AI Solutions Architect

Responsibilities

• Architect end-to-end GenAI systems, including prompt chaining, memory strategies, token budgeting, and embedding pipelines.
• Design and optimize Retrieval-Augmented Generation (RAG) workflows using tools like LangChain, LlamaIndex, and vector databases such as FAISS, Pinecone, or Qdrant.
• Evaluate tradeoffs between zero-shot prompting, fine-tuning, LoRA/QLoRA, and hybrid approaches; align solutions with user goals and constraints.
• Integrate LLMs and APIs (OpenAI, Anthropic, Cohere, Hugging Face) into real-time products and services with a focus on latency, scalability, and observability.
• Collaborate with cross-functional teams to translate complex GenAI architectures into stable, maintainable features that support product delivery.
• Write and review technical design documents and be actively involved in implementation decisions.
• Deploy to production following best practices for version control, API lifecycle management, and monitoring (including hallucination detection, prompt drift, etc).

Requirements

• Proven experience building and deploying GenAI-powered applications, ideally in enterprise or regulated environments.
• Deep understanding of LLMs, vector search, embeddings, and GenAI design patterns (such as RAG, prompt injection protection, tool use with agents).
• Proficiency in Python and fluency with frameworks and libraries like LangChain, Transformers, Hugging Face, and OpenAI SDKs.
• Hands-on experience with vector databases (FAISS, Qdrant, Pinecone).
• Familiarity with cloud infrastructure (AWS, GCP, Azure) and core MLOps concepts (CI/CD, monitoring, containerization).
• Delivery-focused mindset with the ability to balance speed, quality, and feasibility in fast-moving projects.

Preferred Qualifications

• Experience building multi-tenant GenAI platforms.
• Exposure to enterprise-grade AI governance and security standards.
• Familiarity with multi-modal architectures (e.g., text + image or audio).
• Knowledge of cost-optimization strategies for LLM inference and token usage.

Benefits

• Competitive salary and performance bonuses
• Comprehensive health insurance
• Professional development and certification support
• Opportunities to work on cutting-edge AI projects
• International exposure and travel opportunities
• Flexible working arrangements
• Career advancement opportunities in a rapidly growing AI company

This position offers the chance to shape the future of AI implementation, working with a talented team at the forefront of technological innovation. The selected candidate will play a crucial role in delivering transformative AI solutions to clients.

About the Company

Deeplight focuses on innovative artificial intelligence solutions for enterprise clients. While specific company information is not provided, applicants are encouraged to visit the company's official website for more details.