API - AI Lead

Role Summary

• We are seeking a highly experienced API Lead with strong AI Architecture expertise to design and deliver next-generation GenAI platforms.
• This role will focus on building API-first AI ecosystems, enabling LLM-powered applications, agentic workflows, and intelligent automation at enterprise scale.
• The ideal candidate will lead the design of scalable AI architectures, integrate LLMs and AI agents with enterprise systems, and drive adoption of modern API frameworks for seamless interoperability across platforms.

Key Responsibilities

1. API Architecture & Platform Leadership

1. Define and implement API-first architecture strategy for AI and GenAI platforms
2. Establish API governance including versioning, security, authentication, throttling, and monitoring
3. Build reusable APIs for:
4. AI services (LLM integration, inference APIs)
5. Agent orchestration
6. Data and knowledge access layers

2. AI / LLM Architecture (Primary Focus)

1. Architect end-to-end GenAI solutions leveraging:
2. Large Language Models (LLMs)
3. Retrieval-Augmented Generation (RAG)
4. Prompt engineering and orchestration frameworks
5. Design AI pipelines involving data ingestion, embedding generation, retrieval, and response generation
6. Define architecture standards for scalability, reliability, and performance optimization

3. Agentic AI & Intelligent Automation

1. Design and implement AI agent frameworks and multi-agent architectures
2. Build intelligent workflows for:
3. Task automation
4. Decision-making systems
5. Conversational and autonomous agents
6. Leverage frameworks such as LangChain, LlamaIndex, or similar orchestration tools

4. Integration & Microservices Architecture

1. Lead integration of AI capabilities with enterprise applications using APIs and microservices
2. Ensure seamless connectivity with:
3. Enterprise platforms (CRM, ERP, data platforms)
4. Backend services and digital ecosystems
5. Promote reusable, modular, and scalable design patterns

5. Governance, Security & Responsible AI

1. Define and enforce Responsible AI practices, data security, and compliance standards
2. Address key risks including:
3. Data privacy (PII/PHI handling)
4. Model hallucination and bias
5. Auditability and explainability
6. Implement monitoring frameworks for LLM performance and lifecycle management

6. Leadership & Stakeholder Collaboration

1. Lead architecture discussions, design reviews, and governance forums
2. Collaborate with business stakeholders, product owners, and engineering teams
3. Mentor technical teams on AI architecture, API strategy, and GenAI best practices
4. Drive solutioning and contribute to client-facing discussions and proposals

Required Skills & Expertise

Core Technical Skills

• Strong experience as API Lead / Solution Architect / AI Architect
• Deep expertise in API design and management (REST, GraphQL, API Gateway)
• Strong understanding of microservices and distributed systems architecture
• Hands-on experience with GenAI, LLMs, and prompt engineering
• AI & GenAI Capabilities

Experience Designing Solutions Using:

• LLMs and GenAI platforms
• RAG pipelines and vector databases
• Knowledge of LLM orchestration frameworks and agent architectures
• Familiarity with LLMOps, monitoring, and performance optimization

Technology Stack:

• Programming: Python (preferred), Java / .NET (good to have)
• Cloud Platforms: Azure / AWS (AI services, scalable architecture)
• Tools & Frameworks:
• Docker, Kubernetes
• CI/CD pipelines
• API management tools

Good to Have

Experience with:

• Multi-agent systems and autonomous AI workflows
• Enterprise modernization or transformation programs
• Exposure to LLM cost optimization and routing strategies

Soft Skills:

• Strong stakeholder communication and client engagement skills
• Strategic thinking with a solution-oriented mindset
• Ability to translate business challenges into AI-driven solutions