Join our team as a Custom Software Engineer, where you will be instrumental in developing cutting-edge custom software solutions. You'll design, code, and enhance components across diverse systems and applications, utilizing modern frameworks and agile methodologies to deliver scalable, high-performing solutions precisely tailored to unique business requirements.

This role focuses on building enterprise-grade GenAI applications, sophisticated intelligent search capabilities, efficient Agentic AI workflows, and robust, scalable data processing pipelines. Expertise with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Vector Databases, and contemporary AI frameworks is essential for success in this dynamic position.

As a Custom Software Engineer, your primary responsibilities will include:

- Designing, developing, and maintaining advanced AI-powered applications leveraging Python. - Constructing enterprise GenAI solutions utilizing LLMs and intuitive Natural Language Interfaces. - Developing and optimizing RAG, Text-to-SQL, Semantic Search, and Agentic AI solutions. - Architecting and implementing scalable data ingestion and processing pipelines. - Seamlessly integrating AI models with existing enterprise applications and APIs. - Proactively monitoring, troubleshooting, and optimizing the performance of AI applications. - Contributing significantly to key architecture decisions and providing mentorship to team members.

To excel in this role, candidates should possess:

- A strong foundation in Python development with at least 2-5 years of experience. - A minimum of 2 years of hands-on experience in AI-GenAI-RAG and LLM application development. - Comprehensive knowledge of Python, OOPs principles, Design Patterns, and Unit Testing. - Proficiency with web frameworks such as FastAPI, Flask, or Django REST Framework. - Solid understanding of SQL, Data Modeling, and Shell Scripting. - Experience with data manipulation libraries like Pandas and NumPy. - Expertise in Authentication & Authorization (JWT-OAuth-SSO). - Proven ability in LLM Integration with platforms like OpenAI, Gemini, or Anthropic. - Hands-on experience with Vector Search, Semantic Search, and Agentic AI Workflows. - Skill in GenAI Tooling and Natural Language Interface Development. - Experience in RAG Pipeline Development & Optimization, and Text-to-SQL Systems. - Familiarity with libraries such as LangChain, LangGraph, and Sentence Transformers. - Experience with Hugging Face Transformers and Embedding Models. - Proficiency in utilizing Vector Databases (e.g., FAISS, Qdrant, Weaviate) and managing Embeddings and Vector Stores. - Experience with monitoring tools like Grafana. - Familiarity with Git and CI/CD practices. - 15 years of full-time education is required.