Job Purpose

As an AI Full Stack Software Engineer at Cendyn, you will design, build, and deploy intelligent features that transform our hospitality technology products. You will own the complete implementation lifecycle—from infrastructure and data pipelines through backend AI integration to responsive user interfaces—delivering production-ready AI capabilities that create measurable value for our customers.

Working across our polyglot technology stack (.NET, Node.js, Python), you will integrate large language models, implement retrieval-augmented generation (RAG) systems, and build scalable AI-powered APIs. As part of our AI Power Team initiative, you will operate with significant autonomy, driving AI adoption across Cendyn's product portfolio while establishing best practices for enterprise AI development in the hospitality technology space. - Job Responsibilities

AI Feature Development & Integration

- Design and implement end-to-end AI features using LLMs (OpenAI, Anthropic, Azure OpenAI) integrated into existing Cendyn products across hospitality workflows
- Build andoptimizeRAG (Retrieval-Augmented Generation) systems using vector databases (Pinecone,Weaviate,pgvector) to ground AI responses inCendyn'sproprietary data
- Develop prompt engineering strategies and implement systematic evaluation frameworks to ensure AI output quality, reliability, and business alignment
- Create intelligent APIs and microservices that expose AI capabilities to internal teams and external integrations, implementing proper rate limiting, error handling, and monitoring

Full Stack Development

- Build responsive user interfaces using modern frameworks (React, Vue.js, Angular) that surface AI capabilities through intuitive, performant experiences
- Develop backend services across our technology stack (.NET/C#, Node.js, Python)



implementing business logic, data processing, and AI orchestration workflows
- Design andmaintaindata pipelines that prepare, transform, and serve data to AI systems, ensuring data quality and system reliability

Infrastructure & DevOps

- Stand up and configure cloud infrastructure (AWS, Azure, GCP) for AI workloads including compute, storage, networking, and security components
- Monitor system performance,identifybottlenecks in AI inference pipelines, andoptimizefor latency, throughput, and cost efficiency
- Establish observability practices for AI systems including logging, metrics, tracing, and alerting to ensure production reliability

Technical Leadership & Collaboration

- Operate independently on AI initiatives with mínimal guidance, owning projects from concept through deployment and ongoing operational support
- Collaborate with product managers, designers, and stakeholders to translate business requirements into technical AI solutions and realistic implementation plans
- Contribute to the AI Power Team initiative byestablishingbest practices, documenting patterns, and mentoring team members on AI integration techniques
- Conduct code reviews,participatein architectural discussions, and drive continuous improvement of development processes and technical standards
- Stay current with AI/ML technologies, frameworks, and industry trends,



evaluating new tools and approaches for applicability toCendyn'sproducts - Required Qualifications

Education & Experience

- Bachelor's degree in Computer Science, Software Engineering, or related technical field (or equivalent practical experience)
- 3+ years of professional software development experience with production systems
- Demonstrated ability to work independently on complex technical projects with mínimal oversight

Technical Skills

Programming & Development

- Strongproficiencyin at least two of: Python, JavaScript/TypeScript, C#/.NET with ability to work across the stack
- Experience with modern frontend frameworks (React, Vue.js, Angular) building responsive, performant user interfaces
- Backend developmentexpertiseincluding RESTful API design, microservices architecture, and database operations (SQL and NoSQL)
- Solid understanding of software engineering fundamentals: data structures, algorithms, design patterns, testing methodologies

AI & Machine Learning

- Practical experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI) including prompt engineering and output evaluation
- Understanding of RAG architectures and experience with vector databases (Pinecone,Weaviate, Chroma,pgvector)

DevOps & Infrastructure

- Working knowledge of containerization (Docker) and orchestration (Kubernetes) for deploying scalable services
- Understanding of CI/CD pipelines, automated testing, and deployment automation practices
- Ability toidentifyperformance bottlenecks in distributed systems and implement optimization strategies
- Basic understanding of system monitoring, logging, and observability tools (CloudWatch,DataDog, New Relic, or similar)

Qualified Competencies

- Strong problem-solving skills with systematic approach to debugging com

📌 Software Engineer - Ai (Hyderabad)
🏢 Cendyn
📍 Hyderabad