Senior AI Engineer

Role Overview

Key Responsibilities

• Design, develop, and maintain end-to-end AI-powered applications and platforms.
• Develop scalable backend services and APIs using Python, FastAPI, Node.js, or similar technologies.
• Integrate LLMs, AI agents, RAG pipelines, vector databases, and AI orchestration frameworks into enterprise applications.
• Build agent workflows—including multi-step reasoning, tool use, memory, planning, and human-in-the-loop patterns—using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Contribute to user-facing experiences by building or extending web interfaces with frameworks such as React or Next.js when required.
• Collaborate with product managers, designers, data scientists, and business stakeholders to translate requirements into technical solutions.
• Develop reusable backend modules, AI integration services, and (where relevant) UI components to accelerate product delivery.
• Optimize applications for performance, scalability, reliability, and security.
• Implement authentication, authorization, API security, and secure system integrations.
• Work with relational and non-relational databases such as PostgreSQL, Redis, MongoDB, Elasticsearch, or Neo4J.
• Build and manage CI/CD pipelines, automated testing, and deployment workflows.
• Deploy and manage applications using Docker, Kubernetes, and cloud platforms preferably but not limited to Azure.
• Utilize AI-assisted development tools and engineering workflows to improve productivity, code quality, and delivery speed.
• Troubleshoot production issues, monitor application health, and ensure high availability of AI systems.
• Participate in code reviews, architecture discussions, and engineering best practices initiatives.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
• 3+ years of experience in software development, including hands-on experience building AI-enabled applications.
• Strong backend development experience using Python, FastAPI, Flask, Django, Node.js, or Express.js.
• Hands-on experience integrating Generative AI and Large Language Models (LLMs) into applications.
• Experience designing and building agent workflows, including tool use, multi-step reasoning, planning, and memory, using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Familiarity with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) architectures.
• Experience working with REST APIs, GraphQL, microservices, and distributed systems architectures.
• Experience with relational and NoSQL databases.
• Strong understanding of cloud-native development and containerization technologies such as Docker and Kubernetes.
• Experience with Git, CI/CD pipelines, automated testing, and agile development methodologies.
• Strong problem-solving, debugging, and analytical skills.
• Excellent communication and collaboration skills in cross-functional environments.
• Nice to Have
• Working knowledge of frontend technologies such as React, Next.js, TypeScript, HTML5, or CSS3.
• Experience building AI copilots, enterprise chatbots, or autonomous AI workflows.
• Familiarity with workflow automation platforms such as n8n, Dify, Flowise, LangFlow, or similar tools.
• Experience with AI orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar technologies.
• Experience with multimodal AI applications involving text, image, audio, or video processing.
• Exposure to MLOps practices including model deployment, monitoring, and lifecycle management.
• Knowledge of event-driven architecture and message brokers such as Kafka or RabbitMQ.
• Experience implementing real-time applications using WebSockets or streaming technologies.
• Familiarity with authentication protocols such as OAuth2, OpenID Connect, and JWT.
• Understanding of AI governance, responsible AI, and model evaluation practices.
• Experience with infrastructure-as-code tools such as Terraform.
• Contributions to open-source projects or technical communities.
• Experience using AI coding assistants and productivity tools in software engineering workflows.