API Lead

Hi,

Hope you are doing well!

I’m Shikha Dixit, Lead Recruiter at Siri Info Solutions. I’ve been reviewing your background in [API, .Net, AI, Microservices, etc.], and your profile stands out as an excellent match for a “API Lead” opening I have in Alpharetta, GA. This is a high-priority, 5-day onsite role with one of our key clients. Given your experience, I’d love to discuss the details and see if this aligns with your career goals. Are you open to a quick 5-minute chat?

 

Role: API Lead

Duration: 6-12 months

Location: Irving, TX (5-day onsite)

 

Job Description: 

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

Define and implement API-first architecture strategy for AI and GenAI platforms

Establish API governance including versioning, security, authentication, throttling, and monitoring

Build reusable APIs for:

AI services (LLM integration, inference APIs)

Agent orchestration

Data and knowledge access layers

 

2. AI / LLM Architecture (Primary Focus)

Architect end-to-end GenAI solutions leveraging:

Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

Prompt engineering and orchestration frameworks

Design AI pipelines involving data ingestion, embedding generation, retrieval, and response generation

Define architecture standards for scalability, reliability, and performance optimization

 

3. Agentic AI & Intelligent Automation

Design and implement AI agent frameworks and multi-agent architectures

Build intelligent workflows for:

Task automation

Decision-making systems

Conversational and autonomous agents

Leverage frameworks such as LangChain, LlamaIndex, or similar orchestration tools

 

4. Integration & Microservices Architecture

Lead integration of AI capabilities with enterprise applications using APIs and microservices

Ensure seamless connectivity with:

Enterprise platforms (CRM, ERP, data platforms)

Backend services and digital ecosystems

Promote reusable, modular, and scalable design patterns

 

5. Governance, Security & Responsible AI

Define and enforce Responsible AI practices, data security, and compliance standards

Address key risks including:

Data privacy (PII/PHI handling)

Model hallucination and bias

Auditability and explainability

Implement monitoring frameworks for LLM performance and lifecycle management

 

6. Leadership & Stakeholder Collaboration

Lead architecture discussions, design reviews, and governance forums

Collaborate with business stakeholders, product owners, and engineering teams

Mentor technical teams on AI architecture, API strategy, and GenAI best practices

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