We are looking for technically hands-on professionals to design and deliver client-centric intelligent systems and support business growth through strategic pre-sales and solutioning initiatives. As part of our growing Enterprise AI consulting practice, we deliver real-world business value through the convergence of AI agents, machine learning, and modern enterprise architecture.

Key Responsibilities: Design and implement AI agents using LangChain, CrewAI, or AutoGen for enterprise-grade use cases. Develop modular code for task decomposition, memory handling, and tool integration with APIs. Collaborate with AI strategists and architects on project design and MVP delivery. Conduct testing and fine-tuning of agent behavior using LLM APIs and embeddings. Participate in internal code reviews, documentation, and reusable framework building. Support pre-sales demos and client innovation sessions with hands-on prototypes.

Requirements: Bachelor's or Master's degree in Computer Science, AI, or related field. PhD preferred for architect-level roles. 3+ years in AI/ML, with recent experience in agentic systems and hands-on development of LLM-based applications. Strong experience with Python and orchestration libraries such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar. Deep knowledge of LLMs (GPT, Claude, LLaMA, Mistral, etc.), prompt engineering, agent memory, tool calling, and autonomous task execution. Experience with RFP/RFI support, and proposal creation in a consulting or enterprise services environment. Understanding of enterprise solutioning with cloud platforms (AWS, Azure, GCP), API integration, and data security best practices. Exceptional communication and consulting skills, with the ability to present solutions to both technical and non-technical stakeholders.

Preferred Skills: Strong proficiency in programming languages such as Python, Java, Spring, Maven, JSON. Object Oriented Programming Hands-on exposure to cognitive architectures, planning-based agents, or reinforcement learning in real-world deployments. Experience integrating AI agents into enterprise apps like Salesforce, ServiceNow, SAP, or custom apps via APIs. Understanding of AI observability, performance monitoring, and ethical guidelines in GenAI systems.

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