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.