Role Overview
We are seeking a highly skilled Senior AI Engineer to design, build, and scale next-generation AI
applications leveraging Large Language Models (LLMs), Agentic AI frameworks, Retrieval-
Augmented Generation (RAG), and cloud-native architectures. The ideal candidate will possess
strong software engineering expertise, hands-on experience with AI orchestration frameworks, and a
proven ability to take AI products from prototype through production deployment.
As a Senior AI Engineer, you will work closely with product teams, architects, data engineers, and
business stakeholders to deliver scalable, secure, and production-ready AI solutions that drive
business value.
Key Responsibilities
AI Solution Development
Design and develop enterprise-grade AI applications leveraging LLMs and Generative AI
technologies.
Build and deploy Agentic AI workflows using frameworks such as LangChain, LangGraph,
and LlamaIndex.
Design and implement Retrieval-Augmented Generation (RAG) architectures for knowledge-
driven AI solutions.
Develop intelligent agents capable of tool calling, memory management, reasoning, and
workflow orchestration.
Integrate AI services with enterprise systems through RESTful APIs and microservices.
Software Engineering & Platform Development
Develop scalable backend services using Python and asynchronous programming patterns.
Design reusable AI components, SDKs, and services to accelerate solution delivery.
Implement robust APIs with authentication, authorization, monitoring, and logging
capabilities.
Ensure software quality through unit testing, integration testing, and CI/CD pipelines.
AI Infrastructure & Cloud Engineering
Deploy and manage AI applications using Docker and Kubernetes.
Build cloud-native AI solutions on AWS, Azure, or Google Cloud Platform.
Optimize model serving, inference performance, scalability, and cost efficiency.
Implement observability, monitoring, and reliability practices for AI workloads.
Vector Search & Knowledge Systems
Design and optimize vector database solutions using Pinecone, Qdrant, Chroma, or similar
technologies.
Develop embedding pipelines, document indexing strategies, and semantic search
capabilities.
Implement data retrieval, ranking, and contextual grounding mechanisms to improve AI
response quality.
Leadership & Stakeholder Collaboration
Lead technical discussions, architecture reviews, and solution design workshops.
Mentor junior engineers and contribute to AI engineering best practices.
Collaborate with cross-functional teams to transform business requirements into scalable AI
solutions.
Drive end-to-end delivery from proof of concept through production rollout and operational
support.
