Solution Architect – Enterprise Applications with AI/ML Exposure

Job Description

Job Title: Solution Architect – Enterprise Applications with AI/ML Exposure Experience: 8–10 Years Location: Thiruvananthapuram Employment Type: Full-time (WFO) Job Summary We’re looking for a talented Solution Architect with a strong foundation in designing and developing large-scale enterprise applications, and a growing interest or experience in modern AI/ML-driven technologies. This role is ideal for someone who is confident in architecture, passionate about emerging trends like AI/ML, and eager to help shape intelligent systems in collaboration with engineering and business teams. Design scalable, secure, and maintainable enterprise application architectures. Translate business needs into clear technical solutions and design patterns. Lead design discussions, code reviews, and solution planning with internal teams. Guide development teams by providing architectural direction and mentoring. Collaborate with DevOps for smooth deployment and CI/CD implementation. Participate in client meetings and technical solutioning discussions. Explore and propose the use of AI/ML capabilities where relevant, especially in areas like intelligent search, automation, and data insights Must-Have Skills & Qualifications 8–10 years of experience in software development and solution architecture. Hands-on expertise in either Python or C# .Net. Deep understanding of software architecture patterns—microservices, event-driven, layered designs. Experience with cloud platforms (AWS, Azure, or GCP). Solid knowledge of databases (SQL & NoSQL), APIs, and integration techniques. Exposure to or strong interest in AI/ML technologies—especially those involving intelligent automation or data-driven systems. Good interpersonal and communication skills; experience interfacing with clients. Capability to lead technical teams and ensure delivery quality. Preferred Skills Awareness of LLMs, vector databases (e.g., Pinecone, FAISS), or RAG-based systems is a plus. Familiarity with Docker, Kubernetes, or DevOps workflows. Knowledge of MLOps or experience working alongside data science teams. Certifications in cloud architecture or AI/ML are a bonus. Show more Show less