Job Title: Generative AI Engineer

Company: United Techno

United Techno is seeking a Generative AI Engineer to join our innovative team. In this role, you will be responsible for designing, developing, deploying, and maintaining AI and Generative AI solutions using Python. You will work on building RAG applications, LLM-powered applications, AI agents, enterprise AI solutions, and AI-powered APIs.

You will work with LLMs, embeddings, vector databases, semantic search, prompt engineering, document processing, and AI frameworks such as LangChain, LangGraph, and Semantic Kernel. You will collaborate with cross-functional teams to understand requirements and translate them into practical, scalable AI solutions.

Key Responsibilities

- Design, develop, and deploy AI and Generative AI solutions using Python.
- Develop and maintain Retrieval-Augmented Generation (RAG) applications and pipelines.
- Work with LLMs, embeddings, vector databases, semantic search, and prompt engineering.
- Develop LLM-powered applications using frameworks such as LangChain, LangGraph, or equivalent frameworks.
- Build AI-powered APIs and backend services using Flask, FastAPI, or similar technologies.
- Work with structured and unstructured enterprise data for AI use cases.
- Implement document processing, data ingestion, chunking, retrieval, re-ranking, and contextual retrieval techniques.
- Integrate AI applications with enterprise systems, databases, APIs, and cloud platforms.
- Evaluate and continuously improve the quality, performance, scalability, and cost efficiency of AI applications.
- Implement monitoring, evaluation, and operational practices for AI/LLM applications.
- Participate in MLOps/LLMOps activities including deployment, monitoring, troubleshooting, and maintenance.
- Work on AI agents and agentic workflows where applicable.
- Collaborate with cross-functional teams to understand requirements and translate them into practical AI solutions.
- Troubleshoot production issues and enhance existing AI applications.
- Stay updated with emerging developments in Machine Learning, Generative AI, LLMs, RAG, and AI technologies.

Skills and Tools Required: Programming & Software Engineering

- Strong proficiency in Python.
- Experience developing applications and REST APIs using Flask, FastAPI, or similar frameworks.
- Good understanding of software development practices and API integration.
- Experience working with SQL and relational databases.
- Familiarity with Git and software development lifecycle practices.





Machine Learning

- Positive understanding of fundamental Machine Learning concepts and workflows.
- Experience working with data preprocessing, feature engineering, model development, and model evaluation.
- Familiarity with commonly used Machine Learning approaches for classification, regression, clustering, and predictive analytics.
- Ability to apply appropriate Machine Learning techniques to solve business problems.
- Experience with Python-based Machine Learning libraries such as scikit-learn, pandas, and NumPy.
- Understanding of basic model optimization and performance improvement techniques.

Generative AI & LLM

- Hands-on experience building applications using Large Language Models and Generative AI.
- Strong understanding of Retrieval-Augmented Generation (RAG).
- Experience with:
- Prompt engineering
- Embeddings
- Vector databases and vector search
- Semantic search
- Hybrid search
- Document processing and chunking
- Retrieval and re-ranking
- Context management

- Understanding of LLM parameters and response generation.
- Understanding of common LLM challenges such as hallucination, context limitations, and grounding.

AI Frameworks

- Experience with one or more LLM application frameworks such as:
- LangChain
- LangGraph
- Semantic Kernel
- Equivalent frameworks

- Familiarity with AI agents and agentic workflows.
- Familiarity with MCP (Model Context Protocol) is preferred.
- Experience with AI/LLM evaluation and observability tools is an advantage.

NLP & Deep Learning

- Basic understanding of NLP and Deep Learning concepts.
- Understanding of transformer-based architectures and attention mechanisms.
- Familiarity with encoder, decoder, and encoder-decoder architectures.
- Familiarity with transformer-based models such as BERT and LLMs.
- Understanding of fundamental neural network concepts.

Cloud & Data Platforms

- Experience with one or more cloud platforms such as Azure, AWS, or GCP.
- Experience with Databricks or similar AI/data platforms is preferred.
- Familiarity with Unity Catalog, vector search, or enterprise AI platforms is an advantage.




- Experience working with enterprise databases, data lakes, document repositories, or other data sources.

Model Fine-Tuning

- Understanding of LLM and language model adaptation techniques.
- Familiarity with LoRA, QLoRA, and PEFT is preferred.
- Experience with fine-tuning language models is an advantage.

Preferred Qualifications:
- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
- 2–4 years of experience in AI, Machine Learning, Data Science, Software Engineering, or Generative AI.
- Experience developing and deploying production-grade AI or Generative AI applications.
- Experience with Docker and CI/CD practices is preferred.
- Familiarity with cloud-based AI services and deployment practices.
- Understanding of AI security, responsible AI, data privacy, and LLM security is an advantage.

Key Competencies:
- Strong analytical and problem-solving skills.
- Strong Python and AI engineering capabilities.
- Ability to translate business requirements into scalable AI solutions.
- Ability to work independently as well as collaboratively.
- Strong debugging and troubleshooting skills.
- Good communication and documentation skills.
- Willingness to learn and adapt to rapidly evolving AI technologies.

Technology Stack: Programming: Python, SQL

Machine Learning: Scikit-learn, Pandas, NumPy

Generative AI: LLMs, RAG, Prompt Engineering, Embeddings, Vector Search, AI Agents

NLP / Deep Learning: Transformers, BERT, LLMs

Frameworks: LangChain, LangGraph, Semantic Kernel

Backend: Flask, FastAPI, REST APIs

Data: SQL, Vector Databases, Enterprise Data Sources

Cloud / Platforms: Azure, AWS, GCP, Databricks

AI Engineering: LLMOps, MLOps, Evaluation, Monitoring, Fine-Tuning, LoRA, QLoRA, PEFT

Development: Git, CI/CD, Docker

Preferred Certifications

- Relevant certifications in Artificial Intelligence, Machine Learning, or Generative AI are an advantage.
- Certifications such as NVIDIA Generative AI, Microsoft Azure AI, or equivalent industry-recognized AI certifications are preferred.
- Cloud certifications in Azure, AWS, or GCP are an added advantage.

Join United Techno and help us revolutionize the way businesses utilize AI and Generative AI technologies. If you are passionate about building practical AI solutions, developing intelligent applications, and pushing the boundaries of innovation, we would love to hear from you.

📌 Generative AI Engineer (Chennai)
🏢 United Techno Info Systems
📍 Chennai