GEN AI/Prompt engineer
At a glance
Mid-level AI Engineering role at Fa Ewjt Saasfaprod1. Noida · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Create and launch generative AI products powered by large language models
- Test and refine prompts to improve accuracy, consistency and performance
- Develop agent-based systems and coordinated workflows for enterprise use
- Build RAG solutions, using vector search, embeddings and knowledge retrieval
- Connect model APIs and coordinate with data engineers and application teams on integration
What you bring
- Three to six years developing applications with generative AI, large language models and prompt engineering
- Practical Python experience, including REST APIs, JSON and connecting APIs
- Experience with frameworks such as LangChain, LangGraph or another listed option
- Strong grasp of RAG, prompt design, AI agents and model evaluation
Who this fits
This mid-level role suits you if you want to develop and improve enterprise AI applications, from prompt testing to deployment. The job is based in Noida with a hybrid schedule.
From the employer
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.
AI Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
AI Engineering
Find me workBy the team behind aimlroles.