT.\nProficiency in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, CrewAI, or AutoGen.\nExperience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in cloud environments.\nExperience with APIs, databases, vector databases, RAG, embeddings, and AI application integration.\nUnderstanding of solution architecture principles, system integration, scalability, security, and performance optimisation.\nKnowledge of data engineering practices, including data preparation, cleaning, preprocessing, and pipeline development.\nStrong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.\nStrong communication and stakeholder management skills, with the ability to explain technical concepts to both technical and non-technical audiences.\nPassion for AI innovation and the ability to stay current with emerging AI technologies and industry trends.\nSkills\nDesign, Generative AI Application Development and Deployment, AI Agents, Data Pipeline, Model Selection, AI Evaluation, Azure AI Search, Enterprise Applications, LLMs, Generative AI, Developing Frameworks, Cloud Services, Collaboration With Stakeholders, API, Databases, 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