Generative AI Architect

Generative AI Architect (10 Years Experience)

Role Summary

We are looking for a seasoned Generative AI Architect with 10 years of experience to lead the design and deployment of enterprise-scale GenAI solutions. This role requires deep expertise in LLM ecosystems AI architecture and enterprise governance along with strong leadership capabilities to drive AI transformation initiatives in highly regulated environments (e.g. banking financial services).

The candidate will act as a technical authority and strategic advisor owning the AI architecture roadmap guiding engineering teams and ensuring secure scalable and compliant AI deployments.

Key Responsibilities

1. Enterprise AI Strategy & Architecture

• Define and own organization-wide GenAI architecture strategy and roadmap

• Design scalable modular and reusable GenAI platforms for enterprise adoption

• Lead architecture decisions across:

  • RAG pipelines

  • Fine-tuning strategies

  • Agentic AI frameworks

• Establish reference architectures best practices and design standards

2. Advanced Solution Design & Implementation

• Architect complex solutions involving:

  • Multi-agent systems

  • Conversational AI platforms

  • Knowledge assistants and copilots

• Drive implementation of:

  • RAG with hybrid retrieval (keyword semantic search)

  • Context-aware LLM pipelines with memory and tool usage

• Oversee integration with enterprise data ecosystems and legacy systems

3. Leadership & Technical Governance

• Provide technical leadership and mentorship to AI/ML engineers and architects

• Conduct architecture reviews design validations and code oversight

• Define and enforce:

  • GenAI guardrails

  • Secure prompt frameworks

  • Responsible AI practices

• Collaborate with risk compliance and security teams

4. Model Evaluation & Lifecycle Management

• Establish enterprise-grade LLM evaluation frameworks including:

  • Hallucination and grounding checks

  • Faithfulness relevance toxicity evaluation

  • Cost vs performance optimization

• Define model lifecycle processes:

  • Versioning monitoring retraining strategies

  • Continuous evaluation and improvement pipelines

5. Governance Risk & Compliance (Critical for 10 yrs role)

• Ensure alignment with:

  • Model Risk Management (MRM) frameworks

  • Data privacy laws and PII handling

• Lead implementation of:

  • Audit trails for AI decisions

  • Explainability frameworks

  • Bias detection and mitigation

• Drive secure-by-design AI architecture

6. Performance Scalability & Cost Optimization

• Architect high-performance systems with:

  • Low latency and high availability

  • Efficient token usage and caching strategies

• Optimize inference cost and throughput

• Design observability systems for LLM pipelines

7. Stakeholder Engagement & Business Alignment

• Interface with senior leadership and business stakeholders

• Translate business use cases into AI-driven solutions

• Lead AI transformation initiatives and PoCs to production scaling

Required Skills & Experience

Core Experience

• 10 years of overall experience in Software Engineering / Data Science / AI

• 3 5 years in AI/ML and at least 2 years in GenAI/LLMs

• Proven track record of delivering enterprise-scale AI solutions

Technical Expertise

• Strong proficiency in:

  • Python (mandatory)

  • System design and scalable architecture

• Deep experience with:

  • LLM frameworks: LangChain LlamaIndex Semantic Kernel

  • Prompt engineering and prompt optimization

  • RAG pipelines and embeddings

LLM & GenAI Expertise

• Hands-on experience with:

  • OpenAI / Azure OpenAI / Gemini / open-source LLMs

• Deep understanding of:

  • Transformer architectures

  • Fine-tuning (LoRA PEFT)

  • Vector search and similarity techniques

Cloud & Platform Expertise

• Strong experience with:

  • Azure AI (preferred) AWS Bedrock or GCP Vertex AI

• Experience in:

  • Kubernetes Docker

  • CI/CD MLOps pipelines

• Exposure to:

  • Event-driven architectures (Kafka Pub/Sub)

Data & Integration

• Experience with:

  • Vector databases: Pinecone FAISS Weaviate Azure AI Search

  • Data engineering pipelines (Spark Airflow)

• Integration with:

  • Enterprise APIs and microservices

Soft Skills & Leadership

• Strong architectural thinking and decision-making ability

• Excellent stakeholder management at senior/executive level

• Ability to:

  • Influence cross-functional teams

  • Drive consensus on complex technical decisions

• Mentorship and team development experience

Education

• Bachelors or Masters in Computer Science AI Data Science or related field

Nice to Have

• Experience in multimodal AI (text image speech)

• Knowledge of knowledge graphs

• AI governance certifications or cloud certifications

• Contributions to enterprise AI frameworks or open-source projects

Key Deliverables

• Enterprise GenAI architecture roadmap and standards

• Production-grade scalable AI systems

• Governance-compliant AI deployment frameworks

• Performance and evaluation dashboards

• Mentored and high-performing AI engineering teams