ai / ml engineer

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ai/ml intern (machine learning & generative ai) Jobs in India

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agentic ai engineer

Mindsprint

<div>
 
 
 About the Role
 
 
 
 
 
 
 
 We are seeking an experienced AI Engineer with 4+ years of strong expertise in Generative AI and Agentic AI, combined with solid production engineering capabilities.
 
 
 
 
 
 
 The ideal candidate will have hands-on experience building, deploying, and scaling LLM-powered systems &mdash; moving beyond prototypes into robust, enterprise-grade AI applications.
 
 
 Key Responsibilities
 
 
 
 
 
 &bull; Design, build, and deploy GenAI / Agentic AI solutions, including:
 
 
 o LLM pipelines
 
 
 o Retrieval-Augmented Generation (RAG) systems
 
 
 o Autonomous AI agents
 
 
 &bull; Develop scalable APIs, microservices, and model-serving architectures using cloud platforms (Azure preferred).
 
 
 &bull; Implement:
 
 
 o Prompt engineering and prompt workflows
 
 
 o Embeddings and vector search
 
 
 o Guardrails and safety mechanisms for responsible AI
 
 
 &bull; Deploy production AI systems using:
 
 
 o Docker, Kubernetes o CI/CD pipelines
 
 
 o Monitoring and observability frameworks
 
 
 
 
 
 &bull; Integrate AI solutions with enterprise systems, data sources, and external APIs.
 
 
 &bull; Ensure reliability, performance, compliance, and alignment with Responsible AI standards.
 
 
 Must-Have Skills (GenAI / Agentic AI)
 
 
 &bull; Hands-on experience in Generative AI development using models such as:
 
 
 o GPT, Claude, Llama, Mistral, etc.
 
 
 
 
 
 &bull; Strong experience in Agentic AI, including:
 
 
 o Multi-step AI agents o Tool-calling workflows
 
 
 o Autonomous task pipelines
 
 
 &bull; Expertise in RAG architectures and vector databases such as:
 
 
 o Pinecone, FAISS, Chroma, Azure Cognitive Search
 
 
 &bull; Proficiency in Python or JavaScript/TypeScript.
 
 
 &bull; Experience with frameworks like: o Azure OpenAI, LangChain, LlamaIndex, or similar
 
 
 &bull; Strong production engineering skills:
 
 
 o Docker, Kubernetes
 
 
 o CI/CD pipelines o API development and deployment best practices Nice to Have
 
 
 &bull; Model fine-tuning, quantization, or optimization experience.
 
 
 &bull; Familiarity with LLM evaluation frameworks such as:
 
 
 o Ragas, TruLens, DeepEval
 
 
 &bull; Exposure to event-driven or real-time AI systems.
 
 
 
 
 
 Job Location Chennai/Bangalore (Hybrid Model)
 
</div>

Agentic AI Engineer

Collabera

Position Details:-Experience: 6-9 YearsWork Location: Gurugram (Hybrid)Mode: Full Time PermanentJob Description:We are hiring mid-to-senior level Agentic / Generative AI Engineers (6&ndash;9 years&rsquo; experience) to design and deliver production-grade LLM-powered and agentic systems. This role is ideal for engineers with a strong Data Engineering / Data Science foundation who have transitioned into hands-on GenAI delivery&mdash;building real-world solutions such as RAG based assistants, document intelligence platforms, and agent-driven workflows. You will collaborate across data, platform, and business teams to build secure, scalable, and measurable AI applications for enterprise use cases.Key Responsibilities : Design and develop LLM-powered applications using agentic patterns (single/multi agent) for business use cases Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis) Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs) Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications Integrate LLM solutions with enterprise systems, data platforms, and workflows  Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling Contribute to reusable components, documentation, and engineering best practicesExperience &amp; Core Requirements (Must-Have) Overall Experience  6&ndash;9 years total experience 1&ndash;3+ years in hands-on GenAI / LLM application development (production use cases)LLM / GenAI &amp; Agentic Engineering  Strong hands-on experience with: o LLMs (Claude, OpenAI, etc.)o RAG pipelines and retrieval optimisationo GPT + Agentic AI implementation experience Experience with: o LangChain, LangGraph, or similar frameworks o Agent orchestration and tool-calling architectures Deep understanding of: LLM limitations, evaluation, and optimisation strategiesPay: ₹2,000,000.00 - ₹3,000,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Life insurance</li><li>Paid time off</li><li>Provident Fund</li></ul>Work Location: In person

Senior AI Data Engineer

Accenture in India

<div>
 
 Project Role :
 
 AI / ML Engineer
 
 
 
 Project Role Description :
 
 Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
 
 
 
 Must have skills :
 
 Machine Learning (ML)
 
 
 
 Good to have skills :
 
 NA
 
 
 
 Minimum 3 Year(s) Of Experience Is Required
 
 
 
 
 Educational Qualification :
 
 15 years full time education
 
 
 Role Summary
 
 
 We are seeking a hands-on AI Native Engineer who can design, build, and deploy end-to-end agentic and LLM-powered systems. This includes constructing RAG pipelines, working with vector databases, building autonomous or semi-autonomous agents, integrating tools and skills, and developing evaluation frameworks for high-quality AI behaviour. You will prototype rapidly, experiment with models, and evolve solutions from PoC to production while working closely with cross-functional teams.
 
 
 AI Powered Tech Talent
 
 
 Key Responsibilities
 
 
 Agentic &amp; LLM System Development
 
 
 Build agentic AI systems, including agent orchestration, planning loops, tool calling, and memory modules.
 
 
 Implement LLM toolchains, custom prompts, templates, evaluators, and multi-step reasoning workflows.
 
 
 Develop autonomous/semi-autonomous agents for retrieval, summarization, decision support, or workflow automation.
 
 
 RAG Pipelines &amp; Vector Intelligence
 
 
 Design and implement RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, vector search, hybrid retrieval, and grounding.
 
 
 Integrate vector databases such as pgvector, Pinecone, Weaviate, or Milvus.
 
 
 Optimize retrieval quality, latency, and factual accuracy using rerankers, retrieval evaluators, and freshness pipelines.
 
 
 Model Integration &amp; AI Ops
 
 
 Integrate enterprise-grade AI APIs, foundation models, and transformer models into scalable systems.
 
 
 Implement robust evaluation frameworks including offline and online evals, regression tests, content safety checks, and red-team scenarios.
 
 
 Build monitoring for model drift, agent failure modes, hallucination detection, and end-to-end system health.
 
 
 Full-Stack &amp; Cloud Alignment
 
 
 Deploy services using Python/Node/Java microservices, serverless functions, or containerized workloads.
 
 
 Integrate event streams, API gateways, and cloud-native patterns across Azure/AWS/GCP.
 
 
 Build CI/CD pipelines for AI services with safe rollouts, versioning, and feature flags for model updates.
 
 
 Prototyping &amp; Rapid Iteration
 
 
 Rapidly experiment with models, embeddings, architectures, and agentic patterns.
 
 
 Translate business requirements into AI-native technical architectures and communicate trade-offs via demos and deep-dives.
 
 
 Document designs, experiments, and evaluation results for reproducibility and knowledge sharing.
 
 
 Professional &amp; Technical Skills
 
 
 Must-Have (AI Native Core)
 
 
 Hands-on experience with LLMs, agent frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen), and vector DBs.
 
 
 Strong Python skills for building agents, RAG services, data pipelines, and evaluation harnesses.
 
 
 Deep understanding of transformer models, embeddings, prompt engineering, and model fine-tuning workflows.
 
 
 Experience deploying AI systems to production with monitoring, error handling, retries, and fallback strategies.
 
 
 Good to Have
 
 
 Experience with cloud AI platforms (Azure OpenAI, Bedrock, Vertex AI).
 
 
 Knowledge of multimodal models, reinforcement learning, or advanced reasoning agents.
 
 
 Familiarity with evaluation frameworks (pytest, JUnit) and custom eval harnesses.
 
 
 Additional Information
 
 
 Minimum 3 years of experience in ML/AI engineering (AI-native experience preferred).
 
 
 Location: Bengaluru.
 
 
 Education: 15 years full-time education., 15 years full time education
</div>

AI / ML Engineer

ThoughtFocus

<div><h1 class="jobSectionHeader">Lead Software Engineer (Agentic AI &amp; Strong Programming) 6-8 Years</h1>
<h2 class="jobSectionHeader">Role Overview</h2>
<div>We are looking for an AI Engineer with strong programming fundamentals and hands-on experience in Agentic AI development. The ideal candidate should be language-agnostic and capable of working across multiple technologies, with expertise in any of the following programming languages: Python, Java, C#, or C++.</div>
<div>This role requires solid experience in system design, OOP principles, REST API development, and building scalable AI-driven applications.</div>
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<ul><li>Design and develop AI agent-based systems and workflows</li>
<li>Build scalable backend services and REST APIs</li>
<li>Apply OOP principles and design patterns in production systems</li>
<li>Integrate LLMs and AI capabilities into applications</li>
<li>Solve complex technical problems</li>
<li>Work across multiple programming languages when required</li>
<li>Collaborate with cross-functional teams</li>
<li>Containerize applications using Docker and support deployments</li>
<li>Contribute to architecture and technical design decisions</li> 
</ul><div></div> 
<h2 class="jobSectionHeader">Required Skills (Must Have)</h2>
<ul><li>Strong programming skills in any of the following: Python, Java, C#, or C++</li>
<li>Strong understanding of Object-Oriented Programming (OOP)</li>
<li>Good knowledge of Design Patterns</li>
<li>Strong problem-solving skills</li>
<li>Hands-on experience building REST APIs</li>
<li>Experience with AI Agent / LLM-based development</li>
<li>Experience with LangChain, LangGraph, or similar AI agent frameworks</li>
<li>Experience building RAG (Retrieval-Augmented Generation) systems</li>
<li>Experience with AI-assisted coding / coding with AI tools</li>
<li>Ability to effectively leverage AI tools for development productivity</li>
<li>Exposure to Cloud platforms (AWS / Azure / GCP)</li>
<li>Experience with Docker</li>
<li>Ability to learn and adapt to new technologies quickly</li> 
</ul><div></div> 
<h2 class="jobSectionHeader">Preferred (Good to Have)</h2>
<ul><li>Understanding of Data Structures &amp; Algorithms</li>
<li>Kubernetes exposure</li>
<li>Microservices architecture experience</li>
<li>Experience building scalable distributed systems</li>
<li>CI/CD pipeline experience</li> 
</ul><div></div> 
<h2 class="jobSectionHeader">Ideal Candidate</h2>
<ul><li>Strong in engineering fundamentals</li>
<li>Language-agnostic developer</li>
<li>Comfortable working on new technologies</li>
<li>Eager to learn and adapt quickly</li>
<li>Strong analytical and logical thinking</li>
<li>Can contribute to architecture discussions</li></ul></div>

Lead Engineer

Fractal Analytics

<div>It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.<div><div>
Job Description</div></div><div><div><div><div><div><div><div><div><div><h1 class="jobSectionHeader">
EL3 &ndash; Databricks MLOps Engineer (Contract)</h1>
Domain: Claims Payment Integrity | M&amp;R, C&amp;S, E&amp;I Claims (preferred) 
Actuarial &amp; Forecasting Analytics Exposure is an Added Advantage 
Tech Stack: Databricks, Spark, Python, Scala, Azure, GitHub Actions, Terraform 
AI/LLM Capabilities: Embedding Models, LLM Integration, LangChain Agentic Frameworks<h2 class="jobSectionHeader">
Role Summary</h2>
The EL3 Databricks MLOps Engineer is a senior hands-on role responsible for enabling end-to-end machine learning lifecycle automation on Databricks. This includes building and maintaining the CI/CD infrastructure, environment configuration, packaging and deploying ML models, supporting reproducible experiments, and ensuring scalable job orchestration for AI/ML workloads, including LLM-based applications.
The role partners closely with Data Scientists, AI/ML Engineers, platform teams, and business stakeholders within Claims Payment Integrity to ensure robust, reliable, and automated ML delivery.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Enable and automate the end-to-end ML lifecycle on Databricks (environment setup, model workflow automation, job scheduling, monitoring hooks).</li><li>
Build frameworks, templates, and utilities that make ML development and experimentation reproducible and scalable.</li><li>
Implement CI/CD pipelines using Git, GitHub Actions, Jenkins, Azure DevOps, or similar tools.</li><li>
Package, version, and deploy ML models into Databricks-managed execution environments.</li><li>
Set up automated workflows for training, retraining, evaluation, and scheduled job execution.</li><li>
Support creation and integration of machine learning models including classification, forecasting, anomaly detection, NLP, and PI models.</li><li>
Enable LLM/GenAI-driven solutions by integrating:<ul><li>
Embedding model generation</li><li>
RAG architectures</li><li>
Vector databases</li><li>
LangChain agentic workflows</li></ul></li><li>
Optimize resource usage, runtime configurations, and code execution patterns for ML workloads.</li><li>
Collaborate with Data Scientists to translate experimental notebooks into production-ready pipelines.</li><li>
Implement platform-level controls for environment consistency, dependency management, access control, and model versioning.</li><li>
Support troubleshooting, debugging, and performance improvements for ML workloads.</li><li>
Document standards, templates, guidelines, and best practices for MLOps teams.</li><li>
Work cross-functionally with product, engineering, and analytics teams across PI.</li></ul><h2 class="jobSectionHeader">
Required Qualifications</h2><ul><li>
Bachelor&rsquo;s/Master&rsquo;s degree in Computer Science, Engineering, or related field</li><li>
6&ndash;9 years of relevant experience in ML Engineering, MLOps, or platform engineering</li><li>
Strong hands-on experience with Databricks, Spark (batch/streaming), Python, Scala</li><li>
Experience enabling ML lifecycle tools such as MLflow (tracking, packaging, model registration)</li><li>
Strong CI/CD experience using Git, GitHub Actions, Jenkins, or Azure DevOps</li><li>
Experience deploying AI/ML models into cloud environments (Azure preferred)</li><li>
Ability to create and integrate embedding models, semantic vectors, and LLM-driven components</li><li>
Experience with LangChain for agentic workflows and integration of tools/functions</li><li>
Strong problem-solving, debugging, and collaboration skills</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Experience with Azure OpenAI or OpenAI-compatible LLM APIs</li><li>
Familiarity with healthcare claims workflows, PI, FWA, provider billing, or pricing</li><li>
Experience in Agile/Scrum environments</li><li>
Strong understanding of software engineering best practices, packaging, dependency management</li></ul><h2 class="jobSectionHeader">
Good-to-Have Data Knowledge</h2><ul><li>
Call Center datasets (member &amp; provider interactions)</li><li>
Provider RCM datasets (billing, coding, authorizations)</li><li>
EHR/clinical datasets for cross-domain validation</li></ul></div></div></div></div></div></div></div></div></div>
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!<h3 class="jobSectionHeader">
Hiring Related Queries</h3>
India: HiringsupportIndia@fractal.ai
Outside India: HiringsupportROW@fractal.ai
This inbox does not process resume submissions. All applications must be made through posted job openings
Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!</div>

MLOps Engineer

LiveKit

<div><h2 class="jobSectionHeader">About LiveKit</h2>
LiveKit is building the infrastructure layer for the agentic era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe AI agents in production. Founded in 2021, LiveKit powers voice and agentic AI applications for OpenAI, Salesforce, Spotify, Meta, and tens of thousands of other developers, collectively facilitating billions of calls each year.<h2 class="jobSectionHeader">
About This Role</h2>
LiveKit is seeking a Forward Deployed Engineer (FDE) to work directly with customers building real-time communication and voice AI applications on the LiveKit platform.
This role sits at the intersection of engineering, architecture, and customer implementation. Forward Deployed Engineers partner closely with customers to design systems, prototype solutions, and solve complex technical challenges as teams move from experimentation to production.
You'll work alongside customers' engineering teams to help them successfully deploy and scale applications built on LiveKit &mdash; designing architectures, building integrations, debugging production issues, and developing reference implementations that demonstrate best practices.
This is an ideal role for engineers who enjoy solving real-world problems in real customer environments. You'll collaborate closely with Product and Engineering to surface insights from customer implementations and help shape the future of the LiveKit platform.
Your mission: make it seamless for developers to build and scale real-time audio, video, and AI applications on LiveKit.<h2 class="jobSectionHeader">
You'll Thrive Here If You:</h2><ul><li>
are obsessed with helping developers succeed</li><li>
are known as the go-to person for solving tricky technical issues</li><li>
work hard and can move fast without sacrificing quality</li><li>
care deeply about polish, detail, and clear communication</li><li>
are a fast learner, frequently picking up new tools, systems, and skills</li></ul><h2 class="jobSectionHeader">
What You'll Do</h2><ul><li>
Work directly (remotely or on-site when necessary) with customer engineering teams to design and implement real-time applications built on LiveKit</li><li>
Design scalable architectures for voice AI, real-time media, and developer platform use cases</li><li>
Build prototype integrations, reference implementations, and sample applications to accelerate customer development</li><li>
Help customers navigate SDKs, APIs, infrastructure, and deployment strategies for production systems</li><li>
Debug and troubleshoot complex technical issues in production environments</li><li>
Lead technical workshops and architecture sessions with developers and product teams</li><li>
Translate customer needs into technical insights that inform product and platform development</li><li>
Partner with Product and Engineering to improve developer experience, documentation, and tooling</li><li>
Contribute code, examples, or improvements to LiveKit's open-source ecosystem when helpful</li><li>
Act as a trusted advisor helping customers successfully launch and scale applications on LiveKit</li></ul><h2 class="jobSectionHeader">
Who You Are</h2><ul><li>
Strong engineering background with 5+ years of experience in backend or infrastructure engineering</li><li>
Proficient in one or more programming languages such as Go, Python, Node, Rust, or C++</li><li>
Comfortable working across APIs, SDKs, distributed systems, and cloud infrastructure</li><li>
Experience building or integrating developer platforms or real-time systems</li><li>
Able to quickly understand complex systems and debug issues in real-world environments</li><li>
Strong communicator who can collaborate directly with customer engineering teams and internal product teams</li><li>
Comfortable operating in fast-paced, low-process environments where ownership and initiative matter</li><li>
Excited to work hands-on with customers solving complex technical implementation challenges</li></ul><h2 class="jobSectionHeader">
Nice to Have</h2><ul><li>
Experience with WebRTC, real-time media systems, or telephony/SIP infrastructure</li><li>
Familiarity with voice AI, conversational agents, or AI infrastructure</li><li>
Experience working in customer-facing engineering roles such as Solutions Engineer, Field Engineer, or Forward Deployed Engineer</li><li>
Experience contributing to open-source projects or developer ecosystems</li><li>
Previous experience building with or integrating LiveKit</li></ul><h2 class="jobSectionHeader">
Our Commitment to You</h2><ul><li>
An opportunity to build something truly impactful to the world</li><li>
Contribute to open source alongside world-class engineers</li><li>
Competitive salary and equity package</li><li>
Health, dental, and vision benefits</li><li>
Flexible vacation policy</li></ul>
LiveKit is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by applicable law. If you require a reasonable accommodation during the application or interview process, please contact recruiting@livekit.io.
Compensation Range: ₹90L - ₹1.1Cr</div>

Forward Deployed Engineer

Aliqan Technologies

Job Description &ndash; GenAI EngineerPosition: GenAI Engineer Experience: 5.5 &ndash; 9 Years Location: Mumbai, Bangalore, Gurugram, Chennai Work Mode: Hybrid (3 Days Work From Office &ndash; Mandatory) Work Location: Candidate must be willing to work from the client location. CTC: Up to ₹36 LPAAbout the RoleWe are looking for an experienced GenAI Engineer with strong expertise in Large Language Models (LLMs), Generative AI, NLP, Computer Vision, and cloud technologies. The ideal candidate should be capable of designing and developing end-to-end AI-powered solutions while working closely with cross-functional teams to build scalable, production-ready applications.Key Responsibilities<ul><li>Design, develop, and deploy advanced solutions using Large Language Models (LLMs).</li><li>Take complete ownership of end-to-end solution development from design to deployment.</li><li>Research and stay updated with the latest advancements in Generative AI, LLMs, and AI frameworks.</li><li>Develop reusable code libraries, frameworks, and tools for AI application development.</li><li>Participate in code reviews and ensure adherence to coding standards and best practices.</li><li>Contribute across the complete Software Development Life Cycle (SDLC), including design, development, testing, deployment, and maintenance.</li><li>Collaborate with product managers, engineering teams, and stakeholders to integrate AI solutions into enterprise applications.</li><li>Analyze business problems and translate them into scalable AI-driven solutions.</li><li>Troubleshoot, optimize, and improve AI models and application performance.</li><li>Communicate effectively with technical and non-technical stakeholders.</li></ul>Required Skills1. Natural Language Processing (NLP)Hands-on experience in one or more of the following:<ul><li>Use case classification</li><li>Topic modeling</li><li>Question Answering (Q&amp;A)</li><li>Chatbots</li><li>Enterprise Search</li><li>Document AI</li><li>Text Summarization</li><li>Content Generation</li></ul>OR2. Computer Vision &amp; Audio AIHands-on experience in:<ul><li>Image classification</li><li>Object detection</li><li>Image segmentation</li><li>Image generation</li><li>Audio analysis</li><li>Video analysis</li></ul>Generative AI &amp; LLMsSaaS LLM PlatformsExperience with:<ul><li>LangChain</li><li>LlamaIndex</li><li>Vector Databases</li><li>Prompt Engineering (Chain of Thought, Tree of Thought, ReAct, AI Agents)</li><li>Azure OpenAI</li><li>Google Vertex AI</li><li>AWS Bedrock</li><li>Multi-modal AI (Text, Audio, Image, Video)</li></ul>Open Source LLMsKnowledge of:<ul><li>Hugging Face</li><li>TensorFlow</li><li>PyTorch</li><li>LLM Fine-tuning (PEFT)</li><li>RLHF (Reinforcement Learning from Human Feedback)</li><li>Quantization</li><li>Data Annotation Workflows</li><li>GPU Utilization and Optimization</li></ul>Cloud TechnologiesHands-on experience with one or more cloud platforms:<ul><li>Microsoft Azure</li><li>Amazon Web Services (AWS)</li><li>Google Cloud Platform (GCP)</li></ul>Preferred:<ul><li>Cloud Certification (Azure/AWS/GCP)</li></ul>Application Development SkillsStrong experience in:<ul><li>Python</li><li>Docker</li><li>FastAPI / Django / Flask</li><li>Git &amp; Version Control</li><li>REST APIs</li><li>Microservices Architecture</li></ul>Required Qualifications<ul><li>5.5&ndash;9 years of overall software development experience.</li><li>Strong experience in Generative AI and LLM-based application development.</li><li>Excellent analytical and problem-solving skills.</li><li>Strong communication and collaboration skills.</li><li>Ability to work independently and take ownership of projects.</li><li>Experience building scalable, production-ready AI applications.</li></ul>Preferred Skills<ul><li>Experience with RAG (Retrieval-Augmented Generation) architectures.</li><li>Knowledge of Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, Milvus, etc.).</li><li>Experience deploying AI applications on cloud platforms.</li><li>Exposure to MLOps and CI/CD pipelines.</li><li>Experience with AI Agents and Agentic AI frameworks.</li></ul>Pay: ₹2,500,000.00 - ₹3,600,000.00 per yearWork Location: Hybrid remote in Bangalore City, Bengaluru, Karnataka

Generative AI Engineer

Explore 68+ Agentic ai engineer in India this July. Find roles across top companies and apply now to boost your career.