Senior Manager Technical Architect Hyderabad (India)

Education: Any graduates Candidate Expectations: 10+ years of software engineering experience, including significant experience in solution or technical architecture and AI/ML-enabled application delivery. Proven ability to design and govern complex, scalable, secure, and maintainable enterprise architectures. Demonstrated experience building and deploying LLM-powered applications, RAG solutions, AI agents, or multi-agent systems. Robust hands-on understanding of microservices, distributed systems, API design, integration patterns, and cloud-native engineering. Experience with at least one major cloud platform: AWS, Azure, or GCP, including relevant AI/ML, compute, storage, networking, security, monitoring, and deployment services. Proficiency in backend technologies such as Python with FastAPI, Flask, or Django; Node.js; or Java, plus working knowledge of contemporary frontend frameworks. Experience with SQL and NoSQL databases, vector databases or search platforms, data pipelines, and data lifecycle/security practices. Practical experience with containers, Kubernetes, CI/CD, infrastructure as code, MLOps/LLMOps, and production observability. Solid understanding of authentication, authorization, secrets management, OWASP principles, privacy, and non-functional requirement engineering. Excellent problem-solving, analytical, communication, collaboration, and technical leadership skills. Detailed Job Description: Own the end-to-end solution architecture across application, data, integration, AI/ML, security, and cloud infrastructure. Define and maintain high-level and low-level designs, reference architectures, reusable patterns, standards, and architecture decision records. Convert functional and non-functional requirements into architecture decisions covering security, performance, scalability, resilience, observability, availability, cost, and maintainability. Lead architecture reviews, design reviews, code reviews, and technical risk assessments; ensure traceability from requirements through implementation. Evaluate technologies and recommend fit-for-purpose choices for LLMs, agent frameworks, vector databases, API gateways, orchestration, and monitoring. .