Job Title: Senior AI Native Engineer

We are looking for a Senior AI Native Engineer to build AI-powered products, own design and architecture decisions, and mentor teammates. You will combine robust backend engineering fundamentals with AI-assisted development and practical LLM integration to build secure, scalable, and reliable production systems.

Responsibilities

- Own development from architecture and system design through implementation, deployment, and production support.
- Build products from scratch and scale them as usage and business complexity grow.
- Design robust APIs, database models, microservices, and event-driven workflows.
- Build AI-powered capabilities using LLM APIs, retrieval-augmented generation (RAG), tool calling, and agentic workflows where they add product value.
- Use AI tools to accelerate coding, testing, debugging, and documentation while independently owning architectural decisions and validating generated code.
- Make architecture decisions balancing performance, scalability, consistency, security, maintainability, and cost.
- Build distributed systems with fault tolerance, reliable communication, and appropriate data consistency guarantees.
- Implement evaluations, guardrails, and fallback mechanisms to improve the reliability of AI features.
- Improve monitoring, logging, metrics, and alerting across backend services and AI workflows, including response quality, latency, and cost.
- Contribute to CI/CD pipelines, automated testing, containerized deployments, and cloud infrastructure.
- Mentor teammates through design discussions, code reviews, and hands-on technical guidance.
- Collaborate with product and engineering teams and take ownership of delivery and product outcomes.

Requirements

- Strong experience building and operating production backend systems.
- Experience in any backend programming language,



with strong engineering fundamentals and openness to working with Java/Golang. Prior Java/Golang experience is not mandatory.
- Solid understanding of design patterns, architectural principles, and system design.
- Hands-on experience with databases, data modeling, query optimization, and API development.
- Experience with event-driven architectures, asynchronous processing, and distributed systems.
- Strong understanding of consistency, concurrency, scalability, and failure handling.
- Practical experience using AI coding assistants, with the ability to explain, review, test, and debug the resulting code.
- Hands-on experience integrating LLM APIs into applications, including prompt design, structured outputs, and tool calling.
- Familiarity with RAG, agentic workflows, and evaluating AI outputs for correctness and reliability.
- Knowledge of application security, authentication, authorization, and secure data handling, including sensitive data used in AI workflows.
- Working knowledge of DevOps basics, including CI/CD, containers, and Kubernetes.
- Experience with cloud platforms, preferably Google Cloud; AWS experience is also acceptable.
- Ability to work independently, communicate technical decisions, and mentor teammates in a remote environment.

Preferred Background

- Startup experience building products from 0 to 1 and scaling them from 1 to 100.
- Experience owning architecture and delivering greenfield products.
- Experience shipping AI-powered features used in production, including managing quality, latency, and inference costs.
- Experience implementing safeguards against prompt injection, unreliable outputs, and unintended agent actions.
- Experience in anti-fraud, commercial banking, or growth engineering is a plus.
- Comfort working with ambiguity, taking ownership, and balancing delivery speed with engineering quality.

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📌 Ai Native Engineer (India)
🏢 Shuru
📍 India