We are looking for an experienced

GenAI Engineer with strong hands-on expertise in designing, developing, and deploying end-to-end Generative AI solutions

. The candidate will be responsible for taking GenAI use cases from problem understanding and solution design through development, integration, testing, deployment, and production support

.

Key Responsibilities

- Design and develop end-to-end

Generative AI and LLM-based applications

.

- Understand business requirements and translate them into practical GenAI solutions.

- Build and implement

RAG pipelines

, knowledge-based applications, and semantic search solutions.

- Develop

AI agents and agentic workflows using LLMs, tools, APIs, and enterprise systems.

- Implement prompt engineering, function/tool calling, structured outputs, memory, and context management.

- Integrate GenAI applications with

REST APIs, databases, third-party services, and enterprise applications

.

- Work with structured and unstructured data, documents, and enterprise knowledge bases.

- Evaluate and improve LLM applications for accuracy, relevance, latency, reliability, and hallucination

.

- Optimize prompts, retrieval pipelines, model selection, and overall application performance.

- Develop scalable and production-ready GenAI applications.

- Deploy, monitor, troubleshoot, and maintain GenAI solutions in production.

- Collaborate with business, product, and engineering teams to identify and implement new GenAI use cases.

Required Technical Skills

- Strong hands-on experience with

Generative AI and Large Language Models (LLMs)

.

- Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar LLM platforms.

- Robust knowledge of

RAG, embeddings, vector databases, semantic search,



and retrieval pipelines

.

- Experience building

AI agents / Agentic AI applications

.

- Experience with

LangChain, LangGraph, or equivalent frameworks

.

- Strong

Python programming skills.

- Experience with REST APIs, JSON, webhooks, SQL, and database integrations.

- Knowledge of prompt engineering, function calling, tool calling, and structured outputs.

- Experience with LLM evaluation and optimization.

- Strong software engineering, debugging, and problem-solving skills.

- Experience with Git/GitHub and production development practices.

Cloud & Deployment

- Experience with

AWS, Azure, or GCP

.

- Docker and containerization.

- API/application deployment.

- CI/CD fundamentals.

- Monitoring and observability for production applications.

Preferred Skills

- Multi-agent systems

- MCP and tool-based AI systems

- AI-powered business process automation

- Document AI / OCR

- Conversational AI / Voice AI

- Fine-tuning or model adaptation

- Enterprise GenAI implementations

- SAP, Salesforce, ServiceNow, CRM, or other enterprise integrations

- Kubernetes / cloud-native deployments

Candidate Profile

- 3–5 years of relevant software, AI, or GenAI engineering experience

.

- Strong hands-on experience building real-world GenAI applications

, not just POCs or prompt-based solutions.

- Ability to independently own the complete GenAI lifecycle:

Business Problem → Solution Architecture → LLM/RAG/Agent Design → Development → Integration → Evaluation → Deployment → Production

- Strong ability to learn and work with rapidly evolving GenAI technologies.

- Candidates with demonstrated experience in building and deploying production GenAI solutions will be preferred.

📌 GenAI Engineer (Hyderabad)
🏢 Lorvenk Technologies
📍 Hyderabad