We are looking for an experienced Applied AI Engineer with expertise in Generative AI, Large Language Models (LLMs), Python, React, and AI application development. The ideal candidate will have hands-on experience designing, developing, deploying, and optimizing AI-powered applications using modern GenAI frameworks such as LangGraph, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP). This role requires strong software engineering fundamentals, AI model integration experience, and the ability to build scalable, production-ready AI solutions.
Key Responsibilities
Design, develop, deploy, and optimize AI-driven applications using Generative AI technologies.
Build end-to-end production AI systems by integrating machine learning models, LLMs, APIs, and supporting services.
Develop intelligent applications using LangGraph, RAG, MCP, and prompt engineering techniques.
Create scalable frontend interfaces using React and JavaScript/TypeScript.
Develop backend services and AI integrations using Python.
Ensure AI systems meet enterprise standards for reliability, explainability, observability, security, and regulatory compliance.
Optimize AI model performance, latency, accuracy, and cost efficiency.
Collaborate with product managers, architects, data scientists, and engineering teams to deliver AI-powered solutions.
Implement CI/CD pipelines and containerized deployments using modern DevOps practices.
Monitor production AI applications and continuously improve model quality and system performance.
Follow software engineering best practices, including code reviews, testing, documentation, and version control.
Required Skills
8–9 years of overall software development experience.
5+ years of hands-on experience with React and JavaScript/TypeScript.
Strong programming experience in Python.
Experience developing applications using Generative AI and Large Language Models (LLMs).
Hands-on experience with LangGraph, Retrieval-Augmented Generation (RAG), or Model Context Protocol (MCP).
Strong understanding of Prompt Engineering and AI workflow orchestration.
Experience integrating AI/ML models into enterprise applications.
Knowledge of AI model deployment, monitoring, explainability, and observability.
Experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.
Experience building and maintaining CI/CD pipelines.
Strong debugging, analytical, and problem-solving skills.
Excellent communication and collaboration abilities.
Preferred Skills
Experience with OpenAI, Anthropic, Azure OpenAI, or similar LLM platforms.
Knowledge of vector databases such as Pinecone, Chroma, FAISS, or Weaviate.
Experience with cloud platforms (AWS, Azure, or GCP).
Familiarity with ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
Experience with REST APIs and microservices architecture.
Understanding of AI governance, responsible AI, and regulatory compliance.
Company Benefits & Culture
Strong communication and analytical skills.
Ability to collaborate with operations, technical teams, and stakeholders.
Problem-solving mindset with attention to detail.
Ability to lead workshops and training sessions.