21 Llamaindex Jobs

Roles and Responsibilities Design and develop data science solutions using Python. Experience in machine learning and deep learning frameworks (PyTorch, TensorFlow) Develop machine learning models using TensorFlow or PyTorch and deploy them on Kubernetes, MLflow, and KServe clusters. Familiarity with machine learning deployment and MLOps tools Experience working with model repositories and fine-tuning frameworks like Hugging Face. Experience with frameworks like LangGraph/LangChain. Design and implement AI agent workflows. Develop end-to-end intelligent pipelines and multi-agent systems (e.g., LangGraph/LangChain workflows) that coordinate multiple LLM-powered agents to solve complex tasks. Create graph-based or state-machine architectures for AI agents, chaining prompts and tools as needed. Build and fine-tune generative models. Develop, train, and fine-tune advanced generative models (transformers, diffusion models, VAEs, GANs, etc.) on domain-specific data. Deploy and optimize foundation models (such as GPT, LLaMA, Mistral) in production, adapting them to our use cases through prompt engineering and supervised fine-tuning.

Role & responsibilities: Work collaboratively with product and business teams to understand requirements Design and develop AI prototypes using LLMs such as Claude and GPT including AI Agents Implement solutions with frameworks like LangChain and other open-source tools Build end-to-end AI pipelines that integrate with existing systems Evaluate appropriate models and technologies for different use cases Document prototype architecture, performance, and learnings for handoff to product / engineering teams. Stay up to date with the latest AI research, libraries, and tools to enable experimentation. Required Qualifications: Bachelor's Degree in Computer Science, Engineering, or related technical field 3+ years of software development experience 1+ years of experience working with LLMs and AI frameworks Strong proficiency in Python and relevant AI/ML libraries Experience with LLM Orchestration frameworks (LangChain, LlamaIndex, etc.) Knowledge of prompt engineering techniques Understanding of vector databases and retrieval approaches Strong problem-solving skills and attention to detail Comfort with ambiguity and an iterative, fast-paced environment.

Responsibilities: * Design and implement AI solutions using GML, Neo4J, ArangoDB, LangChain, LLamaIndex, RAG. * Collaborate with cross-functional teams on ML projects with Python, PySpark, Pytorch, R, SQL.

Job Overview: We are seeking an experienced and passionate Technical Manager/Lead to spearhead our cutting-edge AI initiatives including Phoenix Ask , Phoenix Report Writer , and upcoming AI-powered features. This role will lead a team of 5 Senior Developers focused on developing, deploying, and maintaining advanced AI capabilities using state-of-the-art models and technologies. Key Responsibilities: Lead the design, development, and deployment of scalable AI features and tools. Manage and mentor a team of senior AI developers. Collaborate with cross-functional teams (Product, UX, DevOps) to deliver commercial-ready AI features. Architect AI-driven solutions using modern frameworks and cloud platforms. Ensure best practices in model selection, prompt engineering, fine-tuning, and evaluation. Deploy AI applications using Azure Foundry , AWS Bedrock , and similar platforms. Oversee integration of models like GPT-4o , GPT-o3 , Claude , and LLaMA into business products. Maintain robust documentation and ensure product scalability and performance. Required Skills & Experience: 5+ years of experience in AI/ML development with at least 2 years in a leadership role . Strong expertise in Langchain , Pydantic , and FastAPI . Experience working with MCP (Modular Code Platforms or Microsoft Cloud Platform clarify as needed). Proven hands-on experience with deploying models like GPT-4o, GPT-o3, Claude, LLaMA . Solid understanding of AI model training , fine-tuning , and industry-standard tools . Strong deployment experience on Azure Foundry and AWS Bedrock or equivalent cloud services. Ability to manage sprints, code reviews, and project delivery timelines. Preferred Qualifications: Master's/Bachelors degree in Computer Science, Artificial Intelligence, or related field. Experience in integrating AI with enterprise systems. Prior work on generative AI or natural language applications.

Proven experience in training Local Models like llama. Responsible for developing, deploying, and optimizing machine learning models. Expertise in AI, NLP, & deep learning will play a crucial role in improving customer interactions & automation Health insurance Provident fund

As a Manager, Machine Learning Engineering, you will collaborate with cross-functional teams to strategize, develop, and deliver machine learning models tailored to meet specific business objectives. You will be responsible for overseeing the entire lifecycle of these models, from data preprocessing and algorithm selection to performance evaluation and seamless integration into production systems. This role has a specific focus on Generative AI . Your Impact: What You'll Achieve As a Manager, Data Science specializing in Generative AI, you will: Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences. Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals. Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning. Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP , ensuring measurable outcomes. Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges. Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements. Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact. Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS, and Azure to address real-world business problems with precision and efficiency. Stay at the Cutting Edge: Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects. Responsibilities Design AI Systems: Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization. Develop NLP Pipelines: Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation. Integrate Multi-Modal Systems: Combine data modalities such as text, images, and metadata for enriched user interactions and insights. Optimize AI Pipelines: Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production. Collaborate on AI Innovation: Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions. Qualifications Your Skills & Experience Overall Experience: 8 to 15 years of experience. Generative AI Experience: At least 2 years of Gen AI experience . LLM Fine-tuning: Fine-tuning experience with Large Language Models (LLMs, VLLMs, or Vision models) . Distributed Training/Inference: Experience with distributed training or inference frameworks like Ray, vllm, openllm, bentoML etc. Generative AI Frameworks: Experience with frameworks like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. LLM Deployment/Optimization: Deployment experience or optimized hosting experience of Large Language Models (LLMs, VLLMs, or Vision models) . Vector Databases: Experience working with any Vector database like Milvus, FAISS, ChromaDB etc. Agent Development: Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc. Prompt Engineering: Experience with prompt engineering. Market Trends: Keeping up with latest market trends. Open Source LLMs: Experience working with open-source large language models from HuggingFace . Cloud Providers: Experience working with at least one public cloud provider such as Azure, AWS, or GCP . Container Technology: Experience working with container technology like Docker, ECS etc. DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines for data solutions. Production Deployment: Experience in deploying solutions to production with Kubernetes or OpenShift . ML Workflow Management: Experience with managing ML workflows with MLFlow or KubeFlow.

Here's a detailed overview of the Manager, Machine Learning Engineering (Specializing in Generative AI) role at Publicis Sapient in Hyderabad, Telangana, India: Company Description Publicis Sapient is a digital transformation partner that helps established organizations achieve their future, digitally-enabled state, both in how they work and how they serve their customers. They unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and creative problem-solving . United by their core values and purpose of helping people thrive in the brave pursuit of next, their 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate their clients businesses by designing the products and services their customers truly value. Overview: Manager, Machine Learning Engineering (Generative AI Specialist) Publicis Sapient is seeking an experienced Manager, Machine Learning Engineering to lead their talented team of AI and data science experts. In this influential role, you will be responsible for developing and implementing solutions that address complex business challenges across a wide range of industries, empowering clients to revolutionize their businesses by harnessing the potential of advanced technology. As a Manager, Machine Learning Engineering, you will collaborate with cross-functional teams to strategize, develop, and deliver machine learning models tailored to meet specific business objectives. You will be responsible for overseeing the entire lifecycle of these models, from data preprocessing and algorithm selection to performance evaluation and seamless integration into production systems. This role has a specific focus on Generative AI . Your Impact: What You'll Achieve As a Manager, Data Science specializing in Generative AI, you will: Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences. Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals. Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning. Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP , ensuring measurable outcomes. Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges. Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements. Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact. Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS, and Azure to address real-world business problems with precision and efficiency. Stay at the Cutting Edge: Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects. Responsibilities Design AI Systems: Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization. Develop NLP Pipelines: Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation. Integrate Multi-Modal Systems: Combine data modalities such as text, images, and metadata for enriched user interactions and insights. Optimize AI Pipelines: Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production. Collaborate on AI Innovation: Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions. Qualifications: Your Skills & Experience Overall Experience: 8 to 15 years of experience. Generative AI Experience: At least 2 years of Gen AI experience . LLM Fine-tuning: Fine-tuning experience with Large Language Models (LLMs, VLLMs, or Vision models) . Distributed Training/Inference: Experience with distributed training or inference frameworks like Ray, vllm, openllm, bentoML etc. Generative AI Frameworks: Experience with frameworks like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. LLM Deployment/Optimization: Deployment experience or optimized hosting experience of Large Language Models (LLMs, VLLMs, or Vision models) . Vector Databases: Experience working with any Vector database like Milvus, FAISS, ChromaDB etc. Agent Development: Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc. Prompt Engineering: Experience with prompt engineering. Market Trends: Keeping up with latest market trends. Open Source LLMs: Experience working with open-source large language models from HuggingFace . Cloud Providers: Experience working with at least one public cloud provider such as Azure, AWS, or GCP . Container Technology: Experience working with container technology like Docker, ECS etc. DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines for data solutions. Production Deployment: Experience in deploying solutions to production with Kubernetes or OpenShift . ML Workflow Management: Experience with managing ML workflows with MLFlow or KubeFlow .

Location: Bangalore Job Type: Contract Position overview: We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding

Team : Artificial Intelligence Centre of Excellence Role : ML Engineer Location : Bangalore/Chennai Job Type : Contract Experience Level : Bachelors/Masters degree in Data Science, Computer Science, or a related field from a reputed institute. Candidates with 1+ years of work experience preferred. Position overview: We are seeking a ML Engineer with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Role & responsibilities Design, develop, and deploy machine learning systems, including Generative AI models and LLMs. Research and implement state-of-the-art ML algorithms and tools. Conduct data preprocessing, feature engineering, and statistical analysis. Train, fine-tune, and optimize machine learning models for performance and accuracy. Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. Extend existing ML frameworks and libraries to meet project requirements. Stay updated with the latest advancements in machine learning and AI. Preferred candidate profile Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. - must have Experience in handling databases (SQL and NoSQL)

Customize Llama or leverage OpenAI to develop custom frameworks for investment management alternate data analysis Use Orchestration tools like N8n for document ingestion Setup on cloud or private using Coreweave Lead Machine Learning and UI Engineers Required Candidate profile 5+ years of development experience in .NET , Python and Azure 3+ years of experience in Data Science along with hands on GenAI and LLMs Experience with VectorDB, documentation ingestion workflows etc.

Job Description: Oracle Cloud Infrastructure (OCI) is a pioneering force in cloud technology, merging the agility of startups with the robustness of an enterprise software leader. Within OCI, the Oracle Generative AI Service team spearheads innovative solutions at the convergence of artificial intelligence and cloud infrastructure. As part of this team, you'll contribute to large-scale cloud solutions utilizing cutting-edge machine learning technologies, aimed at addressing complex global challenges. Join us to create innovative solutions using top-notch machine learning technologies to solve global challenges. We're looking for an experienced Principal Applied Data Scientist to join our OCI Gen-AI Solutions team for strategic customers. In this role, you'll collaborate with applied scientists and product managers to design, develop, and deploy tailored Gen-AI solutions with an emphasis on Large Language Models (LLMs), Agents, MPC and Retrieval Augmented Generation (RAG) with large OpenSearch clusters. As part of the OCI Gen AI and Data Solutions for strategic customers team, you will be responsible for developing innovative Gen AI and data services for our strategic customers.As a Principal Applied Data Scientist, you'll lead the development of advanced Gen AI solutions using the latest ML technologies combined with Oracle's cloud expertise. Your work will significantly impact sectors like financial services, telecom, healthcare, and code generation by creating distributed, scalable, high-performance solutions for strategic customers. Work directly with key customers and accompany them on their Gen AI journey - understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers. You will dive deep into model structure to optimize model performance and scalability. You will build state of art solutions with brand new technologies in this fast-evolving area. You will configure large scale OpenSearch clusters, setting up ingestion pipelines to get the data into the OpenSearch. You will diagnose, troubleshoot, and resolve issues in AI model training and serving. You may also perform other duties as assigned. Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Be an enthusiastic, self-motivated, and a great collaborator. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications and experience Bachelors or master's in computer science or equivalent technical field with 10+ years of experience Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations). Demonstrated experience in designing and implementing scalable AI models and solutions for production,relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams. Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming. Practical experience with setting up and finetuning large OpenSearch Clusters. Experience in setting up data ingestion pipelines with OpenSearch. Experience with search algorithms, indexing, optimizing latency and response times. Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts. Familiarity with Agents and Agent frameworks and Model Predictive Control (MPC) Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences. Ability and passion to mentor and develop junior machine learning engineers. Proficient in Python and shell scripting tools. Preferred Qualifications : Masters or Bachelor's in related field with 5+ years relevant experience Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus. Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus. Experience with semantic search, multi-modal search and conversational search. Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities.Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc. Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies. Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers. Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers). Experience in diagnosing, fixing, and resolving issues in AI model training and serving. Career Level - IC4

Hiring AI & Data Retrieval Engineer with expertise in NLQ, Text-to-SQL, LLMs, LangChain, pgVector, PostgreSQL, vector search, Python, AI libraries, Agentic AI & API integration. Exp with NLP, RAG, BI tools, live projects & LLM fine-tuning preferred.

Role & responsibilities Develop robust, secure, and scalable web applications using Django and Python. Design and implement RESTful APIs and integrate third-party APIs/services. Manage databases (PostgreSQL, MySQL) and ensure data integrity and security. Collaborate with front-end developers to ensure seamless integration with user-facing elements. Optimize applications for speed and scalability. Write unit tests and participate in code reviews to maintain high code quality. Maintain technical documentation and follow best practices in development and deployment. Troubleshoot, debug, and upgrade existing systems. Stay updated with emerging technologies and recommend improvements. Preferred candidate profile Bachelors degree in Computer Science, Engineering, or a related field. 4+ years of professional experience with Django and Python. Solid understanding of Django ORM and Django REST Framework (DRF). Experience with HTML, CSS, JavaScript, and templating engines like Jinja2. Familiarity with version control tools, especially Git. Working knowledge of relational databases and SQL. Experience with user authentication and authorization in Django. Understanding of MVC/MVT architecture. Strong problem-solving skills and attention to detail.

Job Summary Director, Collection Platforms and AI As a director, you will be essential to drive customer satisfaction by delivering tangible business results to the customers. You will be working for the Enterprise Data Organization and will be an advocate and problem solver for the customers in your portfolio as part of the Collection Platforms and AI team. You will be using communication and problem-solving skills to support the customer on their automation journey with emerging automation tools to build and deliver end to end automation solutions for them. Team Collection Platforms and AI Enterprise Data Organizations objective is to drive growth across S&P divisions, enhance speed and productivity in our operations, and prepare our data estate for the future, benefiting our customers. Therefore, automation represents a massive opportunity to improve quality and efficiency, to expand into new markets and products, and to create customer and shareholder value. Agentic automation is the next frontier in intelligent process evolution, combining AI agents, orchestration layers, and cloud-native infrastructure to enable autonomous decision-making and task execution. To leverage the advancements in automation tools, its imperative to not only invest in the technologies but also democratize them, build literacy, and empower the work force. The Collection Platforms and AI team's mission is to drive this automation strategy across S&P Global and help create a truly digital workplace. We are responsible for creating, planning, and delivering transformational projects for the company using state of the art technologies and data science methods, developed either in house or in partnership with vendors. We are transforming the way we are collecting the essential intelligence our customers need to do decision with conviction, delivering it faster and at scale while maintaining the highest quality standards. What were looking for ? You will lead the design, development, and scaling of AI-driven agentic pipelines to transform workflows across S&P Global. This role requires a strategic leader who can architect end-to-end automation solutions using agentic frameworks, cloud infrastructure, and orchestration tools while managing senior stakeholders and driving adoption at scale. A visionary technical leader with knowledge of designing agentic pipelines and deploying AI applications in production environments. Understanding of cloud infrastructure (AWS/Azure/GCP), orchestration tools (e.g., Airflow, Kubeflow), and agentic frameworks (e.g., LangChain, AutoGen). Proven ability to translate business workflows into automation solutions, with emphasis on financial/data services use cases. An independent proactive person who is innovative, adaptable, creative, and detailed-oriented with high energy and a positive attitude. Exceptional skills in listening to clients, articulating ideas, and complex information in a clear and concise manner. Proven record of creating and maintaining strong relationships with senior members of client organizations, addressing their needs, and maintaining a high level of client satisfaction. Ability to understand what the right solution is for all type of problems, understanding and identifying the ultimate value of each project. Operationalize this technology across S&P Global, delivering scalable solutions that enhance efficiency, reduce latency, and unlock new capabilities for internal and external clients. Exceptional communication skills with experience presenting to C-level executives Responsibilities Engage with the multiple client areas (external and internal) and truly understand their problem and then deliver and support solutions that fit their needs. Understand the existing S&P Global product to leverage existing products as necessary to deliver a seamless end to end solution to the client. Evangelize agentic capabilities through workshops, demos, and executive briefings. Educate and spread awareness within the external client-base about automation capabilities to increase usage and idea generation. Increase automation adoption by focusing on distinct users and distinct processes. Deliver exceptional communication to multiple layers of management for the client. Provide automation training, coaching, and assistance specific to a users role. Demonstrate strong working knowledge of automation features to meet evolving client needs. Extensive knowledge and literacy of the suite of products and services offered through ongoing enhancements, and new offerings and how they fulfill customer needs. Establish monitoring frameworks for agent performance, drift detection, and self-healing mechanisms. Develop governance models for ethical AI agent deployment and compliance. Preferred Qualification 12+ years work experience with 5+ years in the Automation/AI space Knowledge of: Cloud platforms (AWS SageMaker, Azure ML; etc) Orchestration tools (Prefect, Airflow; etc) Agentic toolkits (LangChain, LlamaIndex, AutoGen) Experience in productionizing AI applications. Strong programming skills in python and common AI frameworks Experience with multi-modal LLMs and integrating vision and text for autonomous agents. Excellent written and oral communication in English Excellent presentation skills with a high degree of comfort speaking with senior executives, IT Management, and developers. Hands-on ability to build quick prototype/visuals to assist with high level product concepts and capabilities. Experience in deployment and management of applications utilizing cloud-based infrastructure. A desire to work in a fast-paced and challenging work environment Ability to work in a cross functional, multi geographic teams

Job Summary Director, Collection Platforms and AI As a director, you will be essential to drive customer satisfaction by delivering tangible business results to the customers. You will be working for the Enterprise Data Organization and will be an advocate and problem solver for the customers in your portfolio as part of the Collection Platforms and AI team. You will be using communication and problem-solving skills to support the customer on their automation journey with emerging automation tools to build and deliver end to end automation solutions for them. Team Collection Platforms and AI Enterprise Data Organizations objective is to drive growth across S&P divisions, enhance speed and productivity in our operations, and prepare our data estate for the future, benefiting our customers. Therefore, automation represents a massive opportunity to improve quality and efficiency, to expand into new markets and products, and to create customer and shareholder value. Agentic automation is the next frontier in intelligent process evolution, combining AI agents, orchestration layers, and cloud-native infrastructure to enable autonomous decision-making and task execution. To leverage the advancements in automation tools, its imperative to not only invest in the technologies but also democratize them, build literacy, and empower the work force. The Collection Platforms and AI team's mission is to drive this automation strategy across S&P Global and help create a truly digital workplace. We are responsible for creating, planning, and delivering transformational projects for the company using state of the art technologies and data science methods, developed either in house or in partnership with vendors. We are transforming the way we are collecting the essential intelligence our customers need to do decision with conviction, delivering it faster and at scale while maintaining the highest quality standards. What were looking for ? You will lead the design, development, and scaling of AI-driven agentic pipelines to transform workflows across S&P Global. This role requires a strategic leader who can architect end-to-end automation solutions using agentic frameworks, cloud infrastructure, and orchestration tools while managing senior stakeholders and driving adoption at scale. A visionary technical leader with knowledge of designing agentic pipelines and deploying AI applications in production environments. Understanding of cloud infrastructure (AWS/Azure/GCP), orchestration tools (e.g., Airflow, Kubeflow), and agentic frameworks (e.g., LangChain, AutoGen). Proven ability to translate business workflows into automation solutions, with emphasis on financial/data services use cases. An independent proactive person who is innovative, adaptable, creative, and detailed-oriented with high energy and a positive attitude. Exceptional skills in listening to clients, articulating ideas, and complex information in a clear and concise manner. Proven record of creating and maintaining strong relationships with senior members of client organizations, addressing their needs, and maintaining a high level of client satisfaction. Ability to understand what the right solution is for all type of problems, understanding and identifying the ultimate value of each project. Operationalize this technology across S&P Global, delivering scalable solutions that enhance efficiency, reduce latency, and unlock new capabilities for internal and external clients. Exceptional communication skills with experience presenting to C-level executives Responsibilities Engage with the multiple client areas (external and internal) and truly understand their problem and then deliver and support solutions that fit their needs. Understand the existing S&P Global product to leverage existing products as necessary to deliver a seamless end to end solution to the client. Evangelize agentic capabilities through workshops, demos, and executive briefings. Educate and spread awareness within the external client-base about automation capabilities to increase usage and idea generation. Increase automation adoption by focusing on distinct users and distinct processes. Deliver exceptional communication to multiple layers of management for the client. Provide automation training, coaching, and assistance specific to a users role. Demonstrate strong working knowledge of automation features to meet evolving client needs. Extensive knowledge and literacy of the suite of products and services offered through ongoing enhancements, and new offerings and how they fulfill customer needs. Establish monitoring frameworks for agent performance, drift detection, and self-healing mechanisms. Develop governance models for ethical AI agent deployment and compliance. Preferred Qualification 12+ years work experience with 5+ years in the Automation/AI space Knowledge of: Cloud platforms (AWS SageMaker, Azure ML; etc) Orchestration tools (Prefect, Airflow; etc) Agentic toolkits (LangChain, LlamaIndex, AutoGen) Experience in productionizing AI applications. Strong programming skills in python and common AI frameworks Experience with multi-modal LLMs and integrating vision and text for autonomous agents. Excellent written and oral communication in English Excellent presentation skills with a high degree of comfort speaking with senior executives, IT Management, and developers. Hands-on ability to build quick prototype/visuals to assist with high level product concepts and capabilities. Experience in deployment and management of applications utilizing cloud-based infrastructure. A desire to work in a fast-paced and challenging work environment Ability to work in a cross functional, multi geographic teams

Technical Lead (Enterprise AI Systems) We are seeking a Technical Lead to drive the design and development of our enterprise-grade AI product. This role requires a deep understanding of AI/ML systems, cloud-native architectures, and scalable software design. The applicant should have mandatorily worked on enterprise grade AI product or project for at least 2 - 3 years. This role includes at least 50% hands on development, 30% LLD and the remaining 20% of HLD / Architecture. The role is on the technical career path and is NOT suitable for project managers, technical managers, engineering managers etc. Key Responsibilities: Develop scalable, modular, and secure AI-driven software systems. Design APIs, microservices, and cloud infrastructure for AI workloads. Ensure seamless AI model integration and efficient scaling. Optimize performance & scalability of systems. Implement caching, load balancing, and distributed computing. Ensure security compliance (GDPR, SOC2) and secure data handling. Enforce best practices in authentication, encryption, and API security. Mandatory Skills & Qualifications: Experience: 8 - 12 years in software architecture & design, with at least 3+ years focused on AI/ML product design & development. Last 1 - 2 years should include deep Gen AI experience in enterprise grade AI projects or applications. Experience with design and developing applications with LLMs, RAG Applications, Gen AI Agents. Fine-tuning open-source LLMs. Experience with deploying and monitoring LLMs. Experience with LLM evaluation frameworks or tools like DeepEval, Langfuse or similar. Experience with frameworks like langchain, llamaindex, pydantic etc. Proficiency in RDBMS like PostgreSQL and knowledge of vector databases (eg: chromadb,Pinecone, FAISS, Weaviate). Strong background in microservices, RESTful & GraphQL APIs, event-driven architectures, Working experience with Kafka, RabbitMQ etc... Proficient in Python, Java for backend development Experience with TensorFlow, PyTorch, Hugging Face etc... Skilled in data processing (NumPy, Pandas, Dask,NLTK) and front-end (TypeScript, React.js). Experience in scalable AI systems, data pipelines, MLOps, and real-time inference. Strong understanding of security protocols, IAM, OAuth2, JWT, RBAC. Expertise in cloud platforms (AWS, GCP, Azure), Kubernetes, Docker. Hands-on experience with CI/CD (Eg: github,Jenkins etc...) Hands-on with system monitoring (Eg: ELK Stack,OpenTelemetry, Prometheus, Grafana). Nice-to-Have Skills: Ensuring AI model interpretability, fairness, and bias mitigation strategies. Optimizing model inference using quantization, distillation, and pruning techniques. Experience in deploying AI models in production at scale, including MLOps best practices. Designing AI systems with privacy-preserving techniques (differential privacy, homomorphic encryption etc.). Experience with knowledge graph-based AI applications.

Company Name: Karini AI Job Title: Generative AI Engineer Location: Wakad, Pune (Onsite) Employment Type: Full-time Job Overview: Karini AI is looking for a highly motivated and skilled Generative AI Engineer to join our AI team. The ideal candidate should have expertise in Large Language Models (LLMs), Machine Learning (ML), and Deep Learning . We are looking for problem solvers, collaborative team players, and passionate individuals eager to work on cutting-edge AI technologies. If you aspire to be part of an innovative team and accelerate your career in AI, this is the perfect opportunity for you! Roles & Responsibilities: Collaborate with researchers, engineers, and domain experts to design, develop, and optimize Agentic AI applications . Fine-tune LLMs on large-scale datasets to enhance performance and accuracy. Develop compelling demos and lead proof-of-concept (PoC) projects. Stay updated with the latest research advancements in Generative AI and implement best practices. Deploy large-scale machine learning models in cloud-based environments. Mandatory Technical Skills: Hands-on experience in Generative AI and Deep Learning . Advanced knowledge of prompt engineering . Strong experience in PyTorch and working with GPUs . Proficiency in Python (Intermediate to Advanced level). Understanding of model fine-tuning and distributed computing in the cloud. Eligibility Criteria: Bachelors degree in Computer Science, AI, or a related field (4-year program). Masters degree in Artificial Intelligence or a related domain (preferred). Proven experience working as an AI Engineer with a strong foundation in Generative AI . Proficiency in deep learning frameworks and NLP techniques. Experience with cloud-based infrastructure for deploying machine learning models. Key Skills: Generative AI, Deep Learning, Machine Learning, Natural Language Processing (NLP), PyTorch, Python, Cloud Computing, LLM Fine-Tuning .

Job Details: Experience - 6 to 12 yrs Mandatory Skills - Machine Learning & NLP, RAG & Text-to-SQL Azure Cloud. Model Optimization & Fine-Tuning, Python (LangChain, LlamaIndex), Data Analytics & SQL Location - Mumbai, Pune, Bangalore, Chennai, Hyderabad and Kolkata location. Notice - Immediate to 30 days Job Summary: Develop and optimize AI models for business-specific use cases. Perform data analysis, feature engineering, and model training. Implement and fine-tune NLP and machine learning algorithms. Evaluate model performance and ensure continuous improvements. Work with engineers to deploy models in production environments.

Full stack Developer with AI (AM) BLR / GGN / Noida J48771 Job Description- Fullstack Developers with GenAI experience in Azure or GCP ecosystems Expert in building large scale secure chat-based web applications Expert in setting up RAG and ingestion pipelines from source (e.g. sharepoint) to vector store (e.g. cogsearch) Expert in Python, Flask, FastAPI, LlamaIndex, Langchain, React, Angular, Vue. Fluent in Document Intelligent, API Management, Function/Logic Apps, Cosmo DB Strong problem-solving skills and attention to details Required Candidate profile Candidate Experience Should Be : 7 To 10 Candidate Degree Should Be : BE-Comp/IT,BE-Other,BTech-Comp/IT,BTech-Other,MBA,MCA

Key Responsibilities: Lead the design, development, and deployment of AI/ML models, including deep learning, NLP, computer vision, and generative AI. Research and experiment with various AI models, including transformer-based architectures (GPT, BERT, T5), diffusion models, LLMs, and reinforcement learning models. Optimize and fine-tune models for performance, scalability, and cost-effectiveness. Integrate AI solutions into cloud-based platforms (AWS, Azure, GCP) and on-premise environments. Work with data engineers and MLOps teams to ensure seamless data pipelines and model deployment. Evaluate the latest AI advancements and recommend adoption strategies for cutting-edge models. Mentor and guide junior AI engineers, providing technical leadership and code reviews. Collaborate with cross-functional teams, including product managers, designers, and software engineers, to align AI solutions with business goals. Ensure AI models comply with ethical AI principles, security standards, and regulatory guidelines. Role & responsibilities Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field. 7+ years of hands-on experience in AI/ML, including model training, fine-tuning, and deployment. Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, Keras. Experience working with transformer models (GPT, BERT, Llama), computer vision models (YOLO, CLIP), and generative models (Stable Diffusion, GANs). Proficiency in Python and AI/ML libraries (NumPy, Pandas, Scikit-learn, Hugging Face). Hands-on experience with MLOps tools such as MLflow, Kubeflow, or SageMaker. Strong knowledge of cloud services (AWS Sagemaker, Azure AI, Google Vertex AI) and model deployment strategies. Experience with vector databases (FAISS, Pinecone) and LLM orchestration frameworks (LangChain, LlamaIndex). Excellent problem-solving skills and the ability to troubleshoot AI model issues. Strong communication and leadership skills to guide teams and present AI solutions to stakeholders. Preferred candidate profile Perks and benefits

About the role PubMatic is seeking Data Analytics-focused Senior Software Engineers with expertise in building and optimizing AI agents, including strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, with proficiency in programming languages such as Scala and Python. You will be responsible for developing advanced AI agents that enhance our data analytics capabilities, enabling our platform to handle complex information retrieval, contextual understanding, and adaptive interactions, ultimately improving our data-driven insights and analytical workflows. What You'll Do Build, design, and implement our highly scalable, fault-tolerant big data platform to process terabytes of data and provide customers with in-depth analytics. Develop backend services using Java, REST APIs, JDBC, and AWS. Build and maintain Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Architect and implement real-time data processing workflows and automation frameworks. Design and develop GenAI-powered agents for analytics, operations, and data enrichment use cases using frameworks like LangChain, LlamaIndex, or custom orchestration systems. Integrate LLMs (e.g., OpenAI, Claude, Mistral) into existing services for query understanding, summarization, and decision support. Manage end-to-end GenAI workflows including prompt engineering, fine-tuning, vector embeddings, and retrieval-augmented generation (RAG). Working closely with cross-functional teams on improving the availability and scalability of large data platforms and the functionality of PubMatic software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, and work item prioritization. Frequently discuss with product managers about the software features to include in the PubMatic Data Analytics platform. Support customer issues over email or JIRA (bug tracking system), provide updates, and patches to customers to fix the issues. Perform code and design reviews for code implemented by peers or as per the code review process. We'd Love for You to Have Three to six years of coding experience in Java and backend development. Solid computer science fundamentals, including data structure and algorithm design, and creation of architectural specifications. Expertise in developing the Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews. Hands-on experience with Big Data tools and systems like Scala Spark, Kafka, Hadoop, and Snowflake. Proven expertise in building GenAI applications, including: LLM integration (OpenAI, Anthropic, Cohere, etc.) LangChain, or similar agent orchestration libraries Prompt engineering, embeddings, and retrieval-based generation (RAG) Experience in developing and deploying scalable, production-grade AI or data systems. Ability to lead end-to-end feature development and debug distributed systems. Experience in developing and delivering large-scale big data pipelines, real-time systems & data warehouses would be preferred. Demonstrated ability to achieve stretch goals in a very innovative and fast-paced environment. Demonstrated ability to learn new technologies quickly and independently. Excellent verbal and written communication skills, especially in technical communications. Strong interpersonal skills and a desire to work collaboratively. Qualifications Should have a bachelor's degree in engineering (CS / IT) or equivalent degree from a well-known institute/university. Apply to the link below: https://pubmatic.com/job/?gh_jid=4692032008