Generative AI Engineer (LLM & AI Agent Development)

We are seeking an experienced AI Engineer to design, build, and deploy enterprise-grade Generative AI and Agentic AI solutions that improve business operations and elevate customer experiences. This is a high-impact opportunity for a hands-on engineer who thrives in a fast-paced environment and is passionate about building production-ready AI applications. Candidates with demonstrated experience delivering scalable LLM-powered solutions, modern AI architectures, and collaborative cross-functional projects will be prioritized for interviews. Must Haves Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related technical discipline. 3+ years of professional software engineering experience with machine learning or AI applications. Proven experience developing and deploying production-grade applications powered by Large Language Models (LLMs). Advanced Python programming skills with experience using AI and data science libraries such as NumPy, Pandas, SciPy, and Scikit-learn. Hands-on experience with leading LLM platforms and orchestration frameworks, including OpenAI, Anthropic, Google AI models, Hugging Face, LangChain, LlamaIndex, or similar technologies. Experience designing Retrieval-Augmented Generation (RAG) pipelines and working with vector databases. Strong understanding of prompt engineering, embeddings, model evaluation, and AI application optimization. Experience developing scalable APIs, backend services, and enterprise AI integrations while collaborating effectively across technical and business teams. What the Client Needs You to Do In this role, you will help shape the organization's AI strategy by delivering intelligent applications that automate workflows, improve productivity, and enhance customer interactions. You will collaborate with engineering, data, and business stakeholders to design scalable AI solutions while ensuring reliability, security, and responsible AI practices. Success in this position requires balancing technical excellence with practical business outcomes and continuously evaluating emerging AI technologies to drive innovation. Key Responsibilities Design, develop, and deploy scalable applications powered by Large Language Models for internal and customer-facing solutions. Build intelligent AI agents capable of reasoning, planning, and executing complex, multi-step workflows. Develop and maintain Retrieval-Augmented Generation (RAG) pipelines that leverage enterprise knowledge sources and proprietary data. Design and implement Model Context Protocol (MCP) servers, AI assistants, and multi-agent platforms that support a wide range of business functions. Integrate AI solutions with enterprise applications, APIs, databases, and existing technology platforms. Create effective prompt engineering strategies, evaluation frameworks, and governance controls to improve model quality, safety, and compliance. Optimize AI model performance through prompt refinement, orchestration techniques, and appropriate model tuning strategies. Develop and support MLOps and LLMOps pipelines for monitoring, deployment, testing, and continuous improvement of AI systems. Evaluate build-versus-buy opportunities and collaborate with internal stakeholders and external technology partners to deliver scalable AI solutions. Research emerging advancements in Generative AI, Agentic AI, LLM architectures, orchestration frameworks, and industry best practices to continuously improve technical capabilities. Additional Information Experience building AI agents, autonomous workflows, or multi-agent systems is highly desirable. Familiarity with frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar agent orchestration platforms is preferred. Experience with fine-tuning techniques, including LoRA, PEFT, or other parameter-efficient training methods, is a plus. Exposure to cloud-based AI infrastructure within AWS, Azure, or Google Cloud Platform is preferred. Familiarity with Java, JavaScript, and enterprise application environments is beneficial. Experience implementing AI governance, observability, security controls, and responsible AI guardrails is considered a strong advantage. This position offers the opportunity to work on cutting-edge AI initiatives that directly influence enterprise innovation, operational efficiency, and customer experience while collaborating with multidisciplinary teams in a highly technical environment. Show more Show less