The posting
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._



