AI Architect

Job description

Key Responsibilities

Personal Characteristics

1. Strong portfolio and excellent attitude
2. Self-confident to work independently and in teams
3. Good communication and articulation skills
4. Ability to work across different cultures and time zones
5. Delivery-oriented and able to work under strict deadlines

Core Responsibilities

1. Define technical architecture and solution blueprint for AI-powered agents, copilots, and intelligent automation solutions
2. Lead design of scalable, secure, and enterprise-grade AI solutions
3. Establish architecture principles, design standards, and technical guardrails
4. Architect end-to-end AI solutions involving LLMs, RAG, vector search, orchestration frameworks, APIs, and enterprise systems
5. Collaborate with product teams and stakeholders to translate business requirements into technical solutions

Detailed Responsibilities

1. Design AI agents for use cases like assistants, recommendation engines, copilots, workflow automation, and decision systems
2. Define solution patterns for prompt orchestration, memory, context, and observability
3. Architect retrieval and knowledge frameworks using enterprise data sources
4. Drive decisions on model strategy, vector storage, orchestration, and integrations
5. Review technical designs and guide engineering teams
6. Ensure AI solutions are secure, scalable, and production-ready
7. Define non-functional requirements (performance, security, cost, governance)
8. Guide AI engineering best practices and reusable frameworks
9. Evaluate new AI tools and contribute to AI roadmap

Mandatory Skills

1. Bachelor’s degree in relevant field
2. 10+ years in software engineering/architecture, with 3–5 years in AI/ML/GenAI
3. Strong experience in enterprise-scale and distributed systems
4. Strong programming skills in Python and backend systems
5. Hands-on experience with LLMs, GenAI, prompt engineering, embeddings, vector DB, RAG
6. Experience in AI assistants, copilots, chatbots, or agent-based systems
7. Strong knowledge of microservices and integration patterns
8. Understanding of AI evaluation, observability, and hallucination handling
9. Knowledge of enterprise security, privacy, and governance
10. Experience with AWS/Azure/GCP

Additional Skills

1. CI/CD, containerization, monitoring, and logging
2. Strong analytical and problem-solving skills
3. Good communication and stakeholder management
4. Agile environment experience

Desirable Skills

1. Experience in SaaS, enterprise platforms, or digital transformation
2. Familiarity with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, etc.
3. Exposure to Java, Spring Boot, Node.js, Kafka
4. Experience with vector stores, LLMOps, and AI observability tools
5. Knowledge of recommendation systems and analytics platforms
6. Understanding of Responsible AI and governance
7. Experience mentoring engineers and reviewing designs