Senior AI Engineer

Role OverviewWe are seeking a highly skilled and innovative AI Engineer to design, develop, and deploy AI-powered applications and intelligent digital products. In this role, you will build scalable, secure, and user-centric solutions powered by Large Language Models (LLMs), machine learning, and cloud-native technologies, with a primary focus on AI services, agent workflows, and backend systems.The ideal candidate has strong expertise in modern software engineering combined with hands-on experience integrating AI capabilities into enterprise applications. You should be comfortable building scalable APIs, AI orchestration pipelines, agent workflows, and cloud deployments while collaborating in agile, fast-paced engineering teams.Key ResponsibilitiesDesign, 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.QualificationsBachelor’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 HaveWorking 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.