AI Agent Engineer (LLM Engineer | Agentic AI Engineer | Generative AI Engineer)
DigitalXNode
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Job summary
DigitalXNode is hiring an AI Agent Engineer in Bengaluru to design and build autonomous AI agents capable of interacting with enterprise software, APIs, and data systems.
You will advance LLM-powered applications, craft prompt engineering workflows, and implement robust agent tool-calling and orchestration frameworks for scalable deployments.
Qualifications
- Master's degree, PhD, or equivalent practical experience in CS, AI, ML, Robotics, or data science.
- Strong expertise in LLMs, Generative AI, and AI Agent development.
- Experience integrating AI agents with enterprise software.
Responsibilities
- Design, build, and optimize intelligent AI agents for consumer and enterprise applications.
- Develop scalable agent architectures enabling autonomous decision-making and task execution.
- Implement prompt engineering workflows and agent tool-calling mechanisms.
- Develop deployment frameworks for cloud and edge AI systems.
- Create evaluation frameworks to measure reliability, latency, and scalability.
Skills
Education
Tools
Job description
We are looking for a highly skilled AI Agent Engineer to design, build, and optimize next-generation AI agents that interact seamlessly with enterprise software systems. This is an exciting opportunity for professionals passionate about Agentic AI, Large Language Models (LLMs), Generative AI, Autonomous AI Systems, AI Infrastructure, and Machine Learning Engineering.
As an AI Agent Engineer, you will develop intelligent agent frameworks, agent tool integrations, prompt engineering workflows, and scalable deployment solutions that enable AI systems to perform complex tasks across real-world applications. You will work on cutting-edge AI technologies and help shape the future of autonomous AI interactions.
The AI Agent Engineer will play a critical role in building the infrastructure and interaction patterns that enable AI agents to communicate effectively with software systems, APIs, databases, enterprise platforms, and automation tools.
You will contribute to the design and implementation of advanced Agentic AI systems, develop LLM-powered applications, enhance AI agent performance, and create robust evaluation frameworks to measure reliability, accuracy, and scalability.
This role is ideal for professionals with experience in Generative AI, LLM Engineering, AI Software Development, Machine Learning, Robotics, Autonomous Systems, and AI Infrastructure Engineering.
- Building, deploying, and optimizing intelligent AI agents for consumer and enterprise applications.
- Developing scalable agent architectures that enable autonomous decision-making and task execution.
- Designing advanced agent workflows using Large Language Models (LLMs) and Generative AI technologies.
- Enhancing the AI agent's reasoning, planning, memory, and tool-utilization capabilities.
- Developing and optimization of applications powered by Large Language Models.
- Implementing prompt engineering strategies to improve AI agent performance and reliability.
- Designing agent tool-calling mechanisms and orchestration frameworks.
- Building multi-step reasoning systems that enable AI agents to solve complex business problems.
- Improving agentic interaction patterns for enterprise-scale AI deployments.
- Developing deployment frameworks for cloud-based and edge-deployed AI systems.
- Creating scalable infrastructure for AI agent testing, evaluation, monitoring, and continuous improvement.
- Building systems that support model versioning, experimentation, and performance tracking.
- Collaborating with platform engineering teams to ensure reliable AI deployments.
- Designing evaluation frameworks for measuring AI agent quality, safety, and performance.
- Conducting benchmarking and testing of LLM-powered applications.
- Improving the accuracy, latency, reliability, and scalability of AI systems.
- Developing automated testing methodologies for AI agent workflows.
- Integrating AI agents with APIs, enterprise applications, databases, cloud platforms, and software ecosystems.
- Expanding the capabilities of AI systems through seamless interaction with classical software environments.
- Collaborating with software engineering, machine learning, and product teams to deliver AI-powered solutions.
- Staying updated with current advancements in Agentic AI, Generative AI, LLMs, AI Agents, Autonomous Systems, and Machine Learning.
- Evaluating emerging AI frameworks, tools, and research developments.
- Contributing innovative solutions that improve AI system performance and business impact.
- Master's degree, PhD, or equivalent practical experience in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Data Science, or a related discipline.
- Strong expertise in Large Language Models (LLMs), Generative AI, and AI Agent development.
- Experience building and integrating AI agents with enterprise software systems and applications.
- Strong programming skills in Python, Java, Go, or other modern software development languages.
- Deep understanding of Agentic AI architectures, prompt engineering, and AI orchestration frameworks.
- Experience developing AI-powered applications, autonomous systems, or machine learning solutions.
- Strong software engineering and problem-solving capabilities.
- Experience developing AI solutions for autonomous vehicles, robotics, or intelligent systems.
- Proven track record of innovation in Artificial Intelligence, Machine Learning, or Agentic AI.
- Contributions to research publications, open-source projects, technical communities, or industry conferences.
- Experience working with multimodal AI systems involving image, video, LiDAR, radar, or sensor data.
- Familiarity with MLOps, AI Ops, model lifecycle management, and reproducible AI pipelines.
- Experience with C/C++ development is an added advantage.
- Knowledge of robotics, motion planning, autonomous systems, or advanced machine learning applications.
- Artificial Intelligence (AI)
- Generative AI
- Agentic AI
- Large Language Models (LLMs)
- Autonomous AI Systems
- Multi-Agent Systems
- Machine Learning
- Deep Learning
- Reinforcement Learning
- Python
- Java
- Go
- C++
- SQL
- LangChain
- LangGraph
- CrewAI
- AutoGen
- LlamaIndex
- OpenAI APIs
- Vector Databases
- Retrieval-Augmented Generation (RAG)
- AWS
- Azure
- Google Cloud Platform (GCP)
- Kubernetes
- Docker
- CI/CD Pipelines
- Model Deployment
- Model Monitoring
- Experiment Tracking
- AI Evaluation Frameworks
- Model Versioning
- ML Pipelines
- Work on cutting-edge AI Agent Engineering and Generative AI technologies.
- Build intelligent autonomous systems used in real-world applications.
- Collaborate with world-class AI researchers, machine learning engineers, and software developers.
- Solve complex challenges involving Large Language Models, Agentic AI, and enterprise AI systems.
- Contribute to the future of autonomous AI and next-generation software platforms.
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