Sr AI Engineer

Job Description

We’re hiring a Senior AI Engineer to lead the development and deployment of cutting-edge AI

systems, with a focus on large language models (LLMs), real-time conversational agents,

multimodal intelligence, and multilingual capabilities. This role bridges deep ML expertise, system design, and hands-on implementation — ideal for someone excited to turn AI innovation into real world product impact. You’ll work across open-source and commercial models, cloud platforms, and global user contexts to shape the future of AI-driven user experiences.

*** This is a hybrid position - working 3 days a week from our Bangalore office. ***

- LLM Development & Prompt Engineering

• Design and optimize robust system prompts, few-shot examples, and dynamic control flows
  
  
  
  
  
  

for multilingual, compliance-sensitive use cases.

• Open-Source Model Finetuning
• Fine-tune LLMs (e.g., LLaMA, Mistral) using techniques like LoRA, QLoRA, DPO, and SFT on
  
  
  
  
  
  

domain-specific conversational and annotated datasets.

• Multimodal AI Solutions
• Build and integrate AI systems that process and generate across multiple modalities —
  
  
  
  
  
  

including text, audio, images, and structured data — to deliver richer, context-aware

interactions.

• Model Evaluation & Behavior Control
  
  
  
  
  
  

Develop structured evaluation frameworks covering accuracy, latency, tone, safety, and

compliance. Calibrate models to behave predictably in production settings.

• Retrieval-Augmented Generation (RAG)
  
  
  
  
  
  

Design and maintain RAG pipelines and vector databases to ground AI outputs in enterprise

data and conversational history.

• Multilingual Capabilities
• Build and maintain agents capable of fluent, context-sensitive communication across English,
  
  
  
  
  
  

French, Spanish, and other global languages, with support for code-switching and cultural nuance.

• Cloud-Native Deployment
  
  
  
  
  
  

Design and deploy scalable, secure ML systems across AWS (SageMaker, Bedrock, Q), Azure

(OpenAI, Foundry), and Google Cloud (AI Studio, Vertex AI).

• Production-Grade Delivery
• Translate prototypes into reliable, cost-optimized, production-ready systems. Run A/B tests
  
  
  
  
  
  

and integrate feedback loops for continuous improvement.

• Cross-Functional Collaboration
• Partner with product, engineering, and design teams to align AI solutions with user needs and
  
  
  
  
  
  

business impact.

• Mentorship & Standards
• Contribute to internal ML best practices, mentor junior team members, and champion operational excellence in MLOps and LLMOps.