90 Llamaindex Jobs

You will be working as an AI Platform Engineer in Bangalore as part of the GenAI COE Team. Your key responsibilities will involve developing and promoting scalable AI platforms for customer-facing applications. It will be essential to evangelize the platform with customers and internal stakeholders, ensuring scalability, reliability, and performance to meet business needs. Your role will also entail designing machine learning pipelines for experiment management, model management, feature management, and model retraining. Implementing A/B testing of models and designing APIs for model inferencing at scale will be crucial. You should have proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. As an AI Platform Engineer, you will serve as a subject matter expert in LLM serving paradigms, with in-depth knowledge of GPU architectures. Expertise in distributed training and serving of large language models, along with proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM, will be required. Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results will be part of your responsibilities. Reducing training and resource requirements for fine-tuning LLM and LVM models will also be essential. Having extensive knowledge of different LLM models and providing insights on their applicability based on use cases is crucial. You should have proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. Your proficiency in DevOps and LLMOps practices, along with knowledge of Kubernetes, Docker, and container orchestration, will be necessary. A deep understanding of LLM orchestration frameworks such as Flowise, Langflow, and Langgraph is also required. In terms of skills, you should be familiar with LLM models like Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, and Llama, as well as LLM Ops tools like ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, and Azure AI. Additionally, knowledge of databases/data warehouse systems like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, and Google BigQuery, as well as cloud platforms such as AWS, Azure, and GCP, is essential. Proficiency in DevOps tools like Kubernetes, Docker, FluentD, Kibana, Grafana, and Prometheus, along with cloud certifications like AWS Professional Solution Architect and Azure Solutions Architect Expert, will be beneficial. Strong programming skills in Python, SQL, and Javascript are required for this full-time role, with an in-person work location.,

???? Were Hiring: AI Engineer ???? Location: Bengaluru (Regular office-based role) ???? Employment Type: Full-Time | 5 Days a Week from Office ???? Qualification: B.E / B.Tech or equivalent degree in Computer Science, IT, or related field Are you passionate about building and scaling production-grade AI/ML systems We&aposre looking for a skilled AI Engineer to join our team in Bengaluru and help drive real-world impact through cutting-edge machine learning and GenAI technologies. ???? Must-Have Skills: 48 years of hands-on experience in designing, building, and deploying production-grade AI/ML solutions Proficiency in Python, PySpark, SQL , and ML libraries like Scikit-learn, XGBoost, LightGBM Cloud-native ML development experience on AWS (SageMaker), GCP (Vertex AI), or Azure ML Strong background in NLP/GenAI frameworks: Hugging Face, LangChain, LlamaIndex Practical knowledge of MLOps tools (MLflow, Weights & Biases, DVC) and deployment frameworks ( FastAPI, Flask, Docker, Kubernetes ) Excellent communication, stakeholder engagement, and team collaboration skills Good-to-Have: Publications, blog posts, or open-source contributions in AI/ML Experience leading AI strategy or owning technical roadmaps Show more Show less

At CoffeeBeans Consulting, we are a dynamic software consulting firm helping clients solve complex problems through innovative technology solutions. Were expanding our Data & AI practice and looking for a Lead Consultant Data & AI to help us build and deliver high-impact data and AI projects for our clients. Role Overview: Were looking for a hands-on technical leader who combines deep expertise in AI/ML (traditional ML and GenAI) with strong skills in modern data engineering and architecture . This role is: Hands-on engineering and architecture, building and implementing solutions. Client-facing consulting, understanding business problems and translating them into technical solutions. Mentoring and guiding junior team members, fostering a high-performance team culture. You will work closely with clients to design, build, and deliver impactful Data & AI solutions while establishing best practices and maintaining a high bar for technical quality. Key Responsibilities: Solution Design & Delivery Architect and implement end-to-end AI/ML solutions , including: Data pipelines and scalable data architectures. Traditional ML models and workflows. GenAI and agentic AI systems, including retrieval-augmented generation (RAG) and LLM-based applications. Ensure delivery of high-quality, scalable, and maintainable solutions aligned with client needs. Establish and advocate best practices for MLOps and data engineering workflows. Consulting & Client Engagement Act as a trusted technical advisor for clients, shaping their Data & AI strategy and roadmaps. Translate business problems into technical solutions with clear articulation of value. Facilitate technical discussions and workshops with stakeholders to gather requirements and guide solutions. Technical Leadership Lead by example, contributing hands-on to critical parts of projects. Set code and architectural standards for AI and data projects. Stay current with industry trends and advancements in AI/ML, GenAI, and data engineering. Team Development Mentor and upskill junior engineers and data scientists within the team. Foster a collaborative, inclusive, and supportive team environment. Support the hiring and onboarding of new team members as we grow our Data & AI capability. Key Requirements: ? Experience: 1012 years in the software/technology industry. Minimum 5+ years of experience designing and building AI/ML solutions in production environments. Strong experience with data engineering and architecture in production systems. Experience working in consulting or client-facing delivery environments . ? Technical Skills: Deep knowledge of traditional ML (classification, regression, NLP, computer vision) and GenAI (LLMs, embeddings, RAG, agentic AI workflows). Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, LangChain/LlamaIndex). Proficiency in Python (and/or R, Scala) for data and AI workloads. Experience with data engineering tools and orchestration frameworks (Spark, Databricks, Kafka, Airflow). Strong familiarity with cloud platforms (AWS, GCP, Azure) for deploying AI and data solutions. Understanding of MLOps practices (CI/CD for ML, monitoring, model retraining pipelines). Experience with data modeling, data lakes, and data pipeline architecture . ? Leadership & Mindset: Ability to lead and mentor technical teams in delivery environments. A consulting mindset with the ability to communicate effectively with technical and non-technical stakeholders. Empathetic leadership style, fostering trust and team growth. Comfortable in fast-paced, dynamic, client-facing environments. Nice to Have: Experience with LLM fine-tuning and optimization. Strong hands-on experience with Databricks for scalable data and AI workloads. Exposure to agentic AI frameworks and advanced orchestration for LLM-powered workflows. Certifications in cloud or AI/ML specializations. Experience in growing Data & AI teams within a consulting environment. Why Join Us Opportunity to shape and expand our Data & AI practice from the ground up. Work with diverse clients to solve meaningful and challenging problems. Be part of a collaborative, people-first culture with a focus on growth and learning. Competitive compensation and career advancement opportunities. Show more Show less

You will be part of a team that is developing an enterprise-grade, AI-powered agentic platform for the recruitment industry. Your role as a technical Co-Founder (CTO) will involve leading the development journey and defining the technical vision and architecture of the product from the ground up. Your responsibilities will include: - Defining and executing the technology strategy, roadmap, architecture, and infrastructure for a scalable, secure, and high-performing platform. - Leading hands-on development of the core platform, including AI agent integration, workflow automation, and data interaction layers. - Architecting and implementing LLM-based agentic features using tools like LangChain, OpenAI APIs, RAG pipelines, and vector databases. - Hiring, managing, and mentoring a high-performing engineering team across frontend, backend, ML, and DevOps. - Designing systems to handle large datasets, including data pipelines, analytics, and secure storage solutions. - Overseeing CI/CD pipelines, cloud infrastructure, monitoring, and cost-optimized deployments using AWS/GCP/Azure. The ideal candidate will have: - Proven experience in building and scaling enterprise-level web or mobile apps, preferably from 0 to 1. - Strong skills in Python/Django or Node.js, and modern JS frameworks such as React or Vue. - Deep experience with LLM integration, AI frameworks like LangChain and LlamaIndex, and vector databases like Pinecone and FAISS. - Solid understanding of database architecture, distributed systems, and API-first product development. - Past experience in leading or managing engineering teams. - Experience working in or co-founding an early-stage startup (preferred but not mandatory). Nice to have qualifications include: - Experience with multi-agent orchestration platforms like AutoGen, CrewAI, or AutoGPT. - Exposure to SaaS security, compliance, and data governance. - Knowledge of MLOps and deployment of AI models in production.,

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence. Tezo is seeking passionate AI Engineers who are excited about harnessing the power of Generative AI to transform the company and provide cutting-edge solutions for clients. Join us in revolutionizing enterprises by building intelligent, generative solutions that leverage AI/ML. If you've ever dreamed of contributing to impactful projects on a large scale, this is the opportunity for you! In this role, you will be an integral part of the Machine Learning Platforms/Data Science team, focusing on developing, testing, and deploying generative AI models. We actively respond to customers" evolving needs with innovative solutions, foster a positive and engaging work environment where collective ideas thrive, take ownership of our performance, maximize potential through continuous learning and improvement, and empower individuals to make informed decisions and take calculated risks. Job Summary: We are looking for a dedicated Data Scientist (Senior level) with a strong background in Generative AI to join our team. You will support product, leadership, and client teams by providing insights derived from advanced data analysis and generative modeling. In this role, you will collaborate closely with the development team, architects, and product owners to build efficient generative models and manage their lifecycle using the appropriate technology stack. Core Requirements: - 5+ years of experience working as a Data Scientist. - Proven experience in building production-grade Retrieval-Augmented Generation (RAG) solutions with hands-on experience with advanced RAG techniques for retrieval, re-ranking, etc. - Build GenAI applications using LangChain, LlamaIndex, and familiarity with Vector Stores and Large Language Models. - Experience in fine-tuning Large Language Models (LLMs) for business use cases will be preferred. - Minimum of 4 years of experience in developing end-to-end classical machine learning and NLP projects. - Demonstrated experience in deploying ML solutions in production using cloud services like Azure, AWS. - Business Understanding, Stakeholder management, and Team leading skills. - Strong practical expertise in Python and SQL needed for data science projects. Join us at Tezo to be part of a dynamic team committed to driving innovation through Generative AI solutions!,

As a LLM Engineer at HuggingFace, you will play a crucial role in bridging the gap between advanced language models and real-world applications. Your primary focus will be on fine-tuning, evaluating, and deploying LLMs using frameworks such as HuggingFace and Ollama. You will be responsible for developing React-based applications with seamless LLM integrations through REST, WebSockets, and APIs. Additionally, you will work on building scalable pipelines for data extraction, cleaning, and transformation, as well as creating and managing ETL workflows for training data and RAG pipelines. Your role will also involve driving full-stack LLM feature development from prototype to production. To excel in this position, you should have at least 2 years of professional experience in ML engineering, AI tooling, or full-stack development. Strong hands-on experience with HuggingFace Transformers and LLM fine-tuning is essential. Proficiency in React, TypeScript/JavaScript, and back-end integration is required, along with comfort working with data engineering tools such as Python, SQL, and Pandas. Familiarity with vector databases, embeddings, and LLM orchestration frameworks is a plus. Candidates with experience in Ollama, LangChain, or LlamaIndex will be given bonus points. Exposure to real-time LLM applications like chatbots, copilots, or internal assistants, as well as prior work with enterprise or SaaS AI integrations, are highly valued. This role offers a remote-friendly environment with flexible working hours and a high-ownership opportunity. Join our small, fast-moving team at HuggingFace and be part of building the next generation of intelligent systems. If you are passionate about working on impactful AI products and have the drive to grow in this field, we would love to hear from you.,

As a member of our team, you will be responsible for applying NLP technologies to address business challenges. Your role will involve collaborating with different stakeholders within the organization to gain insights into the business problems at hand. Using your expertise in NLP, you will be developing solutions that leverage the latest technologies in this field. To excel in this position, you should have a solid foundation in statistics, machine learning, and deep learning specifically tailored for text and speech data. Your experience in natural language processing will be crucial as you engage in tasks such as textual data processing, training, and evaluating deep learning models including Transformer based models like Bert and GPT. We are looking for individuals with strong problem-solving abilities and proficiency in programming, particularly in Python. Familiarity with a range of NLP toolkits such as Langchain, LlamaIndex, Huggingface Transformers, Spacy, CoreNLP, OpenNLP will be advantageous. Additionally, experience in utilizing cloud services like AWS or Azure will be a valuable asset in this role.,

We seek a Senior AI Developer skilled in OpenAI (GPT-4/GPT-4o) and Google Gemini to build advanced AI apps and agents. You'll lead LLM integrations, RAG pipelines, and GenAI solutions across industries in a fast-paced, innovative product team. Required Candidate profile 4+ yrs dev exp in GenAI/LLMs. Proficient in OpenAI, Gemini, Python, LangChain, vector DBs. Strong in RAG, prompt engineering, chatbot, cloud. Bonus: experience with Whisper, Gemini Pro, Hugging Face

Define and implement model validation processes and business success criteria in data science terms . Contribute to the architecture and data flow for machine learning models. Rapidly develop and iterate minimum viable solutions (MVS) that address enterprise needs. Conduct advanced data analysis and rigorous testing to enhance model accuracy and performance. Work with Data Architects to leverage existing data models and create new ones as required. Collaborate with product teams and business partners to industrialize machine learning models into Ericsson s enterprise solutions . Build MLOps pipelines for continuous integration, continuous delivery, validation, and monitoring of AI/ML models. Design and implement effective big data storage and retrieval strategies (indexing, partitioning, etc.). Develop and maintain APIs for AI/ML models and optimize data pipelines. Lead end-to-end ML projects from conception to deployment. Stay updated on the latest ML advancements and apply best practices to enterprise AI solutions . Required Skills Experience 4-6 years of hands-on experience in machine learning, AI, and data science . Strong knowledge of ML frameworks (Keras, TensorFlow, Spark ML, etc.). Proficiency in ML algorithms, deep learning, reinforcement learning (RL), and large language models (LLMs) . Expertise in MLOps , including model lifecycle management and monitoring. Experience with containerization orchestration (Docker, Kubernetes, Helm charts). Hands-on expertise with workflow orchestration tools (Kubeflow, Airflow, Argo). Strong programming skills in Python and experience with C++, Scala, Java, R . Experience in API design development for AI/ML models . Hands-on knowledge of Terraform for infrastructure automation. Familiarity with AWS services (Data Lake, Athena, SageMaker, OpenSearch, DynamoDB, Redshift). Strong understanding of self-hosted deployment of LLMs on AWS . Experience in RASA, LangChain, LangGraph, LlamaIndex, Django, Open Policy Agent . Working knowledge of vector databases, knowledge graphs, retrieval-augmented generation (RAG), agents, and agentic mesh architectures . Expertise in monitoring tools like Datadog for K8S environments. Ability to document, present , and communicate technical findings to business stakeholders . Proven ability to contribute to ML forums, patents, and research publications . Educational Qualifications B.Tech/B.E. in Computer Science , MCA, or a Master s in Mathematics/Statistics from a top-tier institute .

As a GenAI Engineer, you will be responsible for architecting and developing Generative AI-based applications using Azure OpenAI, Azure ML Studio, Azure Cognitive Search, and Azure Document Intelligence. Your role will involve building and optimizing Retrieval-Augmented Generation (RAG) pipelines for enterprise search, knowledge management, and domain-specific Q&A systems. You will integrate Large Language Models (LLMs) into production applications while ensuring performance, scalability, and governance. Designing intelligent workflows using LangChain, LlamaIndex, and Semantic Kernel for orchestrating multi-step AI interactions and agent behaviors will be a key aspect of your responsibilities. Collaboration with data scientists, ML engineers, and DevOps to deploy, monitor, and manage cloud-native AI solutions is essential. Additionally, you will incorporate OCR capabilities and document understanding pipelines using Azure Form Recognizer and Document Intelligence, ensuring compliance with enterprise standards, data privacy, and responsible AI principles. Leading proof-of-concepts (PoCs), rapid prototypes, and solution demos to validate GenAI use cases across departments is also part of your role. Maintaining a strong understanding of evolving LLM architectures, foundation models, and emerging GenAI techniques, as well as contributing to technical documentation, best practices, and reusable solution accelerators, are crucial aspects of the job. The ideal candidate for this position should hold a Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proven experience with Azure AI services, including Azure OpenAI, Azure Machine Learning Studio, Azure Cognitive Search, and Azure Form Recognizer / Document Intelligence is required. Strong Python development skills, especially in the context of LLM pipelines and prompt engineering, are essential. Expertise with GenAI libraries and tools such as LangChain, LlamaIndex, and Semantic Kernel is highly desirable. Familiarity with RAG architecture, vector databases (e.g., FAISS, Redis, Azure Cognitive Search), and embedding models is a plus. Experience with containerization (Docker) and cloud-native deployment pipelines using Azure DevOps, Kubernetes, or Terraform is preferred. An understanding of Responsible AI principles, including bias mitigation, explainability, and model monitoring, is necessary. Excellent problem-solving and communication skills are also required, along with the ability to work in cross-functional agile teams. Preferred qualifications for this role include experience integrating agent-based frameworks for autonomous task execution and multi-agent collaboration, as well as knowledge of other GenAI ecosystems like Hugging Face Transformers, Anthropic Claude, or Mistral models. A background in enterprise content management, knowledge graphs, or intelligent document processing (IDP) would be beneficial. Azure certifications such as Microsoft Certified: Azure AI Engineer Associate and Microsoft Certified: Azure Solutions Architect Expert are a plus. In return, we offer you the opportunity to work on groundbreaking AI initiatives at an enterprise scale. You will be part of a collaborative, fast-paced, and innovation-driven team culture, with flexible work arrangements (remote/hybrid), competitive compensation, equity options, and comprehensive benefits.,

As a skilled professional, your primary responsibility will involve designing and implementing cutting-edge deep learning models using frameworks like PyTorch and TensorFlow to tackle specific business challenges. You will be tasked with creating conversational AI agents and chatbots that provide seamless, human-like interactions, tailored to meet client needs. Additionally, you will develop and optimize Retrieval-Augmented Generation (RAG) models to enhance AI's ability to retrieve and synthesize pertinent information for accurate responses. Your expertise will be leveraged in managing data lakes, data warehouses (including Snowflake), and utilizing Databricks for large-scale data storage and processing. You are expected to have a thorough understanding of Machine Learning Operations (MLOps) practices and manage the complete lifecycle of machine learning projects, from data preprocessing to model deployment. You will play a crucial role in conducting advanced data analysis to extract actionable insights and support data-driven strategies across the organization. Collaborating with stakeholders from various departments, you will align AI initiatives with business requirements to develop scalable solutions. Additionally, you will mentor junior data scientists and engineers, encouraging innovation, skill enhancement, and continuous learning within the team. Staying updated on the latest advancements in AI and deep learning, you will experiment with new techniques to enhance model performance and drive business value. Effectively communicating findings to both technical and non-technical audiences through reports, dashboards, and visualizations will be part of your responsibilities. Furthermore, you will utilize cloud platforms like AWS Bedrock to deploy and manage AI models at scale, ensuring optimal performance and reliability. Your technical skills should include hands-on experience with PyTorch, TensorFlow, and scikit-learn for deep learning and machine learning tasks. Proficiency in Python or R programming, along with knowledge of big data technologies like Hadoop and Spark, is essential. Familiarity with MLOps, data handling tools such as pandas and dask, and cloud computing platforms like AWS is required. Skills in LLAMAIndex and LangChain frameworks, as well as data visualization tools like Tableau and Power BI, are desirable. To qualify for this role, you should hold a Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. Specialization in deep learning, significant experience with PyTorch and TensorFlow, and familiarity with reinforcement learning, NLP, and generative models are expected. In addition to challenging work, you will enjoy a friendly work environment, work-life balance, company-sponsored medical insurance, a 5-day work week with flexible timings, frequent team outings, and yearly leave encashment. This exciting opportunity is based in Ahmedabad.,

We are seeking a highly skilled LLM Engineer with deep expertise in chatbot implementations and large language models (LLMs) . The ideal candidate should have hands-on experience with Retrieval-Augmented Generation (RAG) , instruction fine-tuning , parameter-efficient fine-tuning (PEFT) techniques such as LoRA or QLoRA , and proficiency in frameworks like LangChain , LlamaIndex , Haystack , Rasa , or their equivalents. The role requires experience in designing and implementing at least two chatbot projects end-to-end, coupled with a strong understanding of requirement analysis, architecture planning , and solution strategy formulation . Bonus points for experience with Vision-Language Models (VLMs) and multimodal AI applications integrating text, image, video, and audio data. Key Responsibilities Design, architect, and develop intelligent chatbot systems using state-of-the-art LLM techniques. Analyze business and functional requirements and translate them into scalable LLM solutions. Implement Retrieval-Augmented Generation (RAG) pipelines using relevant libraries and vector databases. Apply instruction fine-tuning and PEFT techniques like LoRA/QLoRA for domain-specific customization. Build LLM applications using frameworks such as LangChain , LlamaIndex , Haystack , or Rasa . Integrate chatbots with enterprise systems, APIs, and document stores. Work with vector databases (e.g., Pinecone, FAISS, Weaviate, ChromaDB) and embedding models. Collaborate cross-functionally with design, product, and engineering teams for integration and deployment. (Preferred) Develop multimodal systems that process combinations of text, audio, video, and images. Stay up to date with the latest research in conversational AI, LLMs, and multimodal AI. Document technical architecture, processes, and best practices. Required Qualifications Bachelor's or Masters in Computer Science, Artificial Intelligence, Data Science, or equivalent. 6 to 9 years of total experience in software/AI development with minimum 2+ chatbot projects delivered using LLMs. Proficiency in RAG , instruction tuning , and parameter-efficient fine-tuning (LoRA/QLoRA) techniques. Strong expertise in one or more frameworks: LangChain , LlamaIndex , Haystack , Rasa , etc. Solid programming skills in Python and familiarity with Transformers , PyTorch , or TensorFlow . Experience with vector databases , embedding models , and NLP pipelines . Ability to understand business needs and independently drive solution strategy and implementation. Excellent communication and stakeholder engagement skills. Preferred Qualifications Exposure to multimodal AI and Vision-Language Models (VLMs) such as Flamingo, GPT-4V, or Kosmos. Experience with MLOps tools and deploying LLMs into scalable production environments. Understanding of prompt engineering, few-shot learning, and performance optimization for LLMs. Familiarity with model evaluation metrics specific to conversational and generative tasks. Soft Skills Strong analytical and problem-solving mindset. Self-motivated with the ability to take initiative and ownership. Effective communicator with the ability to translate complex technical concepts into business outcomes. Comfortable working in agile, fast-paced environments

You will be working full-time at Soothsayer Analytics in Hyderabad as a Generative AI/LLM Engineer. Your primary responsibility will be to design, develop, and deploy generative AI models using cutting-edge technologies like Azure OpenAI GPT-4, GPT-4 Vision, or GPT-4 Omni. You should have a strong background in building and deploying AI models, with a focus on leveraging technologies such as Retrieval-Augmented Generation (RAG) and working with Vector Databases. While experience in fine-tuning large language models (LLMs) is beneficial, it is not mandatory. You are expected to have a general understanding of training or fine-tuning deep learning models and be able to quickly learn and implement advanced techniques. Your key responsibilities will include designing, developing, and deploying generative AI models using GPT-4 variants, implementing and optimizing RAG techniques, building and managing AI services using Python frameworks like LangChain or LlamaIndex, and developing APIs with FastAPI or Quart for efficient integration. You will focus on scalability, performance, and optimization of AI solutions across cloud environments, particularly with Azure and AWS. Working with Vector Databases is mandatory, and experience with Graph Databases is optional. You will also utilize Cosmos DB and SQL for data storage and management solutions, apply MLOps or LLMOps practices, and manage Azure Pipelines for continuous integration and deployment. Additionally, you will continuously research and adopt the latest advancements in AI technologies. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field, with at least 1+ years of experience in Generative AI/LLM technologies and 5+ years of experience in related fields. Proficiency in Python and experience with frameworks like LangChain, LlamaIndex, FastAPI, or Quart is required. Expertise in RAG and experience with Vector Databases are mandatory. Knowledge of Cosmos DB and SQL is also essential. Experience with fine-tuning LLMs and Graph Databases is beneficial but not mandatory. You should have proven experience in MLOps, LLMOps, or DevOps, a strong understanding of CI/CD processes, automation, and pipeline management, and familiarity with containers, Docker, or Kubernetes. Experience with cloud platforms, particularly Azure or AWS, and cloud-native AI services is desirable. Strong problem-solving abilities and a proactive approach to learning new AI trends and best practices quickly are necessary for this role.,

We are seeking a Senior LLM Engineer to actively contribute to the development of cutting-edge GenAI applications. Your responsibilities will include building GenAI applications that align with business use cases, designing and optimizing prompts for multi-modal models, testing GenAI solutions to ensure they meet requirements and implementing guardrails to prevent unintended or harmful content generation. Additionally, you will be involved in designing conversational or RAG systems. To be successful in this role, you should have a Bachelor's degree in Engineering or related fields with at least 3 years of experience in ML/LLMs. You should possess knowledge of prompt engineering techniques such as chain of thoughts, tree of thoughts, guardrails, zero-shot or few-shot prompting. Familiarity with open-source and proprietary LLMs like GPT, Claude, LLaMA, and Mistral is required. Proficiency in Python programming and experience with libraries like numpy and pandas are essential. Hands-on experience with frameworks such as Langchain, LlamaIndex, Huggingface, or similar tools is preferred. Knowledge of RAG and experience with self-hosted/cloud-based vector databases is a plus. The ideal candidate will have a proven ability to work effectively in a cross-discipline environment within defined timelines. Experience with cloud-based systems, particularly GCP or AWS, is highly desirable. Strong analytical, problem-solving, written, and verbal communication skills are also key requirements. This position is based in Ahmedabad or Pune.,

As an Enterprise Architect & AI Expert, your role will involve defining and maintaining the enterprise architecture framework, standards, and governance. You will align IT strategy with business goals to ensure architectural integrity across systems and platforms. Leading the development of roadmaps for cloud, data, application, and infrastructure architectures will be a key responsibility. It will also be crucial to evaluate and select technologies, platforms, and tools that align with enterprise goals. You will be responsible for designing and implementing AI/ML solutions to solve complex business problems. Leading AI initiatives such as NLP, computer vision, predictive analytics, and generative AI will be part of your duties. Collaborating with data scientists, engineers, and business stakeholders to deploy AI models at scale will be essential. Ensuring ethical AI practices, data governance, and compliance with regulatory standards will also be critical. In terms of leadership and collaboration, you will act as a strategic advisor to senior leadership on technology trends and innovation. Mentoring cross-functional teams, promoting architectural best practices, and facilitating enterprise-wide workshops and architecture review boards will be part of your role. To qualify for this position, you should have a Bachelors or Masters degree in Computer Science, Engineering, or a related field. You should possess 14+ years of experience in enterprise architecture, with at least 3 years in AI/ML domains. Proven experience with cloud platforms such as AWS, Azure, GCP, microservices, and API management is required. Strong knowledge of AI/ML frameworks like TensorFlow, PyTorch, Scikit-learn, and MLOps practices is essential. Familiarity with data architecture, data lakes, and real-time analytics platforms is also expected. Excellent communication, leadership, and stakeholder management skills are necessary for this role. Mandatory skills for this position include experience in designing GenAI and RAG architectures, familiarity with AWS, Vector DB - Milvus (preferred), OpenAI or Claude, LangChain, and LlamaIndex. Thank you for considering this opportunity. Siva,

NTT DATA is currently looking for a Digital Engineering Sr. Engineer to join their team in Hyderabad, Telangana (IN-TG), India (IN). As a Data Science & AIML, GenAI Lead/Engineer, your responsibilities will include conducting data analysis using Python, developing AI models leveraging Langchain, LlamaIndex, and Azure OpenAI Services, and utilizing Generative AI models and Natural Language Processing techniques. You will also be responsible for implementing Retrieval-Augmented Generation (RAG) solutions, applying machine learning algorithms, data pre-processing, and managing the AI lifecycle (model training, validation, monitoring). The ideal candidate should have a minimum of 2 years of experience with AI Python development and a Bachelors degree in computer science, Information Technology, or a related field. Strong analytical skills, attention to detail, and the ability to work independently or as part of a team are essential for this role. NTT DATA, a $30 billion trusted global innovator of business and technology services, is committed to helping clients innovate, optimize, and transform for long term success. With a diverse team of experts in more than 50 countries and a robust partner ecosystem, NTT DATA offers services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. As one of the leading providers of digital and AI infrastructure globally, NTT DATA is part of the NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com.,

We are seeking a Generative AI Engineer with 712 years of experience for a 12-month hybrid engagement (2 days onsite) in Bengaluru, Chennai, Hyderabad, Pune, or Vadodara. The candidate will develop enterprise-grade, cloud-native GenAI applications leveraging Azure OpenAI, Azure Cognitive Services, Azure ML Studio, and Azure Document Intelligence. Proficiency in implementing LLMs, RAG pipelines, OCR, and agent-based frameworks using LangChain, LlamaIndex, and Semantic Kernel is critical. The engineer should have experience in deploying scalable AI solutions across production environments. This role demands a mix of technical depth and applied AI implementation with strong delivery ownership and a problem-solving mindset. Location - Bengaluru, Chennai, Hyderabad, Pune, Vadodara (Hybrid 2 days WFO)

Key Responsibilities: Design and Implement RAG-Based Solutions: Lead the development of a robust RAG-based system that seamlessly integrates generative AI models with retrieval mechanisms, ensuring optimal accuracy, performance, and scalability. Agent-Based Solution Development : Build AI agents that can autonomously perform tasks using information retrieval, language models, and multi-turn interactions using AutoGen, LangGraph frameworks. Generative AI Integration : Leveraging LLMs (e.g., GPT, Anthropic, Llama, Deepseek etc.) for generating high-quality, contextually accurate content in response to user queries. Prompt Engineering: Strong proficiency in prompt engineering to design, test, and optimize prompts for large language models, ensuring effective agent behavior and task completion Data & Knowledge Integration : Work on integrating structured and unstructured data sources into the RAG framework to improve model outputs. Collaborate with Teams : Work closely with product, engineering, and data science teams to ensure seamless integration of AI capabilities into broader products. Security & Compliance : Ensure following best practices in data security, privacy, and compliance, particularly in AI-driven applications. Model Evaluation : Implement strategies for continuous evaluation, monitoring, and tuning of models to ensure high-quality outputs. Data Pipeline Design : Build robust data pipelines for preprocessing and integrating structured and unstructured data sources into the platform. Collaborate with Teams : Work closely with data engineers, and software engineers to ensure seamless integration of machine learning models into production environments. Performance Optimization : Implement and experiment with various techniques such as vector search , semantic search , and knowledge distillation to enhance the platforms efficiency and accuracy. Data Quality : Ensure data quality and consistency throughout the data pipeline, implementing necessary quality checks and validation processes. Requirements: 4+ years of experience with building GenAI solutions using Python and Langchain and AutoGen technologies. Agentic AI experienced developing agents using AutoGen and LangGraph frameworks. Prior experience in building GenAI solutions using effective text representation techniques and classification algorithms. Experience with ML – Model Building, Semantic extraction techniques, data structures and modelling Experience with Supervised/Unsupervised Learning, Sentiment Analysis, Statistical Analysis using NLP and Python libraries (NLTK, Spacy, Numpy, Pandas) Experienced in building Rest API’s Experience with building applications with micro services & serverless architecture Excellent communication skills Good to have: Experience with Azure cloud services Experience with Azure Foundry & Prompt flow

Business Analyst Lead | GenAI Strategy & Implementation | 7-10 Years of Experience Locations Open To: Gurgaon | Noida Seasoned Business Analyst Lead with 7-10 years of experience driving the adoption and operationalization of Generative AI technologies within enterprise environments. Proven ability to bridge the gap between cutting-edge innovationssuch as LLMs, RAG systems, and AI agentsand measurable business value. GenAI & Technical Expertise: Hands-on with LangChain, LlamaIndex, and RAG architectures; experience fine-tuning models using LoRA and working with vector DBs. Proficient in GenAI platforms including Azure OpenAI Studio, GCP Vertex AI, and Hugging Face. Familiar with synthetic data tools (Gretel, Mostly AI); skilled in validating data quality using SQL and Python. Business Analysis & Use Case Delivery: Skilled in identifying high-impact GenAI use cases across domains like content automation, customer service, and synthetic data generation. Expert in user story mapping for complex agent workflows (AutoGen, CrewAI) and BPMN process modeling for AI-human interaction. Conducts detailed cost-benefit analyses (e.g., GPT-4 Enterprise vs. open-source models) to inform build-vs-buy decisions. Requirements Engineering & Governance: Defines GenAI-specific NFRs including hallucination thresholds, latency SLAs, and ethical safeguards (bias, PII). Documents prompt engineering playbooks and iteration workflows to support scalable solution development. Establishes performance frameworks: token cost metrics, user trust scores, model drift alerts, and audit mechanisms aligned to regulatory standards (e.g., EU AI Act). Stakeholder Enablement: Converts technical GenAI potential into tangible business outcomes—such as reducing support costs by 30% or halving contract turnaround times with AI tools. Manages stakeholder expectations around the probabilistic nature of GenAI, implementing robust fact-checking and feedback loops.

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

Position: AI ML GENAI Architect Experience: 9+ Years Location: Pune/ Kolkata / Indore Work Mode: Hybrid (3 Days WFO / 2 Days WFH) Position Overview: We are seeking an experienced AI/ML Architect with 10+ years of experience, specializing in ML and Gen AI. The ideal candidate will possess the technical depth to design and implement cutting-edge AI/ML solutions, particularly leveraging large language models (LLMs) and agentic workflows, while translating business requirements into actionable technical architectures. This role requires a hands-on professional who thrives in a dynamic environment, delivering impactful AI/ML strategies and solutions. Mandatory Skills: GENAI, Generative AI, LLM, LangChain, LlamaIndex, TensorFlow, Prompt Engineering. Required Skills: Technical Expertise. Very good Skills in Python, Pandas, NumPy, SQL Excellent understanding of Machine Learning algorithms and metrics. Proficiency with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with LLM frameworks like LangChain, LlamaIndex, or similar tools. Strong knowledge of at least one hyperscaler (preferably GCP or Azure). Proficiency and understanding of ML APIs on the cloud. Experience in designing and implementing agentic workflows and modular AI solutions using frameworks like LangGraph, Crew.ai, Microsoft Autogen etc. Understanding of data pipelines, ETL frameworks, and big data technologies (e.g., Spark, Snowflake, Hadoop). Architecture Design Expertise in creating AI/ML solution blueprints and technical diagrams. Familiarity with MLOps practices, microservices architecture, containerization (Docker, Kubernetes), and CI/CD pipelines. Excellent understanding in Gen AI frameworks and models. Prompt Engineering, GANs, OpenAI, Dall-E, Stable Diffusion, Langchain, Lllama2. Prior experience in technical presales and building proposal Domain Expertise Preferred domain expertise in consumer/CPG/retail, supply chain Soft Skills: 1. Strong communication skills with the ability to present technical solutions to business leaders. 2. Proven ability to collaborate cross-functionally with technical and non-technical teams. 3. Problem-solving mindset with a focus on innovation and impact. Role Description: Solution Design & Architecture Work with business teams to identify requirements and design AI/ML solutions that address key challenges in the consumer/CPG/retail sectors. Develop comprehensive architecture diagrams and technology stacks tailored to business needs. Incorporate LLM frameworks (e.g., LangChain, LlamaIndex) into solution designs to deliver advanced language-based functionalities. Technical Implementation & Agentic Workflows Design and implement agentic workflows using LLMs to automate decision-making and complex processes. Build modular, scalable solutions that integrate with existing enterprise systems and tools. Ensure solutions are aligned with MLOps practices for robust deployment and monitoring. Prototyping & POCs. Rapidly develop proof-of-concept (POC) models and prototypes, showcasing the feasibility and value of AI/ML solutions. Test and refine LLM-driven workflows and agent-based models to meet business objectives. Presales. Lead AI discussions with prospects presenting Calsofts capabilities and experience and discussing client need. Understand client need and design technical solution, high-level work plans, and estimates required for an AI related sales proposal.

Automation Anywhere is a leader in AI-powered process automation, utilizing AI technologies to drive productivity and innovation across organizations. The company's Automation Success Platform offers a comprehensive suite of solutions including process discovery, RPA, end-to-end process orchestration, document processing, and analytics, all with a security and governance-first approach. By empowering organizations globally, Automation Anywhere aims to unleash productivity gains, drive innovation, enhance customer service, and accelerate business growth. Guided by the vision to enable the future of work through AI-powered automation, the company is committed to unleashing human potential. Learn more at www.automationanywhere.com. Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 6 to 12 years of relevant experience. - Proven track record as a Solution Architect or Lead, focusing on integrating Generative AI or exposure to Machine Learning. - Expertise in at least one RPA tool such as Automation Anywhere, UiPath, Blue Prism, Power Automate, and proficiency in programming languages like Python or Java. Skills: - Proficiency in Python or Java for programming and architecture. - Strong analytical and problem-solving skills to translate business requirements into technical solutions. - Experience with statistical packages and machine learning libraries (e.g., R, Python scikit-learn, Spark MLlib). - Familiarity with RDBMS, NoSQL, and Cloud Platforms like AWS/AZURE/GCP. - Knowledge of ethical considerations and data privacy principles related to Generative AI for responsible integration within RPA solutions. - Experience in process analysis, technical documentation, and workflow diagramming. - Designing and implementing scalable, optimized, and secure automation solutions for enterprise-level AI applications. - Expertise in Generative AI technologies such as RAG, LLM, and AI Agent. - Advanced Python programming skills with specialization in Deep Learning frameworks, ML libraries, NLP libraries, and LLM frameworks. Responsibilities: - Lead the design and architecture of complex RPA solutions incorporating Generative AI technologies. - Collaborate with stakeholders to align automation strategies with organizational goals. - Develop high-level and detailed solution designs meeting scalability, reliability, and security standards. - Take technical ownership of end-to-end engagements and mentor a team of senior developers. - Assess the applicability of Generative AI algorithms to optimize automation outcomes. - Stay updated on emerging technologies, particularly in Generative AI, to evaluate their impact on RPA strategies. - Demonstrate adaptability, flexibility, and willingness to work from client locations or office environments as needed. Kindly note that all unsolicited resumes submitted to any @automationanywhere.com email address will not be eligible for an agency fee.,

Location: Bangalore Key Responsibilities: Design, develop, and deploy AI/ML models, particularly using LLAMA and similar LLM frameworks. Integrate vector databases and PostgreSQL for intelligent data retrieval and storage. Build and optimize Python-based pipelines , APIs, and backend services for AI applications. Leverage Databricks for scalable data processing, model training, and deployment. Collaborate with cross-functional teams to deliver production-ready AI solutions rapidly. Contribute to POCs and prototypes to validate ideas and iterate quickly. Must-Have Skills: 7+ years of experience in Data Science / AI Engineering roles. Proficiency with Databricks , Python , and PostgreSQL . Hands-on experience working with LLMs (especially LLAMA) and vector DBs like Pinecone, FAISS, or similar. Strong understanding of AI/ML lifecycle , from model development to deployment. Experience in startup or agile environments , with proven rapid delivery capabilities. Good to Have: Familiarity with cloud platforms (AWS/Azure/GCP). Knowledge of LangChain or similar LLM orchestration frameworks. Exposure to MLOps best practices and deployment tools.

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology. We are looking for an experienced AI Developer with proficiency in Python, Generative AI (GenAI) incorporating Retrieval-Augmented Generation (RAG), Robotic Process Automation (RPA), and advanced document intelligence utilizing OCR and LLMs. In this role, you will be responsible for developing AI-driven solutions that extract valuable insights from intricate documents, whether digital or scanned, by utilizing tools such as Tesseract, Hugging Face Transformers, or similar technologies. Your primary focus will be on creating end-to-end automation and AI integration for intelligent document processing, enhancing decision-making capabilities and optimizing workflow efficiencies throughout the organization. Key Responsibilities: - Develop and implement GenAI solutions with RAG pipelines to facilitate intelligent querying and summarization of document repositories. - Extract and organize data from complex documents (e.g., PDFs, Images) using a combination of OCR engines (e.g., Tesseract) and AI-based document and vision language models (DiNO, SmolVLM, etc.). - Incorporate OCR+LLM pipelines into business applications for processing scanned forms, contracts, and other unstructured documents. - Automate repetitive, document-centric tasks using RPA tools (e.g., Blue Prism, etc.). - Design and manage Python-based workflows to coordinate document ingestion, extraction, and LLM-powered processing. - Collaborate across various teams including product, data, and operations to deliver scalable, AI-enhanced document automation solutions. - Ensure model performance, compliance, and audit readiness for all document-handling workflows. Required Qualifications: - Minimum of 4 years of hands-on programming experience with Python. - Demonstrated expertise in building RAG-based GenAI applications using tools like LangChain, LlamaIndex, or equivalent. - Proficiency in OCR tools (e.g., Tesseract, PaddleOCR) and transformer-based document models. - Experience working with LLMs for document understanding, summarization, and Q&A. - Proficient in RPA development utilizing platforms like Blueprism, etc. - Knowledge of vector databases (e.g., FAISS, Pinecone) and embeddings for semantic retrieval. - Strong understanding of REST APIs, JSON, and data integration workflows. Please note that unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.,

We are looking for a GenAI/ML Engineer to design, develop, and deploy cutting-edge AI/ML models and Generative AI applications . This role involves working on large-scale enterprise use cases, implementing Large Language Models (LLMs) , building Agentic AI systems , and developing data ingestion pipelines . The ideal candidate should have hands-on experience with AI/ML development , Generative AI applications , and a strong foundation in deep learning , NLP , and MLOps practices. Key Responsibilities Design, develop , and deploy AI/ML models and Generative AI applications for various enterprise use cases. Implement and integrate Large Language Models (LLMs) using frameworks such as LangChain , LlamaIndex , and RAG pipelines . Develop Agentic AI systems capable of multi-step reasoning and autonomous decision-making . Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval techniques. Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to deploy AI solutions and enhance the AI stack. Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices. Leverage Azure and Databricks for training , serving , and monitoring AI models at scale. Required Qualifications & Skills (Mandatory) 4+ years of hands-on experience in AI/ML development , including Generative AI applications . Expertise in RAG , LLMs , and Agentic AI implementations. Strong experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks. Proficiency in Python and key ML/DL libraries : TensorFlow , PyTorch , Scikit-learn . Solid foundation in Deep Learning , Natural Language Processing (NLP) , and Transformer-based architectures . Experience in building data ingestion , indexing , and retrieval pipelines for real-world enterprise use cases. Hands-on experience with Azure cloud services and Databricks . Proven track record in designing CI/CD pipelines and using MLOps tools like MLflow , DVC , or Kubeflow . Soft Skills Strong problem-solving and critical thinking ability. Excellent communication skills , with the ability to explain complex AI concepts to non-technical stakeholders. Ability to collaborate effectively in agile , cross-functional teams . A growth mindset , eager to explore and learn emerging technologies. Preferred Qualifications Familiarity with vector databases such as FAISS , Pinecone , or Weaviate . Experience with AutoGPT , CrewAI , or similar agent frameworks . Exposure to Azure OpenAI , Cognitive Search , or Databricks ML tools . Understanding of AI security , responsible AI , and model governance . Role Dimensions Design and implement innovative GenAI applications to address complex business problems. Work on large-scale, complex AI solutions in collaboration with cross-functional teams. Take ownership of the end-to-end AI pipeline , from model development to deployment and monitoring. Success Measures (KPIs) Successful deployment of AI and Generative AI applications . Optimization of data pipelines and model performance at scale. Contribution to the successful adoption of AI-driven solutions within enterprise use cases. Effective collaboration with cross-functional teams, ensuring smooth deployment of AI workflows. Competency Alignment AI/ML Development : Expertise in building and deploying scalable and efficient AI models. Generative AI : Strong hands-on experience in Generative AI , LLMs , and RAG frameworks. MLOps : Proficiency in designing and maintaining CI/CD pipelines and implementing MLOps practices . Cloud Platforms : Experience with Azure and Databricks for AI model training and serving.