Role Overview:The Backend AI Architect will be responsible for architecting enterprise-scale backend platforms that are secure, highly available, performant, and cost-efficient. This role involves defining service architecture standards, integrating LLMs and Generative AI capabilities, and driving technical decisions that balance innovation with long-term platform health.
Key Responsibilities:- Architect and design enterprise-scale backend platforms focusing on security, high availability, performance, and cost efficiency.
- Define and govern service architecture standards, API contracts, and runtime patterns across development teams.
- Drive technical decisions that balance innovation, maintainability, operability, and long-term platform health.
- Mentor and guide engineering teams in implementing services, APIs, and shared platform capabilities.
- Define and implement AI augmented backend architectures, including inference-aware service patterns and model serving strategies.
- Integrate LLMs and Generative AI capabilities into customer-facing features and internal platforms.
- Establish spec-driven development workflows leveraging AI to improve developer productivity and quality.
- Partner with Data Science, ML Engineering, and Product teams to operationalize models with strong SLAs, security, and cost controls.
- Evaluate emerging AI frameworks and align solutions with enterprise standards and governance models.
- Champion Developer Experience (DevEx) by improving local development tooling, CI/CD quality gates, and test automation.
- Establish best practices for coding standards, secure development, performance optimization, and reliability engineering.
- Promote observability-first design using logs, metrics, traces, and AI assisted insights.
Required Skills:- Strong experience architecting scalable, secure, and observable distributed systems, including microservices and event-driven architectures.
- Proven expertise defining service architecture strategies, including APIs, data contracts, and runtime platforms.
- Deep understanding of system design fundamentals such as consistency models, caching strategies, resilience patterns, and fault tolerance.
- Hands-on experience with at least one major backend ecosystem: Node.js/TypeScript, Java/Kotlin, .NET, Python, or Go.
- Strong background in operational excellence, including observability, performance tuning, incident response, and reliability engineering.
- Experience integrating or developing with LLMs and Generative AI services within enterprise platforms.
- Strong understanding of prompt engineering, evaluation techniques, and AI quality metrics.
- Experience architecting inference systems, including routing, batching, caching, and cost optimization.
- Ability to design intelligent service flows, including Retrieval Augmented Generation (RAG) and agent-based architectures.
- Familiarity with AI safety, governance, and responsible AI principles.
- Experience developing AI powered platform components, such as intelligent API gateways, policy engines, or observability assistants.
- Knowledge of AI driven analytics and telemetry for monitoring model performance and service health.
- Experience with cloud platforms (AWS preferred; Azure/GCP acceptable).
- Strong understanding of API gateways, service mesh, and networking fundamentals.
- Hands-on experience with data and streaming technologies such as SQL, NoSQL, Kafka, and Redis.
- Experience with CI/CD pipelines, infrastructure as code, automated testing, and progressive delivery strategies.
- Solid grounding in security fundamentals, including threat modeling, identity, encryption, and secure by default design patterns.
- Solution and Functional Architect (SAFA) skills.
- Experience with Angular 2, Spring Boot, and MySQL.
Qualifications:- 10+ years of experience.
- Strong stakeholder management with the ability to communicate effectively at executive, product, and engineering levels.
- Proven experience leading large, matrixed, multi-vendor teams.
- Ability to balance strategic vision with hands-on architectural depth.
