Solution Architect

# Solution Architect (AI / Gen AI Projects) ## Company Overview _Company information is not specified._ ## Job Summary We are seeking an experienced and hands-on **AI Architect** to lead our AI/ML and GenAI solution initiatives. This individual will design, develop, and deliver cutting-edge AI solutions using Generative AI Large Language Model (LLM) frameworks such as GPT or Llama. The role requires a strong mix of technical leadership, hands-on development, client-facing communication, and strategic thinking. ## Responsibilities - **Solutioning & Architecture:** - Architect scalable, production-grade AI/ML and GenAI solutions using LLMs (e.g., GPT, Llama, Mistral), LangChain, and Vector databases (e.g., FAISS, Chroma, Pinecone, Weaviate). - Select and fine-tune LLMs (open-source or proprietary) for customer use cases. - Build end-to-end pipelines integrating OCR/NLP with AI-driven workflows. - Design modular and reusable codebases using Python and machine learning frameworks. - Provide technical Proof of Concepts (PoCs) and solution blueprints for client proposals. - **AI & ML Development:** - Conduct hands-on development of ML/DL models, including supervised, unsupervised, and NLP models. - Build and optimize AI workflows on Azure/AWS platforms or on-premise using open-source stacks. - Implement vector search pipelines with Retrieval Augmented Generation (RAG). - Develop and manage APIs, microservices, and pipelines for AI models. - **Team Leadership & Mentorship:** - Guide and mentor junior developers and AI engineers. - Establish best practices, code quality standards, and model validation mechanisms. - Build and scale internal AI/ML competency through training and Centers of Excellence (CoEs). - **Client & Pre-Sales Engagement:** - Engage in pre-sales discussions, technical conversations, and discovery sessions with clients. - Translate business needs into AI solutions and communicate technical approaches. - Create solution decks, effort estimations, and demo prototypes. - **Product & Innovation:** - Contribute to building AI-based product ideas into Minimum Viable Products (MVPs). - Define and evolve product roadmap and technical architecture. - Ensure models are designed for scalability, maintainability, and performance. - **Project and Delivery Management:** - Participate in the entire project lifecycle including design, development, deployment, documentation, quality assurance, governance, and maintenance. - Contribute to all phases of project delivery from requirements gathering to post-deployment support. ## Qualifications - **Core Technical Skills:** - Strong experience with Generative AI and Large Language Models (e.g., OpenAI GPT, LLaMA, Mistral). - Expertise in orchestration frameworks like LangChain and LlamaIndex. - Hands-on experience with Python, FastAPI/Flask, PyTorch/TensorFlow. - Strong knowledge of NLP, Optical Character Recognition (OCR), and Transformers. - Experience with Vector Databases (e.g., FAISS, Pinecone, Chroma). - Proficiency with cloud AI platforms: Azure AI, AWS Sagemaker, GCP Vertex AI. - Familiarity with Hugging Face and OpenAI APIs, model fine-tuning, and deployment. - Understanding of MLOps principles, prompt engineering, and CI/CD for AI models. - **Architectural & Leadership Experience:** - 2+ years in a solution architect or tech lead role. - Experience working with agile teams and managing project deliveries. - Ability to design enterprise-grade AI solutions for real-world scenarios. - **Pre-sales & Communication:** - Strong communication and presentation skills. - Proven track record in pre-sales, proposal preparation, PoCs, and demos. - Ability to convey complex AI concepts to non-technical stakeholders. - **Product Management Mindset:** - Experience in designing BI/AI-driven products or tools. - Understanding of product lifecycle, market-fit analysis, and MVP strategy. - Passion for researching new trends and technologies in the BI/AI domain. ## Preferred Skills - Exposure to multimodal models (text, image, audio). - Familiarity with data governance, model explainability, and AI ethics. - Experience with AutoML, Reinforcement Learning from Human Feedback (RLHF), and fine-tuning LLMs with Parameter-Efficient Fine-Tuning (PEFT)/LoRA. - Knowledge of tools like Databricks, MLflow, Azure ML, and Streamlit. - Contributions to open-source projects or AI communities. ## Experience - 10 to 12 years of relevant experience with a minimum of 2 to 3 years of hands-on experience in Generative AI/LLMs. ## Environment - _Work setting and location are not specified._ ## Salary - _Salary information is not specified._ ## Growth Opportunities - _Potential career advancement opportunities are not specified._ ## Benefits - _Offered benefits information is not specified._