AIML Engineer

Prophecy Technologies Corp; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Prophecy Technologies Corp in Hyderabad is seeking a Senior AI/ML Engineer to build, deploy, and optimize LLM-based applications. You will work with Python, FastAPI/Flask, and vector search technologies to deliver enterprise-grade AI solutions.

You will collaborate with data scientists and solution architects to design scalable workflows, RAG pipelines, and microservices, with emphasis on production-readiness and maintainable code.

Qualifications

• Strong Python expertise with hands-on AI/ML experience.
• Hands-on with LLM frameworks and vector databases.
• Experience building scalable AI solutions for enterprise use cases.
• Familiarity with RAG pipelines and prompt engineering.

Responsibilities

• Design, develop, and deploy end-to-end LLM-based apps and agents.
• Build prompt strategies, evaluation workflows, and structured prompting.
• Implement RAG systems using Pinecone, FAISS, or ChromaDB.
• Fine-tune and optimize models for latency and accuracy.
• Develop ML models for NLP and document processing.
• Integrate workflows via microservices, APIs, and automation.

Skills

Python proficiency

LLM frameworks

LangChain/LlamaIndex/HuggingFace

RAG pipelines

Vector search

API integrations

Model optimization

NLP/ML basics

Data preprocessing

CI/CD

Education

Bachelor’s or Master’s degree in CS/AI/DS

Tools

Docker

Kubernetes

FastAPI/Flask

Git

Job description

Role Type

Full-time

Work Mode

ONSITE

Experience

3+ Years

Description

About the Role

We are looking for a skilled Senior AI/ML Engineer with hands-on experience in building, deploying, and

optimizing AI/ML and LLM-based applications. The ideal candidate should have strong Python expertise,

experience with LLM frameworks, and the ability to design scalable AI solutions for enterprise use

cases. You will collaborate with cross-functional teams to build agentic AI workflows, RAG pipelines,

vector search systems, and production-grade AI applications.

Key Responsibilities

• Design, develop, and deploy end-to-end LLM-based applications, conversational agents, and
• Build prompt engineering strategies, evaluation workflows, and structured prompting for
• Implement RAG (Retrieval Augmented Generation) systems using vector databases such as Pinecone, FAISS, or ChromaDB.
• Fine-tune, evaluate, and optimize models (open-source or API-based LLMs).
• Build and deploy ML models for classification, NLP, prediction, and document processing.
• Work on data preprocessing, feature engineering, and model optimization.
• Integrate ML/LLM workflows using microservices, APIs, webhooks, and automation pipelines.

Architecture & Integrations

• Work with Python frameworks (FastAPI/Flask) to build scalable model-serving endpoints.
• Integrate AI systems with enterprise platforms, databases, and internal applications.
• Contribute to architecture decisions for LLM apps, agentic systems, and AI microservices.
• Collaborate with data scientists, product owners, and solution architects to deliver AI-powered features.
• Review code, mentor junior engineers, and set technical standards for AI development.
• Prepare documentation, reusable components, and best practices for AI implementation.

Required Skills

Core Skills

• Strong proficiency in Python (Pandas, NumPy, FastAPI/Flask, Async programming preferred).
• Hands-on experience with LLMs (OpenAI, Llama, Mistral, Claude, Qwen, etc.).
• Experience with LangChain, LlamaIndex, or Hugging Face.
• Strong understanding of RAG pipelines, embeddings, and vector search.
• Practical experience with vector databases: Pinecone, FAISS, Weaviate, or ChromaDB.
• Knowledge of REST APIs, JSON integrations, token-based authentication.
• Experience with Git, Docker, CI/CD workflows.

ML & Data Skills

• Experience with NLP, classical ML, text preprocessing, and supervised learning.
• Ability to evaluate model performance and optimize latency & accuracy.
• Understanding of data pipelines and ETL workflows.
• Experience with at least one cloud platform (AWS/Azure/GCP).
• Familiarity with Kubernetes, model deployment, or container orchestration (nice to have).

Nice-to-Have Skills

• Experience with agentic AI frameworks (AutoGen, CrewAI, LangGraph, Swarm, etc.).
• Exposure to MLOps tools (MLflow, Airflow, Weights & Biases).
• Knowledge of front-end AI app integration (Streamlit, Gradio, or React).
• Understanding of AI security, governance, and responsible AI principles.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field.
• 2–5 years of hands-on experience in AI/ML or LLM engineering.
• Previous project or product development experience in NLP/LLM highly preferred