Homomorphic Encryption enables computation on encrypted data, making it a key technology for privacy-preserving cloud computing and artificial intelligence workloads. Among modern schemes, CKKS is well suited for approximate numerical computation, but its adoption remains limited by the cost of polynomial arithmetic over large residue number-system moduli. Microsoft SEAL, a widely adopted open-source library, implements CKKS through reusable arithmetic primitives. Based on this decomposition, this paper presents a preliminary architectural study of FPGA-based microkernels to accelerate these arithmetic operations. The work targets modular addition, modular multiplication, and forward and inverse Number Theoretic Transforms as the core microkernels for CKKS ciphertext operations and investigates their implementation on pipelined and parallel FPGA architectures. The proposed microkernels have been implemented and evaluated on a Xilinx UltraScale+ device to assess the performance, scalability, and feasibility of an FPGA accelerator tightly integrated with Microsoft SEAL.