Required Technical Skills
Generative AI & LLMs
- Strong understanding of:
- Large Language Models (LLMs)
- Prompt Engineering techniques
- Retrieval-Augmented Generation (RAG)
- AI Agents / Agentic AI workflows
- Fine-tuning concepts and model evaluation
Programming Skills
- Hands-on experience with:
- Python
- REST APIs
- JSON handling and API integrations
AI Frameworks & Tools
- Experience with:
- LangChain / LangGraph/LangSmith
- LlamaIndex
- Semantic Kernel
- Knowledge of Low Code Solution
Role Overview
We are seeking a highly skilled and innovative GenAI Engineer / Prompt Engineer with 3–6 years of experience in building AI-powered applications leveraging Large Language Models (LLMs), Generative AI frameworks, and prompt engineering techniques.
The ideal candidate should have hands-on experience in designing AI agents, optimizing prompts, integrating LLM APIs, and developing scalable AI solutions for enterprise use cases. The role involves collaborating with product, engineering, and business teams to create impactful AI-driven applications and workflows.
Key Responsibilities
- Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs).
- Create, test, and optimize prompts for accuracy, consistency, and performance.
- Build AI agents and multi-agent workflows for enterprise applications.
- Integrate LLM APIs such as OpenAI, Anthropic Claude, Gemini, or open-source models.
- Develop Retrieval-Augmented Generation (RAG) and Agentic AI solutions.
- Work on vector databases, embeddings, semantic search, and knowledge retrieval systems.
- Collaborate with data engineers and application teams for end-to-end AI solution integration.
- Evaluate model performance and improve outputs through prompt tuning and experimentation.
- Implement guardrails, security, and responsible AI practices.
- Build reusable AI workflows, templates, and accelerators.
- Stay updated with emerging trends in GenAI, LLMs, and AI frameworks.
Generative AI & LLMs
- Strong understanding of:
- Large Language Models (LLMs)
- Prompt Engineering techniques
- Retrieval-Augmented Generation (RAG)
- AI Agents / Agentic AI workflows
- Fine-tuning concepts and model evaluation
Programming Skills
- Hands-on experience with:
- Python
- REST APIs
- JSON handling and API integrations
AI Frameworks & Tools
- Experience with:
- LangChain / LangGraph/LangSmith
- LlamaIndex
- Semantic Kernel
- Knowledge of Low Code Solutions
Cloud & AI Platforms
- Exposure to:
- Azure OpenAI
- AWS Bedrock
- Google Vertex AI
- Databricks AI capabilities
Databases & Search
- Experience with:
- Vector databases (Pinecone, ChromaDB, FAISS, Weaviate)
- SQL / NoSQL databases
DevOps & Engineering Practices
- Knowledge of:
- Git and version control
- CI/CD pipelines
- Docker and containerization
- API deployment and monitoring
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
- Experience building enterprise AI copilots or conversational AI applications.
- Exposure to multi-modal AI solutions (text, image, audio).
- Understanding of AI governance, compliance, and responsible AI practices.
Experience working with healthcare, supply chain, financial domains is a plus.
Preferred Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- Experience working in enterprise-scale applications.
- Exposure to AI-enabled or data-driven applications.
