Agentic AI Engineer

Role Overview:

We are looking for an innovative Agentic AI Engineer/Developer who will play a key role in designing, developing, and deploying intelligent autonomous systems powered by Agentic AI. You’ll be working at the forefront of AI, where you will architect and implement intelligent agents that can autonomously perform complex tasks, make decisions, and continuously learn. This is an exciting opportunity to work on cutting-edge Agentic AI frameworks, LLM orchestration, and advanced AI workflows that power next-gen autonomous systems.

In this role, you will be responsible for fine-tuning and deploying Large Language Models (LLMs), integrating them into Agentic AI frameworks to create adaptive, intelligent agents. The position requires a deep understanding of Agentic AI protocols (like MCP, A2A), Agentic workflows, and advanced concepts in model inference, to create AI solutions that can autonomously reason, learn, and act.

Key Responsibilities:

• Build Autonomous Agents: Design, develop, and deploy Agentic AI agents using frameworks like LangGraph, AutoGen, Crew AI, and other related platforms. These agents should operate autonomously, making decisions based on complex inputs and evolving situations.
• Agentic AI Workflow Integration: Develop and implement Agentic AI workflows that leverage LLMs, external tools, and memory systems to support modular agent systems that autonomously interact and adapt in real-time.
• LLM Optimization & Fine-Tuning: Fine-tune Large Language Models (LLMs) to fit specific Agentic use cases, utilizing advanced techniques like LoRA, QLoRA, PEFT, and continuous model retraining to improve performance.
• Autonomous System Design: Create intelligent agents that can interact with each other and external systems in real-time, handle complex decision-making processes, and adapt based on the context and feedback loops in dynamic environments.
• Agent-to-Agent Protocols (A2A): Implement and optimize Agent-to-Agent (A2A) communication protocols, ensuring that multiple agents can collaborate, exchange information, and autonomously solve problems.
• Memory & Knowledge Management: Develop systems for memory management and contextual awareness within autonomous agents, ensuring they retain and utilize prior knowledge to enhance their capabilities. Integrate Knowledge Graphs and Retrieval-Augmented Generation (RAG) techniques for improved reasoning.
• Scalable Inference Management: Optimize the inference of LLMs, ensuring the model can scale effectively across distributed systems, using caching techniques, vector databases (e.g., FAISS, OpenSearch, ChromDB, Pinecone, Milvus), and high-performance computing environments.
• Customer & Stakeholder Interaction: Lead rapid POCs, demos, and custom implementations for customers, ensuring that the technical solutions align with business needs and deliver real-world impact.
• Continuous Innovation: Stay up-to-date with the latest advancements in Agentic AI, LLMs, and autonomous systems to push the boundaries of what intelligent agents can do. Experiment with emerging technologies, algorithms, and frameworks to improve our AI solutions.

Primary Skills:

• Agentic AI Frameworks: Proven experience in building intelligent agents using Agentic AI frameworks like LangGraph, AutoGen, Crew AI, or other related platforms.
• LLM Expertise: Deep understanding of Large Language Models (GPT, T5, BERT) and the ability to integrate them into Agentic AI systems for autonomous tasks.
• Autonomous Systems Design: Experience in designing systems where agents interact autonomously, make decisions, and adapt to changing environments, using Agent-to-Agent (A2A) protocols.
• Advanced Prompt Engineering: Expertise in advanced Prompt Engineering techniques, particularly for Agentic AI, including Chain of Thought, Tree of Thought, and Chain of Density for enhancing agent reasoning capabilities.
• Memory Systems & Knowledge Graphs: Hands-on experience in implementing memory systems for autonomous agents and integrating Knowledge Graphs to help agents retain and leverage information for decision-making.
• Scalable Deployment: Experience in managing large-scale AI model deployments, optimizing for high-performance inference, utilizing vector databases like FAISS or Milvus, and managing real-time data flow.
• Agentic Workflows: Expertise in building intelligent workflows using Agentic protocols, integrating models, tools, memory, and external systems to enable autonomous decision-making.
• Vector Databases & Retrieval-Augmented Generation (RAG): Experience in using RAG for enhancing agent intelligence by providing them access to large databases, real-time knowledge retrieval, and reasoning.
• Advanced Integration: Ability to integrate and orchestrate workflows using platforms such as n8n, Zapier, Temporal, or other tools that enable automation of data, triggers, and model execution pipelines.

Must Have:

• Experience with Agentic AI protocols (e.g., MCP, A2A).
• Familiarity with open-source LLMs like Llama, Mistral, and DeepSeek for use in autonomous systems.
• Experience in designing and deploying multi-agent systems with the ability to enable communication and collaboration between agents.
• Knowledge of distributed systems, cloud technologies (AWS, Azure, GCP), and high-performance computing for scaling autonomous agent-based systems.
• Exposure to DevOps practices for CI/CD pipelines and deployment of autonomous AI systems.

Key Attributes & Qualities:

• Self-Driven & Independent: You thrive in a fast-paced, high-autonomy environment and take ownership of projects from ideation to deployment.
• Complex Problem-Solver: A deep passion for solving complex AI challenges and creating autonomous, self-adaptive systems that deliver real-world value.
• Clear Communicator: You can effectively communicate complex technical ideas, especially those related to Agentic AI, to both technical and non-technical stakeholders.
• Innovative Mindset: Always thinking ahead, you seek to innovate and push the boundaries of what autonomous agents can achieve using cutting-edge technologies.

Qualifications & Experience:

• Education: Bachelor's or Master’s degree in Computer Science, Engineering, AI, Data Science, or related fields (or equivalent experience).
• Experience: 3+ years of hands-on experience in Agentic AI, AI/ML, and LLMs. Proven track record of building and deploying autonomous systems and intelligent agents.
• Experience with Autonomous Systems: Hands-on experience developing systems with autonomous decision-making, reasoning, and Agent-to-Agent (A2A) interactions.

Why Join Us?

• Be on the Cutting Edge: Work on next-generation autonomous systems powered by Agentic AI, at the forefront of technological innovation.
• Innovative Culture: Be part of a creative and forward-thinking team that’s solving challenging problems in the world of intelligent, autonomous systems.
• Impactful Work: Your work will directly shape the future of AI-powered autonomous agents, pushing the boundaries of how AI can operate and interact with the world.