Job Description :

We are looking for an experienced AI Architect with 8 - 10 years of software engineering experience, including strong hands-on experience designing and architecting production-grade AI and GenAI solutions.

The ideal candidate will have worked across multiple systems and technology stacks, with a proven ability to define architecture, guide senior engineers, and deliver scalable AI solutions used by real users.

Key Responsibilities :

- Define and drive the architecture for enterprise-scale AI, Generative AI, and agentic AI solutions across multiple systems and applications.

- Design scalable architectures for LLM-based applications, including retrieval, orchestration, agent runtimes, and AI-powered workflows.

- Translate business and product requirements into robust technical architectures, technology choices, and implementation roadmaps.

- Work hands-on with multiple technology stacks and contribute to critical components, prototypes, and production implementations.

- Design and implement solutions involving LLMs, RAG, vector databases, prompt engineering, model integration, and AI agents.

- Establish architectural standards and best practices for scalability, reliability, security, performance, and maintainability.

- Evaluate emerging AI technologies, models, frameworks, and cloud services and assess their suitability for production use.

- Provide technical leadership to senior engineers and influence architecture decisions across teams without relying on formal people-management authority.

- Collaborate with engineering, product, data, security, and business teams to drive end-to-end delivery of AI solutions.

- Design AI systems with appropriate monitoring, evaluation, observability, security, governance, and cost controls.

- Troubleshoot complex technical and architectural issues across distributed AI and software systems.

- Drive proof-of-concepts and transition successful AI solutions into production environments.

Required Skills & Experience :

- 8 - 11 years of experience in software engineering, with significant experience in solution/technical architecture across multiple systems.

- Strong hands-on software development experience with at least two relevant technology stacks such as Python, Java, JavaScript/TypeScript, or similar.

- Proven production experience designing and deploying LLM-based or agentic AI applications used by real users.

- Strong understanding of Generative AI concepts including LLMs, RAG, embeddings, vector databases, prompt engineering, model orchestration, and AI agents.

- Experience with agentic architectures, agent runtimes, workflow orchestration, and multi-step AI systems.

- Strong experience with at least one major cloud platformAWS, Azure, or GCPand hands-on exposure to cloud-based AI/ML services.

- Experience designing distributed, scalable, and highly available software systems.

- Strong understanding of APIs, microservices, event-driven architectures, databases, and cloud-native application development.

- Experience with AI/ML frameworks and tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.

- Experience with AI evaluation, observability, security, and performance optimization for production AI systems.

- Strong technical leadership skills with the ability to influence senior engineers and drive architecture decisions across teams.

Good to Have :

- Experience with multi-agent systems and autonomous AI workflows.

- Experience with Azure OpenAI, AWS Bedrock, Amazon SageMaker, Google Vertex AI, or equivalent platforms.

- Experience with Kubernetes, Docker, and CI/CD for AI application deployment.

- Knowledge of AI governance, responsible AI, data privacy, and enterprise security requirements.

- Experience with vector databases such as Pinecone, Weaviate, Milvus, pgvector, or equivalent.

- Experience designing AI platforms or reusable enterprise AI capabilities.

- Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related discipline.