System Integration Specialist - Gen AI / LLM

6 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Senior Systems Integrator Lead


About the Role :

We're seeking an experienced Senior Systems Integrator Lead to spearhead the integration of our cutting-edge LLM solutions with diverse enterprise systems. This is a technical leadership role where you'll be hands-on in architecting, building, and deploying complex integration solutions while providing guidance and mentorship to a team of engineers. You'll be at the forefront of connecting disparate systems, orchestrating seamless LLM integrations, and establishing best practices for AI-driven system architecture.

The ideal candidate combines deep technical expertise in systems integration with proven leadership capabilities and extensive experience in LLM/Generative AI implementations.


Key Responsibilities :

Technical Leadership & Team Guidance

Lead Integration Architecture: Design and oversee complex, multi-system integration strategies that seamlessly connect LLM solutions with existing enterprise infrastructure

Team Technical Guidance: Mentor and guide development teams on integration best practices, code architecture patterns, and LLM implementation strategies

Hands-on Development: Remain technically hands-on, writing code, conducting code reviews, and troubleshooting complex integration challenges

Standards & Best Practices: Establish and enforce integration standards, development workflows, and quality assurance processes


LLM & AI Integration Expertise:

Advanced LLM Integration: Design and implement sophisticated integration patterns for various LLM providers (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, etc.)

AI Pipeline Architecture: Build robust, scalable pipelines for prompt engineering, response processing, and model orchestration

Performance Optimization: Optimize LLM integration performance including token management, caching strategies, and response time optimization

Multi-modal AI Integration: Integrate text, image, and other AI modalities into existing business workflows


Systems Integration & Architecture:

Enterprise Integration Patterns: Implement complex integration solutions using APIs, message queues, ETL/ELT pipelines, and event-driven architectures

Microservices Architecture: Design and maintain microservices-based integration layers with proper service mesh, API gateway, and monitoring implementations

Cloud-Native Solutions: Architect cloud-native integration solutions leveraging containers, serverless functions, and managed services

Data Flow Management: Ensure secure, efficient data flow between systems while maintaining data integrity and compliance requirements


Full-Stack Development & UI Integration:

React.js Applications: Build sophisticated front-end applications using React.js that interface with LLM backends and integrated enterprise systems

API Development: Design and implement RESTful and GraphQL APIs that serve as integration points between systems

Real-time Features: Implement real-time capabilities for AI interactions using WebSockets, Server-Sent Events, or similar technologies


Collaboration & Communication:

Cross-functional Leadership: Work with product managers, data scientists, DevOps teams, and business stakeholders to translate requirements into technical solutions

Technical Documentation: Create comprehensive architecture documentation, integration guides, and system design specifications

Knowledge Sharing: Conduct technical sessions, workshops, and knowledge transfer meetings with team members and stakeholders


Key Experiences


Experience & Leadership:

6-8+ years of systems integration experience with 2+ years in technical leadership roles

Proven team leadership experience including mentoring junior developers and leading technical initiatives

3+ years hands-on experience with LLM integration, Generative AI implementations, and AI/ML pipeline development


Technical Skills:

LLM Integration Expertise: Deep experience with major LLM providers' APIs, prompt engineering, fine-tuning, and deployment strategies

Integration Technologies: Advanced knowledge of REST/GraphQL APIs, message brokers (Kafka, RabbitMQ), ETL tools, and integration platforms

Cloud Platforms: Proficiency with AWS, Azure, or GCP, including serverless architectures, container orchestration, and managed AI services

React.js Mastery: Strong expertise in React.js, modern JavaScript (ES6+), TypeScript, and state management libraries

Database Integration: Experience with both SQL and NoSQL databases, data modeling, and database integration patterns

DevOps & Monitoring: Knowledge of CI/CD pipelines, containerization (Docker/Kubernetes), and observability tools


Architecture & Design

Software Architecture: Strong understanding of microservices, event-driven architectures, and distributed system design patterns

Security & Compliance: Knowledge of API security, data encryption, and compliance frameworks (SOC2, GDPR, etc.)

Performance Engineering: Experience in system performance optimization, load balancing, and scalability planning


Soft Skills

Technical Communication: Excellent ability to communicate complex technical concepts to both technical and business stakeholders

Problem-Solving: Strong analytical and troubleshooting skills with a solutions-oriented mindset

Adaptability: Comfortable working in fast-paced environments with evolving requirements and emerging technologies


Preferred Experience

Experience with vector databases and semantic search implementations

Knowledge of prompt engineering frameworks and AI agent architectures

Background in enterprise software integration (SAP, Salesforce, ServiceNow, etc.)

Experience with infrastructure-as-code (Terraform, CloudFormation)

Previous experience in AI/ML product development or consulting


What You'll Bring to the Team

Technical expertise that can tackle the most complex integration challenges

Leadership skills to guide and grow a high-performing engineering team

Strategic thinking to align technical solutions with business objectives

Hands-on mentality with the ability to dive deep into code when needed

Innovation mindset to explore and implement cutting-edge AI integration patterns

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