Job Title: LLM Architect-Product Engineering

Location: Pune

Employment Type: Full-Time

Experience: 8-12 Years

Domain: Generative AI / Large Language Models / AI Platforms

About the Role

We are looking for a highly experienced LLM Architect to lead the design and implementation of scalable, production-grade Generative AI systems for our product platform.

This is a strategic role in a product-based workplace, requiring deep expertise in Large Language Models (LLMs), prompt engineering, RAG architectures,

fine-tuning, model optimization, and enterprise AI deployment.

You will work closely with product, engineering, data science, and leadership teams to architect AI-native capabilities that differentiate our platform in the market.

Key Responsibilities

Architect end-to-end LLM-powered product features (chatbots, copilots,

semantic search, summarization, automation agents)

Design and implement RAG (Retrieval-Augmented Generation) pipelines

Lead LLM fine-tuning, prompt engineering, and model evaluation strategies

Build scalable, secure, and cost-effective AI architectures

Optimize inference performance and latency for production environments

Define LLM governance, safety, hallucination mitigation, and monitoring frameworks

Collaborate with data engineering teams for vector database and embedding pipelines

Evaluate open-source vs. proprietary LLM models for product integration

Mentor engineering teams and define AI architecture standards

Required Technical Skills Core LLM Expertise

8-12 years of experience in ML / AI / Platform Engineering

Strong hands-on experience with:

Large Language Models (GPT, Llama, Mistral, etc.)

Prompt engineering & structured prompting

Fine-tuning techniques (LoRA, PEFT,



adapters)

RAG architectures

Embeddings & vector search systems

Experience integrating LLM APIs (e.g., OpenAI, Anthropic)

Programming & Frameworks

Expert-level proficiency in Python (Mandatory)

Experience with

PyTorch / TensorFlow

Hugging Face Transformers

LangChain / LlamaIndex (or similar orchestration frameworks)

FastAPI / Flask for AI services

Data & Infrastructure

Vector databases (Pinecone, Weaviate, FAISS, Milvus, etc.)

Strong understanding of embeddings, semantic search

Cloud platforms (AWS / Azure / GCP)

Docker / Kubernetes

CI/CD for ML systems

Product & Architecture Expectations

Experience building AI features in a product-led environment

Understanding of

Scalability & cost optimization of LLM workloads

Security & compliance considerations (especially for enterprise customers)

Model evaluation metrics and A/B testing

Ability to design modular, reusable AI architecture components

Good to Have

Experience with multi-modal LLMs

Knowledge of Knowledge Graph + LLM hybrid systems

Exposure to edge deployment / on-prem AI solutions

Contributions to open-source AI projects

Experience working with global customers

Ideal Candidate Profile

Strong architectural mindset with hands-on coding capability

Product thinking and ability to balance innovation with reliability

Ability to translate business problems into AI-native solutions

Strong communication skills for stakeholder engagement

Experience mentoring senior engineers

Why This Role Matters

Generative AI is reshaping product ecosystems. As an LLM Architect, you will define the AI backbone of the platform and directly influence product differentiation, scalability, and long-term AI strategy.

📌 LLM Architect (Pune)
🏢 Datametica
📍 Pune