{"id":3675395,"url":"https://alion.io/job/newron-ai-lead-engineer","title":"AI Lead Engineer","company":{"id":4204,"name":"Newron","domain":"newron.ai","url":"https://alion.io/company/newron","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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CNN","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-11-03T10:35:20Z","employer_posted_date":null,"last_verified_at":"2026-11-03T10:35:20Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"An AI Lead Engineer is responsible for designing, developing, implementing, and managing advanced Artificial Intelligence solutions to address complex business challenges. The role requires strong expertise in Deep Learning, Machine Learning, Generative AI, and AI architecture, along with the ability to lead end-to-end AI development initiatives.\n\nResponsibilities: \nDesign and develop scalable AI/ML solutions, ensuring high performance, accuracy, and reliability.\nLead the development and deployment of Machine Learning and Deep Learning models for real-world applications.\nArchitect and implement Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other advanced AI technologies.\nDefine AI architecture, technical strategies, and best practices for building scalable and production-ready AI systems.\nEvaluate and integrate modern AI frameworks, algorithms, tools, and technologies to improve solution efficiency.\nCollaborate with cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders.\nMentor junior AI/ML engineers and provide technical guidance throughout the development lifecycle.\nOptimise AI models for accuracy, scalability, performance, cost efficiency, and deployment readiness.\n\nRequirements: \nCandidates should have 6-8 years of hands-on experience in AI/ML engineering, including experience designing AI architectures, developing intelligent applications, deploying production-grade models, and leading technical teams or projects.\nThey should demonstrate strong problem-solving abilities, architectural decision-making skills, and the capability to translate business requirements into effective AI-driven solutions.\n\nCore Technical Skills: \nDeep Learning: Neural Networks, CNN, RNN, Transformers, TensorFlow, PyTorch.\nMachine Learning: Supervised and Unsupervised Learning, Model Training, Feature Engineering, Model Optimisation.\nGenerative AI: LLMs, Prompt Engineering, RAG, Fine-Tuning, LangChain, LlamaIndex.\nAI Architecture: AI Solution Design, Scalable AI Systems, Microservices, Model Deployment, MLOps.\nProgramming: Python, SQL, API Integration, REST APIs.\nCloud and Deployment: AWS, Azure, or Google Cloud; 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