{"id":2673819,"url":"https://alion.io/job/itechminds-consulting-aiml-architect","title":"AI/ML Architect","company":{"id":3806477,"name":"iTechMinds Consulting","domain":"itechmindscl.com","url":"https://alion.io/company/itechminds-consulting","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":"staff","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":{"min_usd":31000,"max_usd":77000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ElasticSearch","optional":false},{"name":"FAISS","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"NER","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-10-16T04:28:44Z","employer_posted_date":null,"last_verified_at":"2026-10-16T04:28:44Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Position : AI/ML Architect\n\nLocation : Bangalore\n\nJob Summary : \n\nWe are seeking an experienced and visionary AI/ML Architect to lead the end-to-end design, development, deployment, and operationalization of advanced AI/ML and Generative AI (GenAI) solutions on cloud platforms. The ideal candidate will possess deep technical expertise in ML architecture, GenAI frameworks, Retrieval-Augmented Generation (RAG) pipelines, cloud-native deployment, and MLOps practices. You will work closely with cross-functional teams, clients, and engineering teams to define scalable AI strategies and deliver cutting-edge solutions across various domains.\n\nKey Responsibilities : \n\nCustomer Engagement & Solution Architecture : \n\n- Interact with clients and stakeholders to gather business and technical requirements and translate them into scalable AI/ML solutions.\n\n- Architect and design AI/ML systems across AWS, GCP, or Azure with a strong focus on cloud-native and cost-optimized architecture.\n\n- Create detailed system design documents, architecture diagrams, and technical roadmaps.\n\n- Define data architecture, storage, and retrieval strategies tailored to AI/ML workflows.\n\n- Lead the design and implementation of Generative AI solutions using LLMs, LangChain, LlamaIndex, Prompt Engineering, and vector databases such as Pinecone, FAISS, Weaviate, or Elasticsearch.\n\n- Architect RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases including knowledge management, chatbot development, and document summarization.\n\n- Implement prompt orchestration, retrieval optimization, and grounding techniques to enhance LLM output accuracy and relevance.\n\n- Guide the development of Python-based APIs, data preprocessing workflows, and model training pipelines.\n\n- Design and implement robust CI/CD pipelines for ML model deployment using tools like SageMaker, Vertex AI, or Azure ML.\n\n- Define and implement model monitoring, retraining, and performance management strategies for production-grade ML systems.\n\n- Ensure best practices in versioning, reproducibility, model lineage, and auditability (MLOps/LLMOps).\n\n- Review and approve system designs, PoCs, and implementation approaches.\n\n- Provide hands-on leadership and mentorship to data scientists, ML engineers, and software developers.\n\n- Lead architectural decision-making, code quality reviews, and sprint grooming sessions.\n\n- Champion best practices in security, compliance, scalability, and performance optimization for AI/ML solutions.\n\nRequired Qualifications : \n\n- 9+ years of overall IT experience in designing, developing, deploying, and operationalizing AI/ML solutions.\n\n- Minimum 3 years of experience in architecting end-to-end AI/ML solutions, including design, implementation, and production deployment.\n\n- Proven experience in GenAI, LLMs, RAG architecture, prompt engineering, and orchestration tools like LangChain, LlamaIndex, etc.\n\n- Hands-on with vector databases (e.g., Pinecone, FAISS, Elasticsearch) and unstructured data retrieval.\n\n- Deep knowledge of Machine Learning and Deep Learning algorithms : CNNs, RNNs, LSTMs, Transformers, etc.\n\n- Experience in Natural Language Processing (NLP), including language modeling, summarization, classification, and NER.\n\n- Strong expertise in Python, with frameworks like PyTorch, TensorFlow, HuggingFace, NumPy, and Pandas.\n\n- Demonstrated experience in designing cloud-native AI/ML 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