Senior AI Agent Engineer

Roles and Responsibilities

• Design, implement, and optimize AI Agents using LLMs, reinforcement learning, planning algorithms, and decision-making frameworks.
• Develop scalable multi AI Agent architectures supporting long horizon reasoning, autonomy, planning, interaction, and complex task completion.
• Integrate AI Agents with APIs, backend services, databases, and enterprise applications.
• Prototype, deploy, and maintain AI-driven systems ensuring reliability and performance in production environments.
• Optimize agent behavior through continuous feedback, reinforcement learning, and user interaction.
• Collaborate closely with research, engineering, product, and deployment teams to iterate on agent capabilities and innovate continuously.
• Monitor AI Agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical AI practices.
• Document AI Agent architectures, design decisions, workflows, and maintain comprehensive technical documentation.
• Stay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.

Core Technical Skills

• Proficiency in Python and/or languages like JavaScript, TypeScript, Node.js, or Java, Go, with strong coding and software engineering practices.
• Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs.
• Hands-on experience with LLMs, prompt engineering, and natural language processing (NLP).
• Knowledge of agent orchestration platforms and multi-agent systems (e.g., AutogenAI, LangGraph, MCP protocol).
• Familiarity with data management, vector databases, semantic retrieval, and real-time data pipelines.
• Experience deploying AI systems on cloud platforms (AWS, Google Cloud) with container orchestration (Docker, Kubernetes).
• Strong understanding of machine learning model training, fine-tuning, and evaluation techniques.
• Awareness of AI ethics, data privacy, and secure handling of sensitive information.

Qualifications

• 5+ years of relevant experience and a Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, AI Engineering, or related fields.
• 3+ years of experience in AI, GenAI application development & deployment particularly with autonomous agent systems or related AI software engineering roles.
• Demonstrated ability to work independently in fast-paced, experimental environments.
• 3+ years of experience designing and building GenAI apps that allow users to experience AI use cases supporting features like agent orchestration, multi-step reasoning, prompt engineering, RAG integration, and model selection.
• 3+ years of experience with LLMs and deep learning models, machine learning lifecycle management, data generation methods, model training & validation coupled with strong fundamentals and passion in software engineering and system architecture.