AI Engineer - Forward Deployed Engineer

About the Role We are looking for an experienced AI Engineer (FDE) who can design, architect, and develop AI-powered solutions for diverse business use cases. The ideal candidate should possess strong GenAI and AI/ML expertise, be capable of solutioning across multiple AI technology stacks, and have excellent business communication skills to engage with stakeholders and translate business requirements into scalable AI solutions. Key Responsibilities • Design, architect, and implement AI/GenAI solutions for enterprise business use cases. • Engage with business stakeholders to understand challenges and recommend AI-driven solutions. • Build end-to-end AI applications using modern AI frameworks and cloud platforms. • Evaluate and adapt to different AI technologies, models, and platforms based on business needs. • Develop scalable RAG (Retrieval-Augmented Generation), AI Agents, and LLM-based applications. • Integrate AI solutions with enterprise systems and APIs. • Optimize AI model performance, cost, scalability, and security. • Collaborate with cross-functional teams including Product, Engineering, Data Science, and Business teams. • Stay updated with the latest advancements in AI, GenAI, LLMs, AI Agents, and cloud AI services. • Prepare solution architecture documents, technical proposals, and client presentations. Required Skills • 4+ years of experience in AI/ML or Generative AI solution development. • Strong experience with LLMs (OpenAI, Claude, Gemini, Llama, Mistral, etc.). • Hands-on experience building RAG pipelines , AI Agents, Agentic AI, and prompt engineering. • Experience with AI frameworks such as: • LangChain • LangGraph • LlamaIndex • Semantic Kernel • CrewAI / AutoGen (preferred) • • Strong programming skills in Python . • Experience with vector databases such as Pinecone, ChromaDB, Milvus, Weaviate, or FAISS. • Experience with cloud AI platforms (Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, etc.). • Good understanding of MLOps, model deployment, monitoring, and AI governance. • Experience integrating AI solutions using REST APIs and microservices. • Familiarity with containerization (Docker, Kubernetes) is an advantage.