Solutions Architect

The Solution Architect will be responsible for designing and implementing end-to-end AI architectures that integrate Large Language Models (LLMs) into production-ready products. This role sits at the intersection of software engineering, data science, and infrastructure, focusing on creating scalable, secure, and cost-effective AI solutions.

Key Responsibilities:

• Architecture Design: Lead the design of RAG (Retrieval-Augmented Generation) architectures, agentic workflows, and multi-model systems.
• Product Customization: Translate business requirements into technical blueprints for fine-tuning models or utilizing prompt engineering to meet specific product goals.
• Evaluation & Optimization: Establish frameworks for evaluating model performance (e.g., faithfulness, relevancy) and optimize for inference latency and token costs.
• Infrastructure & Integration: Design the integration between LLMs, vector databases (e.g., Pinecone, Milvus, or Weaviate), and existing enterprise data pipelines.
• Security & Compliance: Ensure all AI implementations adhere to data privacy standards, focusing on PII masking and preventing prompt injection or data leakage.
• Technical Leadership: Act as the bridge between the Product Owner and the Engineering team, ensuring technical feasibility and long-term maintainability

Required Technical Skills:

• Bachelors or Masters in Computer Science with 10 years of experience in the field & atleast 3+ years in technical architecture design for AI solutions
• LLM Frameworks: Deep proficiency in LangChain, LlamaIndex, or Haystack.
• Model Providers: Experience working with APIs from OpenAI, Anthropic, or Google (Gemini/Vertex AI), as well as open-source models (Llama 3, Mistral).
• Vector Databases: Practical experience with vector embeddings and similarity search.
• Cloud & DevOps: Strong knowledge of cloud AI platforms (AWS Bedrock, Azure AI Studio, or Google Vertex AI) and CI/CD for ML (MLOps).
• Coding: Proficiency in Python (fastAPI, Pydantic) and understanding of asynchronous programming

Preferred Qualifications:

• Experience in Fine-tuning (PEFT/LoRA) and quantization techniques.
• Background in traditional NLP (Named Entity Recognition, Sentiment Analysis).
• Familiarity with guardrail frameworks (e.g., NeMo Guardrails or Guardrails AI).

Job Locations Available:

Mumbai, Bangalore, Pune, Hyderabad, Gurgaon