Gammastack - Python Developer - Artificial Intelligence/Machine Learning

GAMMASTACK; Indore District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

GAMMASTACK is seeking a Senior Python Engineer specialized in AI and ML to develop and deploy AI-powered applications. This role emphasizes strong Python skills and knowledge of AI frameworks including generative models and LLMs.

The ideal candidate should possess over 5 years of experience in Python development and have a solid understanding of AI technologies. You will work on innovative solutions using tools like AWS, Docker, and Kubernetes.

Qualifications

• 5+ years of strong hands-on Python development experience.
• Practical experience with Django, Django REST Framework, FastAPI, or Flask.
• Solid understanding of AI/ML, Generative AI, LLMs, embeddings, RAG, and semantic search.

Responsibilities

• Design and develop AI/ML and AI-powered applications using Python.
• Build and optimize RAG pipelines using LLMs.
• Implement prompt engineering and hallucination reduction techniques.

Skills

Python development

AI/ML

FastAPI

Django

Flask

Prompt engineering

RAG evaluation

LLM frameworks

REST API development

Docker

Kubernetes

CI/CD pipelines

Tools

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Hugging Face Transformers

FAISS

Pinecone

Chroma

Milvus

Redis

PostgreSQL

MySQL

MongoDB

Job description

Senior Python Engineer (AI, ML & Agentic AI)

Location: Indore

Experience: 5+ Years

About The Role

We're looking for a Senior AI/ML Engineer to design, build, and deploy production‑grade AI‑powered applications. The ideal candidate has strong Python engineering fundamentals combined with hands‑on expertise in AI/ML, Generative AI, LLM frameworks, RAG pipelines, and AI agent systems. This role is primarily AI/ML focused, with a strong emphasis on building scalable, secure, and well‑governed LLM‑based solutions.

Key Responsibilities

• Design and develop AI/ML and AI‑powered applications using Python, with FastAPI as the primary framework (Django and Flask also used)
• Build and optimize RAG (Retrieval‑Augmented Generation) pipelines using LLMs, embeddings, and vector databases
• Design and execute evaluation frameworks for single‑agent and multi‑agent systems to measure task completion, reasoning quality, tool usage, and workflow efficiency.
• Develop GenAI solutions using LangChain, LangGraph, LlamaIndex
• Build AI agents and multi‑agent workflows for business process automation
• Implement prompt engineering, retrieval evaluation, and hallucination reduction techniques
• Design and enforce LLM guardrails and governance frameworks (content filtering, output validation, safety policies, compliance, and audit logging)
• Build REST APIs and microservices to integrate AI/ML components with backend systems
• Deploy AI/ML services using AWS or GCP services, Docker, Kubernetes, and CI/CD pipelines
• Work with cloud AI platforms: AWS Bedrock, GCP Vertex AI, Azure OpenAI, or OpenAI APIs
• Monitor AI/ML model performance, cost, latency, and accuracy in production environments

Required Skills

• 5+ years of strong hands‑on Python development experience
• Practical experience with Django, Django REST Framework, FastAPI, or Flask
• Solid understanding of AI/ML, Generative AI, LLMs, embeddings, RAG, and semantic search
• Hands‑on experience with prompt engineering, RAG evaluation, re‑ranking, and hallucination handling
• Experience implementing LLM guardrails and governance frameworks (safety, compliance, monitoring, and risk controls for AI systems)
• Experience with LLM frameworks: LangChain, LangGraph, LlamaIndex
• Experience with ML/AI libraries: Pandas, NumPy, Scikit‑learn, PyTorch, TensorFlow, Hugging Face Transformers
• Experience with vector databases: Pinecone, FAISS, Chroma, Weaviate, Milvus, or pgvector
• Good knowledge of AWS Bedrock (model invocation, RAG, and integration with S3, Lambda, Glue, Athena, and OpenSearch)
• Strong understanding of REST API development, microservices architecture, and API security best practices
• Hands‑on experience with AWS or GCP services, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions/GitLab CI)
• Experience with relational and NoSQL databases: PostgreSQL, MySQL, MongoDB, or Redis