Backend AI Architect

Job Description

Core Back End Architecture

• 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 across multiple teams.

• 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 partnering with product, security, SRE, and data teams to translate business requirements into resilient technical solutions.

AI Driven & Intelligent Platform Skills

• 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.

Cloud, Integration & Platform Engineering

• 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

Roles & Responsibilities

Back End Architecture Leadership

• Architect and design enterprise scale backend platforms that are secure, highly available, performant, and cost efficient.

• 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.

AI Augmented Platform Architecture

• Define and implement AI augmented backend architectures, including inference aware service patterns and model serving strategies.

• Integrate LLMs and GenAI 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.

Developer Experience & Engineering Excellence

• 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.

Generic Managerial Skills, If any

• 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.

Key Words to search in Resume

• Back End Architect, Distributed Systems, Microservices, Event Driven Architecture, API Design, Cloud Native, AWS, DevEx, CI/CD, Observability, LLM, GenAI, RAG, AI Agents, Inference Architecture, Platform Engineering

Pre-Screening Questionnaire

• • Describe your experience designing and scaling backend platforms using microservices or event driven architectures.

• • How have you integrated LLMs or GenAI capabilities into enterprise backend systems?

• • Explain your experience with inference architecture (routing, caching, cost optimization).

• • Describe how you have improved developer experience, CI/CD quality, or platform reliability in past roles.

Required Skills: AI, LLM , Gen AI ,