AI Engineer

Job Summary
We are looking for an AI Engineer to architect, build, and deploy production-grade AI applications powered by the latest advancements in generative AI. The ideal candidate combines strong software engineering skills with practical expertise in Large Language Models (LLMs), agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, and modern AI frameworks. You will work closely with cross-functional teams to develop scalable, reliable, and secure AI solutions, leveraging emerging technologies to automate complex processes, improve decision-making, and create exceptional user experiences.

Key Responsibilities
Architect, design, and deliver production-grade AI applications and intelligent agent systems leveraging state-of-the-art machine learning and generative AI technologies.
Integrate AI solutions with enterprise platforms, REST APIs, databases, MCP servers, and third-party services to enable end-to-end business workflows.
Evaluate, fine-tune, and optimize AI models using rigorous evaluation methodologies, ensuring accuracy, robustness, and business impact.
Optimize AI inference pipelines for scalability, latency, throughput, and cost efficiency while maintaining high availability in production environments.
Design and develop scalable backend services and APIs using Python and modern application frameworks to support AI-powered products.
Research, evaluate, and adopt emerging AI models, frameworks, and technologies, translating cutting-edge advances into scalable, production-ready solutions.
Collaborate with cross-functional engineering, product, and research teams to define technical strategy, influence architecture decisions, and deliver innovative AI capabilities.

Required Qualifications
Bachelor's or Master's degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.
2+ years of hands-on experience designing, developing, and deploying AI-powered applications.
Strong proficiency in Python and software engineering best practices.
Solid understanding of prompt engineering, agentic AI architectures, and AI application design patterns.
Hands-on experience with Large Language Models (LLMs), including OpenAI, Anthropic, Gemini, Llama, or similar models.
Experience building AI applications using orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen.
Experience designing and implementing Retrieval-Augmented Generation (RAG) systems using vector databases such as Pinecone, FAISS, Chroma, Weaviate, or Milvus.
Familiarity with AI evaluation and observability frameworks such as LangSmith, DeepEval, or Ragas.
Experience integrating AI solutions with REST APIs, databases, and third-party services.
Experience deploying and operating AI applications using Docker, Kubernetes, and modern cloud-native deployment practices.
Proficiency with Git, version control, and modern software development methodologies.
Strong analytical, problem-solving, and debugging skills.
Excellent written and verbal communication skills, with the ability to collaborate effectively across cross-functional teams.

Preferred Qualifications
Experience designing, deploying, and managing AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Familiarity with MLOps practices, including model lifecycle management, automated deployment, monitoring, and CI/CD pipelines.
Familiarity with modern AI agent interoperability and communication standards, including Model Context Protocol (MCP), Agent-to-Agent (A2A), Agent-to-UI (A2UI), and Agentic UI (AG-UI) frameworks.
Experience implementing AI safety measures, guardrails, and governance practices.
Experience fine-tuning open-source language models.

What We Offer
Opportunity to work on cutting-edge AI technologies.
Opportunity to influence the design and architecture of next-generation AI products.
Professional development and continuous learning opportunities.
Competitive salary and benefits.
Flexible working arrangements.