Senior Backend Engineer

About PGAGI:

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

About the Role

We are at the forefront of building advanced AI systems — from fully autonomous agents that power intelligent customer interactions, to data analysis tools that deliver actionable business insights. This internship combines hands-on AI/ML engineering with robust backend development, giving you a complete picture of how production-grade AI systems are built, deployed, and scaled.

You will work across the full stack: designing and fine-tuning AI models on one end, and architecting the APIs, databases, and server-side infrastructure that bring those models to life on the other.

Key Responsibilities

AI / ML ENGINEERING

Design, experiment with, and fine-tune large language models (LLMs) and NLP pipelines for real-world use cases.

Develop and iterate on prompt engineering strategies to optimise model performance and output quality.

Integrate and deploy models using Hugging Face and OpenAI platforms; evaluate open-source alternatives.

Build deep learning workflows including training, evaluation, and continuous improvement loops.

Collaborate on data collection, preprocessing, and feature engineering for ML pipelines.

BACKEND ENGINEERING

Architect and develop scalable RESTful APIs and GraphQL endpoints using Node.js / FastAPI / Express.

Build and maintain full-stack features using Next.js (App Router), integrating server-side rendering, API routes, and React components.

Design and manage relational and NoSQL databases (PostgreSQL, MongoDB, or equivalent); write efficient queries and manage schema migrations.

Implement authentication, authorisation, and security best practices (JWT, OAuth 2.0, role-based access control).

Containerise services with Docker and contribute to CI/CD pipelines for reliable, automated deployments.

Integrate AI/ML model inference endpoints into backend services, handling async processing, queuing, and latency optimisation.

Write clean, well-tested, and well-documented backend code; participate actively in code reviews.

VERSION CONTROL & COLLABORATION

Use Git and GitHub for all version control workflows — branching strategies, pull requests, and code reviews.

Contribute to technical documentation, architecture decision records, and internal knowledge bases.

Duration & Compensation

Duration: 6 Months

Stipend: Base ₹8,000/month — up to ₹15,000/month based on performance

Post-Internship: Full-time opportunity as AI/ML Engineer (₹6–8 LPA) based on performance

Perks & Benefits

Hands-on experience shipping real AI products used by actual customers.

Mentorship from senior engineers and industry experts in AI/ML and backend development.

Exposure to the full development lifecycle — from model training to production deployment.

Collaborative, innovative, and flexible work environment.

Accelerated growth path with a clear route to a full-time engineering role.

How to Apply

Interested candidates are invited to submit their resume and complete the assignment using

the link : https://pgagi.in/jobs/28df1e98-f0c3-4d58-9509-d5b1a4ea9754

Shortlisted candidates will be contacted for an interview.

Selection Process

Initial Screening: We'll review your application for evidence of your skills, experience, and a strong foundation in AI.

Task Assignment: Candidates need to submit assignment which is already being attached in careers page , designed to assess your practical skills.

Performance Review: Our experts will evaluate your task submission, with excellence in this stage being crucial for further consideration.

Interview: Impressive task performers will be invited for an interview to discuss their potential contribution to our team.

Onboarding: Successful candidates will join our team, with exciting projects ahead

Requirements

MUST-HAVE SKILLS

Strong proficiency in Python for AI/ML development and scripting.

Solid understanding of JavaScript / TypeScript; experience with Node.js and Next.js (or a strong willingness to learn quickly).

Familiarity with REST API design principles and at least one backend framework (Express, FastAPI, Django, etc.).

Working knowledge of at least one database system (PostgreSQL, MySQL, MongoDB).

Experience with Git and GitHub version control workflows.

Exposure to AI/ML platforms such as Hugging Face and OpenAI.

Understanding of prompt engineering concepts and the model fine-tuning process.

GOOD TO HAVE

Hands-on experience with Next.js App Router, React Server Components, or similar modern full-stack frameworks.

Familiarity with Docker, basic DevOps concepts, or cloud platforms (AWS, GCP, or Azure).

Experience with message queues (Redis, RabbitMQ) or background task processing.

Knowledge of LLM orchestration tools such as LangChain or LlamaIndex.

SOFT SKILLS & MINDSET

Strong problem-solving instincts and a genuine curiosity about AI technology.

Ability to own tasks end-to-end and communicate progress clearly.

Comfortable working in a fast-moving environment where requirements evolve.

A growth mindset — eager to learn, receive feedback, and level up continuously.

TECH YOU'LL WORK WITH

Python

Next.js

Node.js

FastAPI

LLMs / NLP

PostgreSQL

React

Docker

HuggingFace

OpenAI API

GitHub

REST / GraphQL

Apply now to embark on a transformative career journey with PGAGI, where innovation and talent converge!

#artificialintelligence #Machinelearning #AI #AIML #LLM #FastAPI #NLP #openAI #AImodels #AIMLInternship #AIintern #Internship #aimlgraduate #Python

Job Title: AI Architecture Intern

Company: PGAGI Consultancy Pvt. Ltd.

Location: Remote

Employment Type: Internship

Position Overview

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

Duration: 6 months

Key Responsibilities:

• AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
• Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
• Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
• Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
• Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.

Requirements:

• Strong understanding of AI concepts, machine learning algorithms, and data structures.
• Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
• Proficiency in programming languages such as Python, Java, or C++.
• Demonstrated interest in system architecture, design thinking, and scalable solutions.
• Up-to-date knowledge of AI trends, tools, and technologies.
• Ability to work independently and collaboratively in a remote team environment

Perks:

- Hands-on experience with real AI projects.

- Mentoring from industry experts.

- A collaborative, innovative and flexible work environment

Compensation:

- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.

After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer.

Preferred Experience:

• Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
• Exposure to AI-driven startups or fast-paced technology environments.
• Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.

Job Description: Python Developer

Experience: 2+ Years

Job Location: Nr. Iskcon Mega Mall, SG Highway, Ahmedabad

Timings: 10 AM to 7 PM

Job Description:

Technical Skills :

• Good knowledge of Python with 2+ years of minimum experience 
• Strong understanding of various Python Libraries, APIs, and toolkits. 
• Good experience in Django, Django REST Framework, and Flask framework.
• Understanding of AWS Serverless implementation using Lambda and API Gateway
• Hands-on Experience in Databases like Mysql, PostgreSQL.
• Good experience/understanding in Agentic AI / RAG.
• Proficient in NoSQL document databases especially MongoDB, Redis.
• Stronghold in Data Structures and Algorithm
• Thorough understanding of version control system concepts especially GIT.
• Understanding of the whole web stack and how all the pieces fit together (front-end, database, network layer, etc.) and how they impact the performance of your application.
• Excellent understanding of MVC and OOP. Bonus for the understanding of prevalent design patterns.
• Excellent debugging and optimization skills

Job Responsibilities :

• Building big, robust, scalable, and maintainable applications.
• Debugging, Fixing bugs, Identifying Performance Issues, and Improving App Performance.
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency.
• Handling complex technical issues related to web app development & discussing solutions with the team.
• Developing, Deploying, and maintaining Multistage, Multi-tier applications.
• To write high-performing code and will be participating in key architectural decisions.
• Project Execution & Client Interaction
• Scrum Implementation

AI Engineer

LLMs, Agents & AI Services

📍 Mumbai (On-site) | Full-time | 2-4 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

AI is core to how we design, deliver, and scale software for our customers.

We are hiring an AI Engineer for a dedicated client engagement building a complex production AI platform, working on the AI capabilities and agentic features at the core of the product.

The mandatory requirement for this role is at least one AI feature personally shipped to production for real users, with operational ownership.

The role suits someone who thinks quickly on solutioning, can take an ambiguous problem to a working prototype in days, and has the discipline to carry it through to production with predictable economics.

You will work alongside the Senior AI Engineer and the wider pod, with ownership of parts of the AI surface area of the product.

Responsibilities:

Solutioning and POCs

Translate ambiguous customer problems into working POCs at speed.

Pick the right model, framework, and architecture, and demonstrate value early before scaling investment.

LLM Application Development

Build AI features and services using LLM APIs from OpenAI, Anthropic, Google, and self-hosted open-weight models (Llama, Qwen, Mistral).

Choose the right model per use case based on cost, latency, capability, and context-window trade-offs.

Agentic System Design

Design and implement agentic workflows using LangGraph, CrewAI, AutoGen, LlamaIndex Agents, or custom orchestration.

Cover tool use, planning, memory, and multi-step reasoning appropriate to the problem.

API and Service Development

Build production AI services and APIs using Python and FastAPI.

Handle streaming responses, async processing, structured outputs, retries, and graceful degradation when models or tools fail.

Retrieval and Tool Integration

Implement RAG pipelines with vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma), embeddings, chunking strategies, hybrid search, and reranking.

Integrate external tools, internal APIs, and document sources through tool-calling and MCP-style patterns.

Cost Analysis and Unit Economics

Model the per-request and per-user cost of every AI feature before it ships.

Track token usage, prompt caching, batching, and model-routing strategies.

Drive measurable improvements in unit economics.

Production Hardening

Add observability and tracing (LangSmith, Langfuse, OpenTelemetry), guardrails, content safety checks, prompt injection defences, and fallback behaviour.

Prompt Engineering and Evaluation

Design, test, and iterate prompts with measured outcomes.

Build evaluation harnesses for accuracy, hallucination, latency, and cost.

Run benchmarks across models and prompt variants before locking in a design.

Requirements:

AI Feature Shipped to Production (Mandatory)

Must have personally built and shipped at least one AI feature that runs in production for real users, with operational ownership.

POCs, internal demos, and one-off scripts do not qualify.

2 to 4 Years of Professional Software or AI Engineering Experience

With at least one production AI feature owned end to end.

Strong Python Proficiency and API Development with FastAPI

Comfort with type hints, async, packaging, testing, streaming responses, and authentication.

Production-grade Python, not notebook-only code.

Hands-on Depth Across the LLM and Agent Stack

Working experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or self-hosted open-weight models (vLLM, Ollama, Together, Replicate).

Working familiarity with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Working knowledge of RAG, embeddings, and vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma).

Solutioning Speed and POC Velocity

Demonstrated ability to move from a fuzzy problem to a working prototype in days.

Strong instinct for what to build first, what to defer, and what to throw away.

Cost Discipline for Production AI

Ability to calculate, monitor, and optimise the cost of LLM APIs, tokens, embeddings, vector store usage, and infrastructure.

Treats unit economics as a first-class concern.

AWS Familiarity

Working knowledge of EC2, S3, IAM, and at least one of Bedrock, SageMaker, or equivalent.

Comfortable in a Fast-Moving Environment

Self-directed, comfortable with ambiguity, takes ownership without being asked, and ships under shifting priorities.

Strong Written and Spoken English Communication

Able to explain trade-offs to non-AI engineers, designers, product managers, and clients in plain language.

Nice to Have

• fine-tuning or LoRA, QLoRA, PEFT exposure
• MCP server authoring
• eval framework experience (LangSmith, Promptfoo, Ragas, DeepEval)
• open-source AI contributions
• multi-modal models (vision, audio)

Company Description

Recruiting Bond International is a next-generation Talent Intelligence, Executive Search, and Human Capital Advisory firm helping start-ups, enterprises, GCCs, and VC/PE-backed companies build high-impact global teams. It is a global leader in Recruitment Process Outsourcing (RPO), executive search, and workforce consulting, specializing in building transformative talent strategies.

From high-growth startups to Fortune 500 companies, Recruiting Bond partners with organizations across 50+ industries and 140+ countries to deliver fast, scalable, and inclusive hiring solutions. The company supports businesses in scaling teams, fostering innovation, and creating talent-first strategies to achieve their goals.

With deep expertise across Technology, FinTech, Healthcare, Real Estate, and Energy, Recruiting Bond is dedicated to building careers, companies, and futures by connecting world-class talent with high-impact opportunities globally.

About the Role

Our client is hiring a Backend Engineer (India-based, Remote) to design, build, and scale the core memory infrastructure powering production-grade AI agents.

This role is intended for an experienced engineer with 7–10 years of backend engineering experience, who has deeply internalized AI-native engineering practices and actively builds using tools such as Claude Code, Codex, Cursor, Windsurf, or comparable AI development tools as a core part of their workflow.

The hiring process is intentionally non-traditional and skill-first. There is no evaluation based on IIT pedigree, LeetCode performance, or conventional resume filters. Instead, the only evaluation criterion is: how you build with AI in real-world scenarios.

Candidates are expected to submit prompt logs or transcripts from Claude Code, Codex, Cursor, or Windsurf demonstrating a feature or product they are proud of.

What You'll Own

• Build and scale backend systems powering the memory infrastructure of the product
• Own and deliver features end-to-end, integrating AI coding tools into the core development workflow
• Design, manage, and optimize database, storage, and retrieval systems for persistent memory
• Collaborate closely on system architecture, scalability, performance, and reliability engineering
• Contribute directly to product roadmap decisions based on real customer usage and production insights

Requirements

Must-Have

• 7–10 years of backend engineering experience
• Demonstrated ability to build with AI coding tools (Claude Code, Codex, Cursor, Windsurf, or comparable)
• Ability and willingness to submit prompt log transcripts from a feature or product you are proud of
• Strong Python fundamentals
• Strong PostgreSQL or comparable relational database fundamentals
• Comfort owning systems end-to-end in production
• Based in India, remote work from anywhere in the country

Nice-to-Have

• Prior AI infrastructure or developer tools product experience
• FastAPI fluency
• Open-source contributions in AI, memory, vector databases, or developer tools
• Prior experience in memory systems, RAG pipelines, or vector database engineering
• Public technical writing or conference talks on AI-native engineering practices

About Techjays

At Techjays, we build production-grade AI platforms for global clients. We operate at the intersection of backend engineering, distributed systems, and applied AI — delivering secure, scalable, and enterprise-ready intelligent systems. Our team has built and scaled products at Google, Akamai, NetApp, ADP, Cognizant, and Capgemini.

About the Role

This is not a feature-delivery role. We are looking for an AI Lead who can architect, own, and scale intelligent backend systems end-to-end. You will drive both technical direction and execution — working across LLM integrations, RAG pipelines, agentic AI workflows, and cloud-native backend systems for global clients.

What You'll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement RAG pipelines, AI agents, and LLM integrations
• Own systems end-to-end — from architecture to deployment and scaling
• Integrate and optimize LLMs (Claude, GPT, Gemini) for real-world production use cases
• Build high-performance distributed systems with observability and cost efficiency
• Lead backend and AI initiatives with strong technical ownership
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to deliver AI-native solutions

What We're Looking For

• 6–10 years of strong backend engineering experience
• Hands-on expertise in Python (FastAPI / Django / Flask)
• Deep understanding of Generative AI and LLM-based systems
• Strong experience with RAG pipelines and Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Solid knowledge of Agentic AI — building autonomous agents and multi-agent workflows
• Proficiency in AWS or GCP in production environments
• Experience with distributed systems, microservices, and system design
• Strong grasp of Data Structures, Algorithms, and Design Patterns
• Familiarity with WebSockets, Git, Linux/Unix, and CI/CD

Nice to Have

• Experience with Anthropic Claude API and Claude Code
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• MLOps and AI system lifecycle experience
• Optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable navigating fast-moving, ambiguous environments
• You stay updated with the latest in Generative AI and backend technologies
• Strong communicator who can collaborate across teams and global clients

What We Offer

• Competitive compensation (Best in Industry)
• Work on production-grade AI systems used by global clients
• Exposure to cutting-edge AI tools and frameworks
• A culture that values clarity, integrity, and continuous growth

About Techjays

At Techjays, we build production-grade AI platforms for global clients. We operate at the intersection of backend engineering, distributed systems, and applied AI — delivering secure, scalable, and enterprise-ready intelligent systems. Our team has built and scaled products at Google, Akamai, NetApp, ADP, Cognizant, and Capgemini.

About the Role

This is not a feature-delivery role. We are looking for an AI Lead who can architect, own, and scale intelligent backend systems end-to-end. You will drive both technical direction and execution — working across LLM integrations, RAG pipelines, agentic AI workflows, and cloud-native backend systems for global clients.

What You'll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement RAG pipelines, AI agents, and LLM integrations
• Own systems end-to-end — from architecture to deployment and scaling
• Integrate and optimize LLMs (Claude, GPT, Gemini) for real-world production use cases
• Build high-performance distributed systems with observability and cost efficiency
• Lead backend and AI initiatives with strong technical ownership
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to deliver AI-native solutions

What We're Looking For

• 6–10 years of strong backend engineering experience
• Hands-on expertise in Python (FastAPI / Django / Flask)
• Deep understanding of Generative AI and LLM-based systems
• Strong experience with RAG pipelines and Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Solid knowledge of Agentic AI — building autonomous agents and multi-agent workflows
• Proficiency in AWS or GCP in production environments
• Experience with distributed systems, microservices, and system design
• Strong grasp of Data Structures, Algorithms, and Design Patterns
• Familiarity with WebSockets, Git, Linux/Unix, and CI/CD

Nice to Have

• Experience with Anthropic Claude API and Claude Code
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• MLOps and AI system lifecycle experience
• Optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable navigating fast-moving, ambiguous environments
• You stay updated with the latest in Generative AI and backend technologies
• Strong communicator who can collaborate across teams and global clients

What We Offer

• Competitive compensation (Best in Industry)
• Work on production-grade AI systems used by global clients
• Exposure to cutting-edge AI tools and frameworks
• A culture that values clarity, integrity, and continuous growth

About the Role

At Techjays, we build production-grade AI systems for global clients. We are looking for a Solution Architect who can bridge the gap between client needs and technical delivery — someone who can walk into a client room, understand their business challenges, and walk out with a compelling, technically sound AI solution.

This role sits at the intersection of pre-sales, solutioning, and delivery governance.

What You'll Do

• Own end-to-end solutioning from client discovery to architecture design
• Partner with pre-sales teams on RFPs, proposals, and client presentations
• Define architectures for LLM integrations, RAG pipelines, and agentic workflows
• Conduct architecture reviews and technical assessments for ongoing projects
• Act as a trusted technical advisor to enterprise clients during pre-sales

Key Skills

• Python, REST APIs, Microservices, Distributed Systems
• AWS / Azure / GCP, Docker, Kubernetes, CI/CD
• LLM Integrations, RAG Pipelines, AI Agents, Vector Databases
• Enterprise data architecture and integration patterns
• Strong client communication and presentation skills

Who You Are

• Client-first mindset — listens, understands, and translates business pain into technical clarity
• Strong communicator comfortable with C-level stakeholders
• High ownership — accountable for every solution you sign off on
• Collaborative across sales, delivery, and engineering

What We Offer

• Flexible work environment
• Paid holidays & flexible time off
• Medical insurance (Self & Family up to ₹4 Lakhs)
• Exposure to global clients and high-impact pre-sales engagements
• A culture of clarity, integrity, and continuous growth

We're Hiring: Senior Developer (AI & Machine Learning)** 🚀

🔧 **Tech Stack**: Python, Neo4j, FAISS, LangChain, React.js, AWS/GCP/Azure

🧠 **Role**: AI/ML development, backend architecture, cloud deployment

🌍 **Location**: Remote (India)

💼 **Experience**: 5-10 years

If you're passionate about making an impact in EdTech and want to help shape the future of learning with AI, we want to hear from you!

About Synorus

Synorus is building a next-generation ecosystem of AI-first products. Our flagship legal-AI platform LexVault is redefining legal research, drafting, knowledge retrieval, and case intelligence using domain-tuned LLMs, private RAG pipelines, and secure reasoning systems.

If you are passionate about AI, legaltech, and training high-performance models — this internship will put you on the front line of innovation.

Role Overview

We are seeking passionate AI/LLM Engineering Interns who can:

• Fine-tune LLMs for legal domain use-cases
• Train and experiment with open-source foundation models
• Work with large datasets efficiently
• Build RAG pipelines and text-processing frameworks
• Run model training workflows on Google Colab / Kaggle / Cloud GPUs

This is a hands-on engineering and research internship — you will work directly with senior founders & technical leadership.

Key Responsibilities

• Fine-tune transformer-based models (Llama, Mistral, Gemma, etc.)
• Build and preprocess legal datasets at scale
• Develop efficient inference & training pipelines
• Evaluate models for accuracy, hallucinations, and trustworthiness
• Implement RAG architectures (vector DBs + embeddings)
• Work with GPU environments (Colab/Kaggle/Cloud)
• Contribute to model improvements, prompt engineering & safety tuning

Must-Have Skills

• Strong knowledge of Python & PyTorch
• Understanding of LLMs, Transformers, Tokenization
• Hands-on experience with HuggingFace Transformers
• Familiarity with LoRA/QLoRA, PEFT training
• Data wrangling: Pandas, NumPy, tokenizers
• Ability to handle multi-GB datasets efficiently

Bonus Skills

(Not mandatory — but a strong plus)

• Experience with RAG / vector DBs (Chroma, Qdrant, LanceDB)
• Familiarity with vLLM, llama.cpp, GGUF
• Worked on summarization, Q&A or document-AI projects
• Knowledge of legal texts (Indian laws/case-law/statutes)
• Open-source contributions or research work
• 
  

What You Will Gain

• Real-world training on LLM fine-tuning & legal AI
• Exposure to production-grade AI pipelines
• Direct mentorship from engineering leadership
• Research + industry project portfolio
• Letter of experience + potential full-time offer
• 
  

Ideal Candidate

• You experiment with models on weekends
• You love pushing GPUs to their limits
• You prefer research + implementation over theory alone
• You want to build AI that matters — not just demos

Location - Remote

Stipend - 5K - 10K