GenAI Engineer

Infosys Consulting is a globally renowned management consulting firm on the front-line of industry disruption. It operates as a mid-size player with an entrepreneurial spirit and is part of the larger Infosys group which is a top-5 IT brand experiencing rapid growth. The consulting business is recognized annually as a top firm by the Financial Times and Forbes for client innovations, diversity, and training programs. The company fosters an inclusive work culture.

• 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), prompt engineering, agent memory, tool calling, and autonomous task execution.
• Experience with RFP/RFI support and proposal creation in consulting or enterprise services.
• Understanding of enterprise solutioning with cloud platforms (AWS, Azure, GCP), API integration, and data security best practices.
• Exceptional communication and consulting skills for presentation to technical and non-technical stakeholders.

Nice to have:

• Strong proficiency in programming languages such as Python, Java, Spring, Maven, JSON, and 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.

• 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.