Agentic AI Engineer

Job Summary:

We are looking for an Agentic AI Engineer to join our growing team to design and develop agentic AI systems that can plan, reason, and act. This includes single- and multi-agent AI systems and orchestration of workflows that involve retrieval augmented generation (RAG), contextual awareness, reasoning, tool calling, and inter-agent communication. This role is ideal for software engineers with AI/ML development experience, and the passion for transforming generative AI models into actionable, goal-driven systems capable of solving complex, real-world business problems.

Key Responsibilities:

• Architect and build agentic AI systems that integrate agents with foundational generative AI models, third-party tools and enterprise systems, and APIs, using existing agentic frameworks or custom-built orchestrators.

• Build and maintain retrieval-augmented generation (RAG) and reasoning pipelines to ground agent decisions in reliable, real-world data, and enable persistent and adaptive agent behavior.

• Optimize orchestration and reasoning performance, balancing autonomy, interpretability, and reliability.

• Collaborate with Gen AI and application engineers, ML Ops, and product teams to deploy agentic AI systems in production.

• Monitor and benchmark agent performance and ensure that our AI systems are safe, accurate, trustworthy, and deliver an elegant user experience.

• Document agent architectures, communication flows, guard rails, context engineering, and orchestration logic to ensure reproducibility and clarity.

• Stay current with advances in multi-agent orchestration, RAG, cognitive architectures, and AI safety mechanisms.

• Collaborate with cross-functional teams to deliver complete solutions for our customers.

Minimum Qualifications and Experience:

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related fields with 2+ years of experience in development of agentic AI systems, and preferably, 5+ years of overall experience as a software engineer.

Required Expertise:

• Proficiency in Python and agentic frameworks such as LangGraph, DSPy, AutoGen, CrewAI, etc.

• Experience with APIs and agent communication protocols such as Model Context Protocol (MCP), Agent Communication Protocol (ACP), and Agent-to-Agent (A2A).

• Experience in prompt design, context engineering, and integrating AI agents with multimodal foundational AI models for reasoning, planning, and dialogue.

• Working knowledge of vector databases and retrieval augmented generation (RAG).

• Understanding of context windows, memory graphs, and long-term reasoning strategies in agentic systems.

• Solid foundation in computer science fundamentals such as data structures, algorithms, programming, design patterns, virtualization, etc., and strong problem-solving skills.

• Having high standards of code quality (clean, well-documented, modular, maintainable, reliable, efficient, secure coding) and automated testing.

• Team player with excellent interpersonal skills and ability to collaborate effectively with remote team members.

• Go-getter attitude and ability to flourish in a fast-paced, startup environment.

• Experience with or working knowledge of any of the following would be a big plus.

-Contributions to open-source agentic AI frameworks or orchestration protocols.

-Microservices and cloud deployments (e.g., AWS, Azure, GCP).

-Safety, guardrails, traceability, and explainability for agentic AI systems.