Software Engineer

Alike Thoughts; Pune District, Bengaluru, Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Alike Thoughts is seeking a Generative AI Engineer to design, build, and deploy production-grade AI solutions in India. You will bridge ML research with cloud software engineering, building scalable pipelines, optimizing LLMs, and deploying secure RAG applications using Python and cloud platforms.

Key work includes implementing workflows with LangChain, tuning models with PEFT/LoRA, and exposing capabilities via REST APIs.

Qualifications

• Proficiency in Python for async programming and typing patterns.
• Hands-on experience with Transformers, LangChain, LlamaIndex, or Guidance.
• Strong API development with FastAPI, Flask, or modern orchestration layers.
• Familiarity with cloud AI services (AWS or Azure) and vector databases.
• Experience with CI/CD and IaC tools (Git, GitHub Actions, Terraform).

Responsibilities

• Design and implement generative workflows, autonomous agents, and RAG architectures.
• Optimize LLMs via prompt engineering, PEFT/LoRA, and quantization.
• Architect secure, auto-scaling AI microservices on cloud platforms with containers.
• Build high-throughput data ingestion pipelines and vector databases for semantic search.
• Create and maintain RESTful APIs to expose generative capabilities.
• Set up CI/CD, model tracking, latency auditing, and token cost governance.

Skills

Python

Tools

Hugging Face Transformers

LangChain

LlamaIndex

Guidance

FastAPI

Flask

Amazon Bedrock

SageMaker JumpStart

AWS Lambda

ECS/EKS

IAM policies

Azure OpenAI Service

Azure Machine Learning

Azure Functions

AKS

Azure Entra ID

Pinecone

Milvus

Qdrant

PGVector

OpenSearch

Azure AI Search

Git

GitHub Actions

GitLab CI

Terraform

Job description

Job Title: Generative AI Engineer (Python & Cloud )Job Overview

We are seeking a highly skilled Generative AI Engineer to design, build, and deploy production-grade Artificial Intelligence solutions. In this role, you will bridge the gap between advanced machine learning research and robust cloud software engineering. You will build scalable pipelines, optimize Large Language Models (LLMs), and deploy secure Retrieval-Augmented Generation (RAG) applications using Python and cloud ecosystems (AWS or Azure).

Core Responsibilities

• AI Application Development: Design and implement generative workflows, autonomous agents, and RAG architectures using frameworks like LangChain, LlamaIndex, or AutoGen. [1, 2, 3]
• LLM Engineering & Fine-Tuning: Optimize foundational models through prompt engineering, parameter-efficient fine-tuning (PEFT/LoRA), and model quantization. [1]
• Cloud Infrastructure & Pipelines: Architect secure, auto-scaling AI microservices on cloud platforms using containerized environments. [1]
• Data & Vector Management: Build high-throughput data ingestion pipelines into vector databases for semantic search and real-time knowledge retrieval.
• API Integration: Create and maintain clean, well-documented RESTful APIs to expose generative capabilities to front-end systems. [1, 2]
• MLOps & Monitoring: Set up continuous integration and deployment (CI/CD) paths, model tracking, latency auditing, and token cost governance. [1, 2]

Technical Skills Requirements1. Core Programming & AI Libraries

• Language: Expert proficiency in Python (async programming, type hinting, and design patterns).
• AI Frameworks: Hands-on experience with Hugging Face Transformers, LangChain, LlamaIndex, or Guidance.
• API Development: Strong mastery of FastAPI, Flask, or modern API orchestration layers. [1]

2. Cloud & MLOps Infrastructure (AWS or Azure)

• If AWS Stack: Deep familiarity with Amazon Bedrock, SageMaker JumpStart, AWS Lambda, Amazon ECS/EKS, and AWS IAM policies.
• If Azure Stack: Deep familiarity with Azure OpenAI Service, Azure Machine Learning, Azure Functions, Azure Kubernetes Service (AKS), and Azure Entra ID.
• Vector Databases: Experience with Pinecone, Milvus, Qdrant, PGVector, or cloud-native vector indexes (e.g., OpenSearch, Azure AI Search).
• DevOps / IaC: Version control using Git, automation through GitHub Actions or GitLab CI, and infrastructure management via Terraform.Role & responsibilities