{"id":1227079,"url":"https://alion.io/job/tredence-inc-generative-ai-architect","title":"Generative AI Architect","company":{"id":1263,"name":"Tredence Inc","domain":"tredence.com","url":"https://alion.io/company/tredence-inc","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","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, 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architecture, and solutioning of enterprise-grade GenAI platforms and applications.\n\nTotal Experience : 8 - 14 years\n\nKey Responsibilities : \n\nArchitecture & Solution Design : \n\n- Architect end-to-end GenAI solutions, including data pipelines, model selection, LLM fine-tuning, RAG frameworks, orchestration, and deployment.\n\n- Design scalable, secure, and cost-optimized GenAI reference architectures on Azure/AWS/GCP.\n\n- Define solution blueprints integrating LLMs, vector DBs, data lakes, enterprise APIs, and microservices.\n\n- Evaluate and select appropriate foundation models (OpenAI, Anthropic, Meta, Google, etc.) based on business needs.\n\nTechnical Leadership : \n\n- Provide architectural governance and best practices across multiple GenAI initiatives.\n\n- Guide engineering teams on model integration, optimization, evaluation, and MLOps/LLMOps.\n\n- Drive PoCs, feasibility studies, and technology assessments.\n\nRAG & LLM Engineering : \n\n- Architect Retrieval-Augmented Generation (RAG) systems using vector stores (Pinecone, FAISS, Weaviate, etc.)\n\n- Optimize prompt engineering, model evaluation, grounding, hallucination reduction, and response accuracy.\n\n- Implement model fine-tuning, domain adaptation, and performance monitoring.\n\nData Engineering & Security : \n\n- Design data ingestion, governance, and preprocessing pipelines for structured, unstructured, and multimodal data.\n\n- Ensure compliance with enterprise security, privacy, model safety, and responsible AI frameworks.\n\n- Collaborate with data engineering teams to integrate with enterprise data platforms.\n\nStakeholder Engagement & Delivery : \n\n- Work with business leaders to identify GenAI use cases, define roadmaps, and build ROI-driven solutions.\n\n- Prepare and deliver solution proposals, architecture documents, technical presentations, and cost estimates.\n\n- Collaborate with product, engineering, data science, and cloud teams for end-to-end delivery.\n\nRequired Skills & Experience : \n\nCore Technical Skills : \n\n- 8 - 14 years of experience in AI/ML, cloud architecture, or enterprise software engineering.\n\n- 3 - 5 years hands-on experience in LLMs / GenAI platforms.\n\nTech Stack : \n\n- LLMs (OpenAI, GPT, Claude, Gemini, Llama, etc.)\n\n- GenAI frameworks : LangChain, LlamaIndex, HuggingFace\n\n- RAG architecture, vector databases, embeddings\n\n- Cloud platforms : AWS (Bedrock/SageMaker), Azure (OpenAI/ML), GCP (Vertex AI)\n\n- Python, PyTorch, TensorFlow, REST, GraphQL\n\n- CI/CD, MLOps/LLMOps, containerization (Docker, Kubernetes)\n\nArchitecture & Solutioning Skills : \n\n- Enterprise architecture (TOGAF is a plus).\n\n- Building scalable, distributed microservices.\n\n- Design of secure AI systems with RBAC, encryption, data masking, model governance.\n\nSoft Skills : \n\n- Strong communication and executive-level presentation skills.\n\n- Ability to translate complex technical concepts into business-friendly language.\n\n- Proven leadership in multi-functional teams.\n\nPreferred Qualifications : \n\n- Master's degree in Computer Science, Engineering, AI/ML, or related field.\n\n- Certification in cloud architecture (AWS/Azure/GCP).\n\n- Experience in multimodal AI, agents, or advanced model fine-tuning.\n\n- Prior experience as an AI architect or lead ML engineer.\n\nWhy Join Us : \n\n- Lead strategic AI transformation initiatives for global clients.\n\n- Work with cutting-edge GenAI tools, models, and frameworks.\n\n- Opportunity to influence AI strategy and enterprise roadmaps\n\nSkills\nGenerative AI, LLM, LangChain, RAG, Python, Google Cloud Platform, Artificial Intelligence, AI Architecture, Machine Learning, 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