Artificial Intelligence Engineer

AiSensy; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

AiSensy, a WhatsApp-based Marketing & Engagement platform, seeks a Senior AI Engineer with 4+ years of experience to design, build, and scale production-grade AI systems powering the next generation of our platform.

You will own end-to-end AI solutions—from problem definition and architecture to deployment, monitoring, and optimization—working across LLMs, RAG, AI Agents, embeddings, vector search, and AI-powered microservices.

Qualifications

• 4+ years of professional AI/ML engineering experience.
• Strong Python backend development and production AI experience.
• Hands-on with LLMs, Generative AI applications, RAG pipelines and embeddings.
• Experience integrating OpenAI SDK, Google Generative AI SDK, or equivalent APIs and vector databases.

Responsibilities

• Design, develop, and deploy production-grade AI/ML solutions for real-world use cases.
• Build and optimize LLM-powered applications, RAG pipelines, AI Agents, and automation workflows.
• Evaluate and select models, architectures, prompting strategies, and retrieval approaches.
• Collaborate with OpenAI, Google Generative AI, and other foundation model providers.
• Develop reusable AI components and services that scale across product use cases.
• Own AI features from architecture to post-production optimization.

Skills

Python

Production AI

LLMs / Generative AI

RAG pipelines

Embeddings / Vector search

OpenAI / Google Gen AI SDKs

FastAPI / Flask

MongoDB

Redis

Docker / Kubernetes

API design / backend systems

Tools

MongoDB

Pinecone

Qdrant

Redis

Job description

AiSensy is a WhatsApp-based Marketing & Engagement platform helping businesses drive customer engagement, retention, and revenue growth through WhatsApp.

• 250,000+ businesses enabled with WhatsApp Engagement & Marketing


• 800+ crore WhatsApp messages exchanged annually through the AiSensy platform


• Trusted by leading brands including Adani, Delhi Transport Corporation, Yakult, Godrej, Aditya Birla Hindalco, Wipro, Asian Paints, India Today Group, Skullcandy, Vivo, PhysicsWallah, Cosco, and more


• Businesses drive 25–80% of their revenue through WhatsApp using AiSensy


• Mission-driven, high-growth startup backed by Marsshot.vc, Bluelotus.vc, and 50+ angel investors

About the Role

We are looking for a Senior AI Engineer with 4+ years of experience to design, build, and scale production-grade AI systems powering the next generation of AiSensy's WhatsApp engagement platform.

You will work hands-on across LLMs, RAG, AI Agents, embeddings, vector search, AI evaluation, and AI-powered microservices. You will own AI solutions end-to-end—from problem definition and architecture to development, deployment, monitoring, and continuous optimization.

This role is ideal for someone who has moved beyond experimentation and has real-world experience taking AI/ML systems into production, with a strong focus on scalability, accuracy, latency, reliability, and business impact.

What You'll Own

• Design, develop, and deploy production-grade AI/ML solutions for real-world business use cases.


• Build and optimize LLM-powered applications, RAG pipelines, AI Agents, and intelligent automation workflows.


• Evaluate and select appropriate models, architectures, prompting strategies, and retrieval approaches for different use cases.


• Work with OpenAI, Google Generative AI, and other foundation model providers.


• Build reusable AI components and services that can scale across multiple product use cases.

RAG & Vector Search

• Design production-grade Retrieval-Augmented Generation (RAG) systems.


• Develop effective document ingestion, chunking, embedding, indexing, retrieval, and reranking pipelines.


• Work with vector databases such as Pinecone, Qdrant, or equivalent technologies.


• Optimize retrieval quality, relevance, latency, and cost.


• Implement hybrid search and other advanced retrieval techniques where appropriate.

AI Agents & Automation

• Design and build AI Agents capable of reasoning, tool usage, workflow execution, and context management.


• Integrate AI systems with internal APIs, databases, and third-party services.


• Build reliable guardrails around agentic workflows to ensure accuracy, safety, and predictable behavior.


• Develop AI-powered automation for customer engagement and business workflows.


• Build high-performance AI microservices using Python and FastAPI/Flask.


• Design scalable APIs and services for AI-powered product features.


• Work with MongoDB and other data stores for structured and unstructured AI data.


• Design asynchronous and scalable workflows for AI inference and data processing.


• Implement caching and optimization strategies using technologies such as Redis where required.

AI Evaluation & Optimization

• Establish evaluation frameworks for LLM and RAG applications.


• Measure metrics such as accuracy, relevance, groundedness, hallucination rate, latency, and cost.


• Develop strategies to reduce hallucinations and improve response quality.


• Optimize prompts, retrieval strategies, model selection, and inference workflows.


• Continuously evaluate new models and AI technologies for potential production use.

Performance & Reliability

• Optimize AI systems for latency, throughput, scalability, reliability, and cost.


• Identify performance bottlenecks across model inference, retrieval, APIs, databases, and external integrations.


• Design systems capable of handling high-volume production workloads.


• Implement appropriate logging, monitoring, error handling, and observability.

Engineering & Technical Leadership

• Own AI features from architecture and development through deployment and post-production optimization.


• Participate in system design, architecture, and technical decision-making.


• Conduct code and design reviews and maintain high engineering standards.


• Mentor junior AI/ML engineers and contribute to best practices across the AI engineering team.


• Collaborate closely with Product Managers, Backend Engineers, Data teams, and leadership.

Must-Have Qualifications

• 4+ years of professional experience in AI/ML Engineering, Machine Learning Engineering, Applied AI, or a closely related role.


• Strong proficiency in Python and backend development.


• Hands-on experience building and deploying production AI/ML systems.


• Strong practical experience with LLMs and Generative AI applications.


• Hands-on experience building RAG pipelines, including chunking, embeddings, retrieval, and evaluation.


• Experience integrating OpenAI SDK, Google Generative AI SDK, or equivalent LLM APIs.


• Strong understanding of embeddings, semantic search, vector databases, and retrieval pipelines.


• Experience with FastAPI, Flask, or similar Python backend frameworks.


• Experience with vector databases such as Pinecone, Qdrant, Weaviate, Milvus, or equivalent.


• Experience working with MongoDB or similar databases.


• Strong understanding of AI evaluation, hallucination mitigation, prompt engineering, and LLM optimization.


• Good understanding of ML fundamentals including Transformers, neural networks, classification, clustering, KNN, and model evaluation.


• Understanding of API security, authentication, data privacy, and secure AI application design.


• Strong debugging, system design, and problem-solving skills.

Good to Have

• Experience with LangChain, LlamaIndex, LangGraph, or similar frameworks.


• Hands-on experience building AI Agents / agentic workflows.


• Experience with multimodal AI applications.


• Exposure to fine-tuning, LoRA/PEFT, or model adaptation workflows.


• Experience with hybrid search, reranking, BM25, or advanced retrieval optimization.


• Understanding of distributed systems and event-driven architectures.


• Experience with Redis or other caching systems.


• Experience optimizing LLM inference latency and cost.


• Experience with Docker, Kubernetes, AWS, or GCP.


• Familiarity with CI/CD and production ML/AI deployment practices.


• Experience with Node.js for integrations or auxiliary services.


• Experience working on SaaS, MarTech, conversational AI, CRM, CPaaS, or customer engagement products.

What We're Looking For

• Someone who has built and shipped AI systems to production, not just worked on POCs.


• Strong engineering fundamentals combined with practical AI/ML expertise.


• Ability to translate ambiguous business problems into scalable AI solutions.


• Strong ownership of system quality, accuracy, performance, and reliability.


• Comfortable making technical decisions independently.


• Strong experimentation mindset with a focus on measurable outcomes.


• Ability to mentor engineers and raise the technical bar of the team.


• Comfortable working in a fast-paced, high-growth startup environment.

What Success Looks Like

• Production AI features are delivered reliably and adopted by users.


• RAG and AI Agent systems achieve strong accuracy and relevance.


• AI applications maintain low latency and high reliability at scale.


• Hallucination and failure rates are continuously reduced.


• AI infrastructure is optimized for performance and cost.


• AI capabilities create measurable impact on customer experience and business outcomes.


• Engineering standards and AI development practices improve across the team.

Why Join AiSensy?

• Build AI products powering customer engagement for 250,000+ businesses.


• Work on real-world LLM, RAG, Agentic AI, and conversational AI problems at scale.


• Own AI systems from architecture to production.


• Work closely with Product, Engineering, and senior leadership.


• Join a high-growth, mission-driven SaaS company.


• Opportunity to shape AiSensy's next generation of AI-powered products.