Gen AI Engineer Tier 1 college only

Gen AI Engineer Tier 1 college only

Gen AI Engineer Tier 1 college only at Talent Pro · Bengaluru (Bangalore) · 1 - 3 years · ₹20L - ₹27L / yr · Bootstrapped · Posted 3 Apr 2026

Gen AI Engineer Tier 1 college only

at Talent Pro

Posted by Mayank choudhary

1 - 3 yrs

₹20L - ₹27L / yr

Bengaluru (Bangalore)

Skills

Python

Artificial Intelligence (AI)

Strong Junior GenAI / AI Backend Engineer Profiles

Mandatory (Experience 1) – Must have 1+ years of full time expeirence in software development using LLMs (OpenAI / Gemini / similar) in projects (internship / full-time / strong personal projects)

Mandatory (Experience 2) – Must have strong coding skills in Python and hands-on backend development experience (FastAPI / Django preferred)

Mandatory (Experience 3) – Must have built or contributed to AI/LLM-based applications, such as chatbots, copilots, document processing tools, etc.

Mandatory (Experience 4) – Must have basic understanding of RAG concepts (embeddings, vector DBs, retrieval)

Mandatory (Experience 5) – Must have experience building APIs or backend services and integrating with external systems

Mandatory (Experience 6) – Must have AI/LLM projects clearly mentioned in CV (with what was built, not just tools used)

Mandatory (Experience 7) – Must have worked with modern development tools (Git, APIs, basic cloud exposure)

Mandatory (Tech Stack) – Strong in Python + basic AI/LLM ecosystem

Mandatory (Company) – Product companies / Funded startups (Series A / B / high-growth environments)

Mandatory (Education) - Tier-1 institutes (IITs, BITS, IIITs), Can be skipped if from Top notch product companies

Mandatory (Exclusion) - Avoid candidates with Only Prompt Engineers, from pure Data Science / ML theory background without backend coding, Frontend-heavy engineers.

Strong Junior GenAI / AI Backend Engineer Profiles

Mandatory (Experience 1) – Must have 1+ years of full time expeirence in software development using LLMs (OpenAI / Gemini / similar) in projects (internship / full-time / strong personal projects)

Mandatory (Experience 2) – Must have strong coding skills in Python and hands-on backend development experience (FastAPI / Django preferred)

Mandatory (Experience 3) – Must have built or contributed to AI/LLM-based applications, such as chatbots, copilots, document processing tools, etc.

Mandatory (Experience 4) – Must have basic understanding of RAG concepts (embeddings, vector DBs, retrieval)

Mandatory (Experience 5) – Must have experience building APIs or backend services and integrating with external systems

Mandatory (Experience 6) – Must have AI/LLM projects clearly mentioned in CV (with what was built, not just tools used)

Mandatory (Experience 7) – Must have worked with modern development tools (Git, APIs, basic cloud exposure)

Mandatory (Tech Stack) – Strong in Python + basic AI/LLM ecosystem

Mandatory (Company) – Product companies / Funded startups (Series A / B / high-growth environments)

Mandatory (Education) - Tier-1 institutes (IITs, BITS, IIITs), Can be skipped if from Top notch product companies

Mandatory (Exclusion) - Avoid candidates with Only Prompt Engineers, from pure Data Science / ML theory background without backend coding, Frontend-heavy engineers.

Read more

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About Talent Pro

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Read more

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Develop and maintain applications using Python and modern frameworks.
Build GenAI/LLM-based applications and solutions.
Develop RAG pipelines using vector databases.
Work with LangChain/LangGraph for LLM and agent-based applications.
Develop and integrate REST APIs using FastAPI.
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We are looking for a Python Developer with strong experience in Generative AI and LLM-based applications. The candidate should have hands-on experience building AI solutions using Python, RAG, LangChain/LangGraph, and related GenAI technologies.

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Develop and maintain applications using Python and modern frameworks.
Build GenAI/LLM-based applications and solutions.
Develop RAG pipelines using vector databases.
Work with LangChain/LangGraph for LLM and agent-based applications.
Develop and integrate REST APIs using FastAPI.
Implement Agentic AI workflows and AI-powered features.
Integrate LLMs with existing applications and microservices.
Apply prompt engineering techniques to improve AI application performance.

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Build and deploy AI/LLM-powered applications and features.
Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
Build scalable backend APIs and services.
Develop frontend applications using React/Next.js.
Integrate LLMs such as OpenAI, Claude, Gemini, etc.
Work with databases, cloud platforms and production deployments.
Collaborate with product and design teams and take ownership of features end-to-end.

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3–6 years of software engineering experience.
Strong Python and/or TypeScript/Node.js.
Strong React.js / Next.js / TypeScript experience.
Hands-on experience with LLMs / Generative AI.
Experience with RAG, AI Agents or tool/function calling.
Experience building and deploying real-world products.
Good understanding of APIs, databases and cloud deployment.

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LangChain / LangGraph / LlamaIndex
PostgreSQL / Vector Databases
AWS / GCP / Azure / Vercel
Docker / CI/CD
Experience in an early-stage startup or AI product company.

We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.

About the Role

We are looking for a hands-on Applied AI / Full Stack Engineer to build AI-powered products and experiences. The ideal candidate should be comfortable working across AI, backend, and frontend and taking features from idea to production.

Key Responsibilities

Build and deploy AI/LLM-powered applications and features.
Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
Build scalable backend APIs and services.
Develop frontend applications using React/Next.js.
Integrate LLMs such as OpenAI, Claude, Gemini, etc.
Work with databases, cloud platforms and production deployments.
Collaborate with product and design teams and take ownership of features end-to-end.

Must-Have Skills

3–6 years of software engineering experience.
Strong Python and/or TypeScript/Node.js.
Strong React.js / Next.js / TypeScript experience.
Hands-on experience with LLMs / Generative AI.
Experience with RAG, AI Agents or tool/function calling.
Experience building and deploying real-world products.
Good understanding of APIs, databases and cloud deployment.

Good to Have

LangChain / LangGraph / LlamaIndex
PostgreSQL / Vector Databases
AWS / GCP / Azure / Vercel
Docker / CI/CD
Experience in an early-stage startup or AI product company.

We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.

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Gen AI Developer

Agency job

via by Naveen Balne

Hyderabad, Bengaluru (Bangalore), Pune, Chennai, Kolkata

5 - 13 yrs

₹15L - ₹40L / yr

Artificial Intelligence (AI)

Generative AI

Generative AI (GenAI)

Python

Large Language Models (LLM)

+7 more

We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.

Key Responsibilities

Develop and enhance Generative AI applications using LLMs and AI frameworks.
Build and optimize RAG pipelines, vector search, and AI-powered workflows.
Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
Develop REST APIs and integrate AI capabilities into enterprise applications.
Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
Ensure code quality through testing, debugging, documentation, and code reviews.
Follow Responsible AI, security, and data governance practices.

Required Technical Skills

Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
Experience with PyTorch, TensorFlow, or Keras.
Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
Understanding of AI governance, data privacy, and Responsible AI principles.

Preferred Skills

Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
Knowledge of multimodal AI applications.

Qualifications

Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
5 years of software development experience, including AI/ML or Generative AI projects.
Experience building and deploying production-grade AI solutions.

Assessment Focus Areas

Candidates will be evaluated on:

Python coding and problem-solving
Data Structures & Algorithms
LLMs, RAG, and Agentic AI concepts
API development and system design
Cloud deployment and AI solution architecture

We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.

Key Responsibilities

Develop and enhance Generative AI applications using LLMs and AI frameworks.
Build and optimize RAG pipelines, vector search, and AI-powered workflows.
Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
Develop REST APIs and integrate AI capabilities into enterprise applications.
Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
Ensure code quality through testing, debugging, documentation, and code reviews.
Follow Responsible AI, security, and data governance practices.

Required Technical Skills

Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
Experience with PyTorch, TensorFlow, or Keras.
Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
Understanding of AI governance, data privacy, and Responsible AI principles.

Preferred Skills

Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
Knowledge of multimodal AI applications.

Qualifications

Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
5 years of software development experience, including AI/ML or Generative AI projects.
Experience building and deploying production-grade AI solutions.

Assessment Focus Areas

Candidates will be evaluated on:

Python coding and problem-solving
Data Structures & Algorithms
LLMs, RAG, and Agentic AI concepts
API development and system design
Cloud deployment and AI solution architecture

Read more

Senior/Lead/Architect Gen AI Engineer

Prithisha Kathiresan

Posted by Prithisha Kathiresan

Bengaluru (Bangalore)

3 - 8 yrs

Best in industry

Generative AI (GenAI)

Large Language Models (LLM) tuning

Retrieval Augmented Generation (RAG)

Azure OpenAI

Amazon Web Services (AWS)

+2 more

Senior Generative AI Engineer

Employment Type: Permanent with VDart Digital

Work Location: Marathalli, Bengaluru

Job Description

We are seeking a highly skilled Senior Generative AI Engineer with strong expertise in designing, developing, and deploying enterprise-scale AI solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The ideal candidate should have hands-on production experience building scalable GenAI applications, AI agents, autonomous workflows, and Retrieval-Augmented Generation (RAG) systems in cloud-native environments.

This role requires deep technical expertise in LLM orchestration, AI application architecture, prompt engineering, vector databases, MLOps, and production deployment of AI systems. Candidates should have proven experience delivering real-world AI solutions in enterprise environments with strong exposure to cloud platforms and DevOps practices.

Key Responsibilities

Design, build, and deploy enterprise-grade Generative AI applications using Large Language Models (LLMs).
Develop intelligent AI agents and autonomous workflows using frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar agentic AI frameworks.
Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search technologies.
Work extensively on prompt engineering, tool calling, memory management, agent orchestration, and multi-agent systems.
Integrate and manage LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar foundation models.
Develop scalable AI services and APIs using Python and FastAPI.
Build production-ready AI solutions with high availability, scalability, monitoring, and observability.
Deploy and manage AI applications in cloud-native environments using Docker and Kubernetes.
Collaborate with Data Science, ML Engineering, and DevOps teams to operationalize AI solutions.
Implement CI/CD pipelines and automated deployment processes for AI workloads.
Monitor model performance, latency, reliability, and operational efficiency in production environments.
Ensure AI solutions follow enterprise security, governance, and responsible AI standards.
Evaluate and adopt emerging Generative AI tools, frameworks, and models.

Required Skills

Generative AI & LLM Expertise

Strong hands-on experience with Generative AI and Large Language Models (LLMs).
Production-level experience building and deploying GenAI applications.
Expertise in LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks.
Experience with AI agents, autonomous workflows, and multi-agent architectures.
Strong understanding of prompt engineering, embeddings, model evaluation, and LLM orchestration.
Experience integrating OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar models.

RAG & Vector Databases

Strong experience implementing RAG pipelines and semantic retrieval systems.
Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
Understanding of chunking strategies, embeddings, indexing, reranking, and retrieval optimization.

Python & AI Development

Strong proficiency in Python.
Experience with FastAPI for AI service and API development.
Experience with AI/ML libraries and data processing tools such as Pandas and NumPy.

Cloud & Production Deployment

Mandatory production experience on at least one cloud platform:
Microsoft Azure
Experience deploying scalable AI applications in enterprise production environments.
Hands-on experience with Docker, Kubernetes, Jenkins, Terraform, and CI/CD pipelines.
Strong understanding of MLOps, AI deployment lifecycle, monitoring, and observability.

Engineering & Operational Excellence

Strong understanding of software engineering best practices.
Experience with Git, version control, automated testing, and release management.
Experience building secure, scalable, and high-performance AI solutions.
Ability to troubleshoot production AI systems and optimize performance.

Preferred Skills

Experience with AI observability and evaluation frameworks.
Exposure to fine-tuning, PEFT, LoRA, or model optimization techniques.
Experience with enterprise AI governance and responsible AI practices.
Knowledge of distributed AI systems and scalable inference architectures.
Familiarity with AI security and compliance standards.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
3–8 years of overall software engineering experience.
Minimum 3+ years of hands-on experience in Generative AI and LLM-based application development,
Proven track record of delivering enterprise-scale AI solutions in production environments.
Strong communication and stakeholder management skills.

Senior Generative AI Engineer

Employment Type: Permanent with VDart Digital

Work Location: Marathalli, Bengaluru

Job Description

We are seeking a highly skilled Senior Generative AI Engineer with strong expertise in designing, developing, and deploying enterprise-scale AI solutions using Large Language Models (LLMs) and modern Generative AI frameworks. The ideal candidate should have hands-on production experience building scalable GenAI applications, AI agents, autonomous workflows, and Retrieval-Augmented Generation (RAG) systems in cloud-native environments.

This role requires deep technical expertise in LLM orchestration, AI application architecture, prompt engineering, vector databases, MLOps, and production deployment of AI systems. Candidates should have proven experience delivering real-world AI solutions in enterprise environments with strong exposure to cloud platforms and DevOps practices.

Key Responsibilities

Design, build, and deploy enterprise-grade Generative AI applications using Large Language Models (LLMs).
Develop intelligent AI agents and autonomous workflows using frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar agentic AI frameworks.
Implement and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search technologies.
Work extensively on prompt engineering, tool calling, memory management, agent orchestration, and multi-agent systems.
Integrate and manage LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar foundation models.
Develop scalable AI services and APIs using Python and FastAPI.
Build production-ready AI solutions with high availability, scalability, monitoring, and observability.
Deploy and manage AI applications in cloud-native environments using Docker and Kubernetes.
Collaborate with Data Science, ML Engineering, and DevOps teams to operationalize AI solutions.
Implement CI/CD pipelines and automated deployment processes for AI workloads.
Monitor model performance, latency, reliability, and operational efficiency in production environments.
Ensure AI solutions follow enterprise security, governance, and responsible AI standards.
Evaluate and adopt emerging Generative AI tools, frameworks, and models.

Required Skills

Generative AI & LLM Expertise

Strong hands-on experience with Generative AI and Large Language Models (LLMs).
Production-level experience building and deploying GenAI applications.
Expertise in LangChain, CrewAI, LangGraph, AutoGen, or similar frameworks.
Experience with AI agents, autonomous workflows, and multi-agent architectures.
Strong understanding of prompt engineering, embeddings, model evaluation, and LLM orchestration.
Experience integrating OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or similar models.

RAG & Vector Databases

Strong experience implementing RAG pipelines and semantic retrieval systems.
Experience with vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
Understanding of chunking strategies, embeddings, indexing, reranking, and retrieval optimization.

Python & AI Development

Strong proficiency in Python.
Experience with FastAPI for AI service and API development.
Experience with AI/ML libraries and data processing tools such as Pandas and NumPy.

Cloud & Production Deployment

Mandatory production experience on at least one cloud platform:
Microsoft Azure
Experience deploying scalable AI applications in enterprise production environments.
Hands-on experience with Docker, Kubernetes, Jenkins, Terraform, and CI/CD pipelines.
Strong understanding of MLOps, AI deployment lifecycle, monitoring, and observability.

Engineering & Operational Excellence

Strong understanding of software engineering best practices.
Experience with Git, version control, automated testing, and release management.
Experience building secure, scalable, and high-performance AI solutions.
Ability to troubleshoot production AI systems and optimize performance.

Preferred Skills

Experience with AI observability and evaluation frameworks.
Exposure to fine-tuning, PEFT, LoRA, or model optimization techniques.
Experience with enterprise AI governance and responsible AI practices.
Knowledge of distributed AI systems and scalable inference architectures.
Familiarity with AI security and compliance standards.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
3–8 years of overall software engineering experience.
Minimum 3+ years of hands-on experience in Generative AI and LLM-based application development,
Proven track record of delivering enterprise-scale AI solutions in production environments.
Strong communication and stakeholder management skills.

Read more

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