AI/ML Engineer

EAGLENET, LLC; Telangana; Presencial; INR 1.200.000 - 2.400.000; Jornada completa

Descripción de la vacante

EAGLENET, LLC is seeking an AI/ML Engineer in Telangana to design and deploy scalable AI solutions. You will work on Python-based pipelines, RAG architectures, and LLM-powered applications, collaborating with cross‑functional teams.

The role emphasizes building MCP servers, Databricks workflows, and production‑grade APIs using FastAPI or Django, with a focus on reliability and performance.

Formación

• 2–3 years of hands-on Python development experience.
• Experience with Generative AI and LLMs.
• Practical knowledge of RAG pipelines and embeddings.
• Experience building MCP servers and tools.
• Experience with Databricks Workflows or Apache Airflow.
• Experience building ETL/ML pipelines with PySpark and Delta Lake.
• Experience developing production-ready Python APIs with FastAPI or Django.
• Familiarity with LangChain, LlamaIndex, or LangGraph.
• Experience with vector databases (pgvector, FAISS, Qdrant) and AWS.

Responsabilidades

• Design, develop, and maintain RAG pipelines, including document chunking, embeddings, vector search, and re‑ranking.
• Build MCP (Model Context Protocol) servers and tools to connect internal APIs, services, and data sources with LLM‑powered agents.
• Design, develop, and schedule DAG‑based workflows using Databricks Workflows and/or Apache Airflow.
• Build and maintain scalable ETL and machine learning pipelines using PySpark, Delta Lake, and MLflow.
• Develop production‑ready Python APIs and backend services using FastAPI or Django.
• Write unit tests, integration tests, and maintain high‑quality, reusable, and maintainable code.
• Implement LLM evaluation frameworks, guardrails, and monitoring for model performance, cost, and latency.
• Collaborate with cross‑functional teams to integrate AI/ML solutions into existing business applications.
• Troubleshoot, optimize the performance, scalability, and reliability of AI/ML applications.

Conocimientos

Python development

REST API development

AI/ML fundamentals

RAG knowledge

MCP understanding

Databricks & Spark

Distributed data pipelines

Educación

B.Tech / B.E.

Herramientas

FastAPI

Django

PyTorch

TensorFlow

scikit-learn

LangChain

LlamaIndex

LangGraph

Databricks

PySpark

Delta Lake

MLflow

Airflow

Git

Docker

PostgreSQL

pgvector

FAISS

Qdrant

AWS

Descripción del empleo

Job Description: AI/ML Engineer

• Experience: 2–3 Years
• Employment Type: Full-Time
• Department: Engineering / Artificial Intelligence & Machine Learning

About the Role

We are looking for a talented and motivated AI/ML Engineer with 2–3 years of hands‑on experience in Python development, Generative AI, Large Language Models (LLMs), and machine learning.

The ideal candidate will have practical experience building Retrieval‑Augmented Generation (RAG) pipelines, developing Model Context Protocol (MCP) servers and tools, implementing data engineering workflows, and deploying scalable AI/ML solutions in production environments.

You will work on developing intelligent applications, integrating LLMs with enterprise APIs and data sources, and building reliable, scalable AI‑powered systems.

Key Responsibilities

• Design, develop, and maintain RAG pipelines, including document chunking, embeddings, vector search, and re‑ranking.
• Build MCP (Model Context Protocol) servers and tools to connect internal APIs, services, and data sources with LLM‑powered agents.
• Design, develop, and schedule DAG‑based workflows using Databricks Workflows and/or Apache Airflow.
• Build and maintain scalable ETL and machine learning pipelines using PySpark, Delta Lake, and MLflow.
• Develop production‑ready Python APIs and backend services using FastAPI or Django.
• Write unit tests, integration tests, and maintain high‑quality, reusable, and maintainable code.
• Implement LLM evaluation frameworks, guardrails, and monitoring for model performance, cost, and latency.
• Collaborate with cross‑functional teams to integrate AI/ML solutions into existing business applications.
• Troubleshoot, optimize, and continuously improve the performance, scalability, and reliability of AI/ML applications.

Required Technical Skills

1. Programming & Backend Development

• Strong proficiency in Python with at least 2 years of production‑level development experience.
• Experience building REST APIs using FastAPI or Django.
• Knowledge of software engineering best practices, testing, and debugging.

2. Artificial Intelligence & Machine Learning

• Strong understanding of AI/ML fundamentals.
• Hands‑on experience with scikit‑learn, PyTorch, or TensorFlow.
• Practical knowledge of Large Language Models (LLMs) and Generative AI applications.

3. RAG & LLM Frameworks

• Experience developing RAG‑based applications.
• Familiarity with LangChain, LlamaIndex, or LangGraph.
• Understanding of embeddings, vector databases, semantic search, chunking strategies, and re‑ranking techniques.

4. Model Context Protocol (MCP)

• Understanding and hands‑on experience with MCP.
• Ability to build MCP servers and tools for integrating APIs and external services with LLM agents.

5. Data Engineering & Databricks

• Hands‑on experience with Databricks, PySpark, and Delta Lake.
• Experience building ETL and ML pipelines.
• Familiarity with MLflow for machine learning lifecycle management.

6. Workflow Orchestration

• Experience designing and managing DAG‑based workflows.
• Hands‑on experience with Databricks Workflows or Apache Airflow.

7. Databases & Cloud Technologies

• Strong SQL knowledge and experience with PostgreSQL.
• Familiarity with vector databases such as pgvector, FAISS, Qdrant, or similar technologies.
• Experience with AWS cloud services.

8. Development & Deployment Tools

• Proficiency with Git and version control.
• Experience with Docker and containerized applications.
• Understanding of REST API integration and deployment practices.

Good to Have

• Experience building AI agents and agentic workflows using LangGraph.
• Familiarity with RAG evaluation frameworks such as RAGAS and LangSmith.
• Knowledge of recommendation systems.
• Experience implementing CI/CD pipelines using GitHub Actions.
• Understanding of LLM observability, prompt optimization, and production monitoring.

Educational Qualifications

• B.Tech / B.E.…