: Gen AI Engineer Location: On-site (Chandigarh) Role Type: Full-Time Experience: 3–4 Years

Position Overview We are seeking a skilled and creative Generative AI Engineer to design, develop, and deploy advanced generative AI applications, including Retrieval-Augmented Generation (RAG) and agentic AI systems. The ideal candidate will have strong Python programming skills, in-depth knowledge of Large Language Models (LLMs), and hands-on experience with modern AI frameworks, agent orchestration, and commercial and open-source AI ecosystems.

Key Responsibilities

- Design, develop, and deploy generative AI applications using LangChain, LlamaIndex, LangGraph, and other relevant frameworks.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Research and stay updated on advancements in generative AI, LLMs, AI agents, agentic architectures, and emerging AI standards and protocols.
- Evaluate and experiment with commercial and open-source LLMs to identify the best solutions for specific use cases.
- Integrate AI functionality into existing and new applications.
- Build and enhance chatbots, RAG solutions, AI agents, and agentic workflows using tool/function calling, workflow orchestration, state management, memory, and external API integrations.
- Build and integrate Model Context Protocol (MCP) servers, clients, tools, and connectors to enable standardized access to external systems and data sources.
- Apply prompt engineering and context engineering techniques to improve AI model performance, accuracy, and reliability.
- Implement embeddings and vector databases to enhance generative AI applications.
- Test and evaluate AI applications for accuracy, reliability, hallucinations, and failure handling.
- Implement guardrails and appropriate controls to ensure safe, predictable, and controlled model and agent behavior.




- Troubleshoot and resolve issues related to AI models and applications.
- Develop and maintain comprehensive technical documentation for AI models and applications.

Required Skills & Qualifications

- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 3–4 years of relevant experience in AI engineering, generative AI, or related development roles.
- Proven experience developing AI applications using LangChain, LlamaIndex, LangGraph, or equivalent frameworks.
- In-depth knowledge of LLMs, including commercial and open-source model families such as OpenAI GPT, Google Gemini, and Anthropic Claude.
- Hands-on experience building chatbots, RAG applications, AI agents, and agentic workflows.
- Working knowledge of Model Context Protocol (MCP), including building or consuming MCP servers, clients, and tools.
- Experience with tool/function calling, orchestration, state/memory management, and external API/service integration.
- Experience testing and evaluating generative AI applications for accuracy, reliability, and predictable behavior.
- Knowledge of guardrails, hallucination mitigation, and safe AI application development.
- Understanding of embeddings, vector databases, prompt engineering, and context engineering.
- Strong problem-solving skills and the ability to work in a rapid-paced, collaborative environment.
- Excellent written and verbal communication skills.

Technical Skills

- Programming: Advanced Python programming.
- AI/ML Frameworks:



LangChain, LlamaIndex, LangGraph, TensorFlow, PyTorch, and Hugging Face.
- Large Language Models: OpenAI GPT, Google Gemini, Anthropic Claude, and equivalent open-source models.
- Generative AI: Retrieval-Augmented Generation (RAG), chatbots, AI agents, agentic workflows, prompt engineering, and context engineering.
- Agent Development: Tool/function calling, workflow orchestration, state management, memory, and external API integrations.
- MCP: Model Context Protocol servers, clients, tools, and connectors.
- Vector Search: Embeddings, vector databases, semantic search, and retrieval optimization.
- Cloud Platforms: AWS, GCP, and Azure, including AI-related services such as Amazon Bedrock and Azure AI Search.
- AI Evaluation & Observability: Testing, tracing, monitoring, reliability evaluation, hallucination detection, and failure handling.
- AI Safety: Guardrails, controlled tool use, agent action controls, and secure AI application development.

Soft Skills

- Excellent analytical and problem-solving abilities.
- Strong written and verbal communication skills.
- Ability to collaborate effectively with cross-functional teams.
- Adaptability to rapidly evolving AI technologies and frameworks.
- Strong research, troubleshooting, and critical-thinking skills.
- Ability to work independently and manage multiple technical challenges.
- Attention to detail and commitment to building reliable, high-quality AI solutions.

Preferred Qualifications

- Understanding of ethical considerations, security, and best practices in modern AI and agentic application development.
- Experience with containerization technologies such as Docker and Kubernetes.
- Understanding of LLM hallucinations and techniques to mitigate them.
- Familiarity with AI application tracing, observability, and performance monitoring.

📌 Gen AI Engineer (Chandigarh)
🏢 BizTecno
📍 Chandigarh