696 Langchain Jobs - Page 23

Seeking Full-Stack Developer to build intelligent, task-driven AI agents using React & FastAPI. Must blend AI/ML expertise with software skills to create scalable, modular systems for API/UI interaction. Required Candidate profile 1. 2+ yrs in software (Full-Stack) development 2. Strong in Next.js 3. Built scalable web apps 4. Well-versed with prompt engineering

Role - Senior Data Scientist / Senior Gen AI Engineer Exp Range - 8 to 18 yrs Position - Permanent Fulltime Company - Data Analytics & AIML MNC Location - Hyderabad, Pune, Bangalore (Relocation accepted) About the Role: We are seeking a Software Engineer with expertise in Generative AI and Microsoft technologies to design, develop, and deploy AI-powered solutions using the Microsoft ecosystem. You will work with cross-functional teams to build scalable applications leveraging generative AI models and Azure services. Skills Required: Experience with Large Language Models (LLMs) like GPT, LLaMA, Claude, etc. Proficiency in Python for building and fine-tuning AI/ML models Familiarity with LangChain , LLMOps , or RAG (Retrieval-Augmented Generation) pipelines Experience with Vector Databases (e.g. FAISS, Pinecone, Weaviate) Knowledge of Prompt Engineering and model evaluation techniques Exposure to cloud platforms (Azure, AWS or GCP) for deploying GenAI solutions Preferred Skills: Experience with Azure OpenAI , Databricks or Microsoft Fabric Hands-on with Hugging Face Transformers , OpenAI APIs or custom model training

Should lead key initiatives in GenAI COE on new tech trends, R and D on new product POC Work on proposals, Provide solutions architecture design solution on different business use cases Ability to work across various different GenAI Models and cloud providers Should have a strong experience in implementing projects in Digital Engineering Or Data Analytics Technically lead a team of developers and groom talent Extensive implementation experience in data analytics space or a senior developer role in one of the modern technology stack Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java Ability to build API based scalable solutions and debug & troubleshoot software or design issues Hands on exposure to integrating atleast one of the popular LLMs(Open AI GPT, PaLM 2, Dolly, Claude 2, Cohere etc.) using API endpoints. Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support Hands on exposure to using cloud(Azure/GCP/AWS) services for storage, serverless-logic, search, transcription and chat Extensive experience with data engineering and should be hands on in using Agentic AI Framework, RAG

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams.

Requirements: Must-have: Python. Azure cloud experience. Experience of developing and refactoring scalable and robust solutions. Strong experience with GenAI/LLM frameworks and technics, like guardrails, Langchain, etc. Nice-to-have: Strong experience with GenAI components, like vector databases (e.g. Cosmos DB, FAISS etc) Practical experience of developing and deploying GenAI/LLMs/SLMs-based solutions. Responsibilities: Refactor current solution to make it scalable and stable Prompt Engineering Libraries/Plugins: Develop libraries or plugins to improve response consistency and quality through pre-built prompts, templates, and best practices for effective prompt crafting. Performance tuning to handle large payloads, such as performance testing scripts, to deliver complete responses. Develop strategies to manage token limitations, enabling the tool to facilitate complex and informative interactions without restrictions. Extend support for a wide range of file formats, including XML, HTML, and HAR, in addition to standard Microsoft product documents (Word, PowerPoint, Excel, PDF). Leverage multi-vector retrieval techniques to enhance the tool's functionality and effectively handle large data sets. Role & responsibilities Preferred candidate profile

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Description: Job Description: We are looking for an experienced Python Developer with expertise in AI/ML to join our team. The ideal candidate should have strong Python development skills and hands-on experience with AI/ML frameworks, LangChain, Haystack, and LangGraph . Key Responsibilities: Develop and optimize AI/ML-driven applications using Python. Implement and enhance solutions leveraging LangChain, Haystack, and LangGraph . Collaborate with cross-functional teams to integrate AI/ML models into production systems. Design and develop scalable machine learning pipelines and APIs. Debug, optimize, and maintain AI-based applications. Requirements: 310 years of experience in Python development , with a focus on AI/ML. Strong expertise in LangChain, Haystack, and LangGraph . Experience in developing and deploying ML models in a production environment. Familiarity with NLP, deep learning, and vector databases is a plus. Excellent problem-solving skills and ability to work independently or in a team.

Primary Responsibilities: Design and develop AI-driven web applications using Streamlit and LangChain. Implement multi-agent workflows with LangGraph. Integrate Claude 3 (via AWS Bedrock) into intelligent systems for document and image processing. Work with FAISS for vector search and similarity matching. Develop document integration solutions for PDF, DOCX, XLSX, PPTX, and image-based formats. Implement OCR and summarization features using EasyOCR, PyMuPDF, and AI models. Create features such as spell-check, chatbot accuracy tracking, and automatic re-training pipelines. Build secure apps with SSO authentication, transcript downloads, and reference link generation. Integrate external platforms like Confluence, SharePoint, ServiceNow, Veeva Vault, Outlook, G.Net/G.Share, and JIRA. Collaborate on architecture, performance optimization, and deployment. Required Skills: Strong expertise in Streamlit, LangChain, LangGraph, and Claude 3 (AWS Bedrock). Hands-on experience with boto3, FAISS, EasyOCR, and PyMuPDF. Advanced skills in document parsing and image/video-to-text summarization. Proficient in modular architecture design and real-time AI response systems. Experience in enterprise integration with tools like ServiceNow, Confluence, Outlook, and JIRA. Familiar with chatbot monitoring and retraining strategies. Secondary Skills: Working knowledge of PostgreSQL, JSON, and file I/O with Python libraries like os, io, time, datetime, and typing. Experience with dataclasses and numpy for efficient data handling and numerical process

Should lead key initiatives in GenAI COE on new tech trends, R and D on new product POC Work on proposals, Provide solutions architecture design solution on different business use cases Ability to work across various different GenAI Models and cloud providers Should have a strong experience in implementing projects in Digital Engineering Or Data Analytics Technically lead a team of developers and groom talent Extensive implementation experience in data analytics space or a senior developer role in one of the modern technology stack Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java Ability to build API based scalable solutions and debug & troubleshoot software or design issues Hands on exposure to integrating atleast one of the popular LLMs(Open AI GPT, PaLM 2, Dolly, Claude 2, Cohere etc.) using API endpoints. Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support Hands on exposure to using cloud(Azure/GCP/AWS) services for storage, serverless-logic, search, transcription and chat Extensive experience with data engineering and should be hands on in using Agentic AI Framework, RAG

Position Overview We are seeking AI Product Engineers with 12 years of experience who can bridge the gap between product development and advanced AI technologies. This role involves working closely with AI models, APIs, and data pipelines, while also contributing to product design, user experience, and deployment strategies. You will work at the intersection of technology , user experience , and business outcomes . Key Responsibilities Collaborate with product managers and AI teams to design and develop AI-driven products leveraging LLMs (GPT-3.5, GPT-4, Gemini). Translate business requirements into AI product features and work on building functional prototypes. Develop and integrate LangChain-based workflows, including LangSmith and LangGraph , to enable intelligent app interactions. Implement Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases (e.g., ChromaDB) to enhance AI performance. Apply prompt engineering to customize model outputs based on product needs and use cases. Build REST APIs and microservices using Flask or FastAPI to support model integration. Work with SQL , PySpark , and Spark SQL to manage and process structured and unstructured data. Collaborate with UI/UX teams to ensure seamless user interaction with AI components. Support product deployment and monitoring on Azure ML or AWS Bedrock . Required Skills Strong programming skills in Python , SQL , PySpark , Spark SQL Understanding of Generative AI , LLMs , and prompt engineering Experience with LangChain , LangGraph , LangSmith Familiarity with vector databases and embedding techniques Exposure to cloud platforms : Azure ML or AWS Bedrock REST API development using Flask or FastAPI Excellent problem-solving skills and product-oriented mindset Preferred Qualifications Bachelor’s degree in Computer Science, AI/ML, Data Science, or related field Internship or academic experience in AI product development or applied NLP Familiarity with MLOps concepts and product lifecycle best practices Basic understanding of UI/UX principles and user-centric design

Req ID: 327886 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a AI & LLM Engineer - Digital Engineering Sr. Engineer to join our team in Hyderabad, Telangana (IN-TG), India (IN). Software Engineer - LLM & Agentic AI Systems Design and build intelligent agents using LLMs that can autonomously complete tasks via planning, reasoning, and tool use. Develop backend services and APIs to support AI agent workflows and integrations. Implement planning frameworks (e.g., ReAct, AutoGPT, BabyAGI, LangGraph) and decision-making loops using LLMs. Build, test, and optimize LLM-based applications with tools like LangChain, LlamaIndex, or Semantic Kernel. Create and manage pipelines that connect LLMs to tools, APIs, and databases in real-time. Collaborate with ML/AI researchers, data engineers, and product teams to ship LLM-powered experiences. About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of 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 NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click . If you'd like more information on your EEO rights under the law, please click . For Pay Transparency information, please click.

3+yrs mandatory into Software Development 1+yrs mandatory exp. with LLMs & AI Frameworks Strong in Python & AI frameworks LLM Orchestration (LangChain) Understanding of Vector Databases

Bachelors degree or higher in Machine Learning, Computer Science, Computational Linguistics, Mathematics or other relevant technical field from premier institute. •Strong foundation in Probability, Statistics, Linear Algebra, Calculus, Machine Learning and Generative AI/LLM. •Expertise in Deep Learning techniques and applications. •Strong understanding of Generative AI (GenAI) including math behind the models and its practical implementations. •Hands-on experience working with Large Language Model APIs like Azure OpenAI, Anthropic etc.. and cloud ecosystems like Azure, AWS, GCP, Databricks •Proficiency in LangChain, LangGraph, and working with Vector Databases for advanced data retrieval and AI workflows. •Proficiency in Python or similar programming languages, with experience in AI/ML libraries and frameworks such as TensorFlow, PyTorch, or Hugging Face. •Knowledge of financial products, including mutual funds, ETFs, and client segmentation, is a plus. •Excellent problem-solving and analytical skills. •Strong communication skills to explain complex models and insights effectively.

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization . You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities 1) Technical Leadership Lead the technical design and architecture of complex Generative AI systems. Ensure solutions align with business objectives, scalability requirements, and technical feasibility. Guide development teams through best practices , architecture reviews, and technical decision-making processes. 2) Solution Architecture Design and develop end-to-end Generative AI solutions , including data pipelines , model training, deployment, and real-time monitoring. Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. Design, train, and fine-tune AI/ML models , especially Generative AI and Large Language Models (LLMs) , to address specific use cases. Build conversational AI solutions and chatbots using frameworks such as LangChain , RAG (Retrieval-Augmented Generation) , and Chain-of-Thought (COT) prompting . 3) Production Deployment Lead the deployment of Generative AI models into production environments . Optimize deployment pipelines leveraging tools like Docker, Kubernetes , and cloud-native services for orchestration. Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. 4) Data Processing & Feature Engineering Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. Implement data wrangling , preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Optimize workflows to extract meaningful insights from large datasets . 5) Model Optimization Identify and implement optimization strategies such as hyperparameter tuning , feature engineering , and model selection for performance enhancement. Focus on computational efficiency and scaling models to production-level performance. 6) Pilot/POCs Development Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. 7) Evangelization Promote and drive the adoption of Generative AI solutions across customer and delivery teams. Provide technical leadership and mentorship to teams working on GenAI projects. Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. 8) Continuous Improvement Stay at the forefront of AI advancements , frameworks, and tools, including emerging concepts in Generative AI. Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications 10+ years of experience in AI/ML architecture, model development, and production deployment Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions Hands-on experience with frameworks like LangChain , Retrieval-Augmented Generation (RAG) , and advanced prompting techniques Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting Experience working with cloud platforms , primarily GCP , with optional experience in AWS or Azure Strong understanding of MLOps tools, pipelines, and model monitoring in production Proficiency in Python and SQL for model development and data processing Experience with data preprocessing, ETL workflows , and feature engineering for AI applications Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions Experience working with large datasets for structured and unstructured AI applications Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies Proven track record of leading POCs/pilots and scaling them to production-grade deployments Preferred Skills Familiarity with Reinforcement Learning from Human Feedback (RLHF) . Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. Strong understanding of orchestration for large-scale production environments. Key Attributes Strong technical leadership and mentorship abilities. Excellent communication and stakeholder management skills. Strategic thinking with the ability to architect scalable and future-ready AI systems. Passion for solving business challenges using state-of-the-art AI techniques. Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us? Lead the development of cutting-edge Generative AI solutions for real-world applications. Be part of a collaborative, innovative, and technology-driven team. Opportunity to work with advanced AI/ML tools and frameworks. Drive innovation through technical leadership , mentorship, and solution evangelization. Continuous professional growth with access to the latest AI/ML technologies and frameworks.

Senior Data Scientist, Operations Mumbai, India About Argus: Argus is the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets. Headquartered in London with 1,500 staff, Argus is an independent media organisation with 30 offices in the worlds principal commodity trading hubs. Companies, trading firms and governments in 160 countries around the world trust Argus data to make decisions, analyse situations, manage risk, facilitate trading and for long-term planning. Argus prices are used as trusted benchmarks around the world for pricing transportation, commodities and energy. Founded in 1970, Argus remains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic. What were looking for: Join our Generative AI team as a Senior Data Scientist, reporting directly to the Lead Data Scientist in India. You will play a crucial role in building, optimizing, and maintaining AI-ready data infrastructure for advanced Generative AI applications. Your focus will be on hands-on implementation of cutting-edge data extraction, curation, and metadata enhancement techniques for both text and numerical data. You will be a key contributor to the development of innovative solutions, ensuring rapid iteration and deployment, and supporting the Lead in achieving the team's strategic goals. What will you be doing: AI-Ready Data Development : Design, develop, and maintain high-quality AI-ready datasets, ensuring data integrity, usability, and scalability to support advanced Generative AI models. Advanced Data Processing : Drive hands-on efforts in complex data extraction, cleansing, and curation for diverse text and numerical datasets. Implement sophisticated metadata enrichment strategies to enhance data utility and accessibility for AI systems. Algorithm Implementation & Optimization : Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development : Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application : Apply advanced prompt engineering techniques to optimize LLM performance for specific data extraction, summarization, and generation tasks, working closely with the Lead's guidance. LLM Evaluation Support : Contribute to the systematic evaluation of Large Language Models (LLMs) outputs, analysing quality, relevance, and accuracy, and supporting the implementation of LLM-as-a-judge frameworks. Retrieval-Augmented Generation (RAG) Contribution : Actively contribute to the implementation and optimization of RAG systems, including working with embedding models, vector databases, and, where applicable, knowledge graphs, to enhance data retrieval for GenAI. Technical Mentorship : Act as a technical mentor and subject matter expert for junior data scientists, providing guidance on best practices in coding and PR reviews, data handling, and GenAI methodologies. Cross-Functional Collaboration : Collaborate effectively with global data science teams, engineering, and product stakeholders to integrate data solutions and ensure alignment with broader company objectives. Operational Excellence : Troubleshoot and resolve data-related issues promptly to minimize potential disruptions, ensuring high operational efficiency and responsiveness. Documentation & Code Quality : Produce clean, well-documented, production-grade code, adhering to best practices for version control and software engineering. Skills and Experience: Academic Background : Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks : 2+ years of hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools : 1+ years Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering : Deep expertise in prompt engineering, including prompt tuning, chaining, and optimization techniques. LLM Evaluation : Experience evaluating LLM outputs, including using LLM-as-a-judge methodologies to assess quality and alignment. RAG and Knowledge Graphs : Practical understanding and experience using vector databases. In addition, familiarity with graph-based RAG architectures and the use of knowledge graphs to enhance retrieval and reasoning would be a strong plus. Cloud : 2+ years of experience with Gemini/OpenAI models and cloud platforms such as AWS, Google Cloud, or Azure. Proficient with Docker for containerization. Data Engineering : Strong understanding of data extraction, curation, metadata enrichment, and AI-ready dataset creation. Collaboration and Communication : Excellent communication skills and a collaborative mindset, with experience working across global teams. Whats in it for you: Competitive salary Hybrid Working Policy (3 days in Mumbai office/ 2 days WFH once fully inducted) Group healthcare scheme 18 days annual leave 8 days of casual leave Extensive internal and external training Hours: This is a full-time position operating under a hybrid model, with three days in the office and up to two days working remotely. The team supports Argus key business processes every day, as such you will be required to work on a shift-based rota with other members of the team supporting the business until 8pm. Typically support hours run from 11am to 8pm with each member of the team participating up to 2/3 times a week. For more details about the company and to apply please make sure you send your CV and cover letter via our website: www.argusmedia.com/en/careers/open-positions By submitting your job application, you automatically acknowledge and consent to the collection, use and/or disclosure of your personal data to the Company. Argus is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.

Lead Data Scientist, Operations Mumbai, India About Argus: Argus is the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets. Headquartered in London with 1,500 staff, Argus is an independent media organisation with 30 offices in the worlds principal commodity trading hubs. Companies, trading firms and governments in 160 countries around the world trust Argus data to make decisions, analyse situations, manage risk, facilitate trading and for long-term planning. Argus prices are used as trusted benchmarks around the world for pricing transportation, commodities and energy. Founded in 1970, Argus remains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic. What were looking for: Join our Generative AI team to lead a new group in India, focused on creating and maintaining AI-ready data. As the point of contact in Mumbai, you will guide the local team and ensure seamless collaboration with our global counterparts. Your contributions will directly impact the development of innovative solutions used by industry leaders worldwide, supporting text and numerical data extraction, curation, and metadata enhancements to accelerate development and ensure rapid response times. You will play a pivotal role in transforming how our data are seamlessly integrated with AI systems, paving the way for the next generation of customer interactions. What will you be doing: Lead and Develop the Team : Oversee a team of data scientists in Mumbai. Mentoring and guiding junior team members, fostering their professional growth and development. Strategic Planning : Develop and implement strategic plans for data science projects, ensuring alignment with the company's goals and objectives. AI-Ready Data Development: Design, develop, and maintain high-quality AI-ready datasets, ensuring data integrity, usability, and scalability to support advanced Generative AI models. Advanced Data Processing: Drive hands-on efforts in complex data extraction, cleansing, and curation for diverse text and numerical datasets. Implement sophisticated metadata enrichment strategies to enhance data utility and accessibility for AI systems. Algorithm Implementation & Optimization: Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development: Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application: Apply advanced prompt engineering techniques to optimize LLM performance for specific data extraction, summarization, and generation tasks, working closely with the Lead's guidance. LLM Evaluation Support: Contribute to the systematic evaluation of Large Language Models (LLMs) outputs, analysing quality, relevance, and accuracy, and supporting the implementation of LLM-as-a-judge frameworks. Retrieval-Augmented Generation (RAG) Contribution: Actively contribute to the implementation and optimization of RAG systems, including working with embedding models, vector databases, and, where applicable, knowledge graphs, to enhance data retrieval for GenAI. Technical Leadership : Act as a technical leader and subject matter expert for junior data scientists, providing guidance on best practices in coding and PR reviews, data handling, and GenAI methodologies. Cross-Functional Collaboration: Collaborate effectively with global data science teams, engineering, and product stakeholders to integrate data solutions and ensure alignment with broader company objectives. Operational Excellence: Troubleshoot and resolve data-related issues promptly to minimize potential disruptions, ensuring high operational efficiency and responsiveness. Documentation & Code Quality: Produce clean, well-documented, production-grade code, adhering to best practices for version control and software engineering. Skills and Experience: Leadership Experience: Proven track record in leading and mentoring data science teams, with a focus on strategic planning and operational excellence. Academic Background: Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: 5+ years of hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools : 2+ years of Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering: Deep expertise in prompt engineering, including prompt tuning, chaining, and optimization techniques. LLM Evaluation: Experience evaluating LLM outputs, including using LLM-as-a-judge methodologies to assess quality and alignment. RAG and Knowledge Graphs: Practical understanding and experience using vector databases. In addition, familiarity with graph-based RAG architectures and the use of knowledge graphs to enhance retrieval and reasoning would be a strong plus. Cloud: 2+ years of experience with Gemini/OpenAI models and cloud platforms such as AWS, Google Cloud, or Azure. Proficient with Docker for containerization. Data Engineering: Strong understanding of data extraction, curation, metadata enrichment, and AI-ready dataset creation. Collaboration and Communication : Excellent communication skills and a collaborative mindset, with experience working across global teams. Whats in it for you: Competitive salary Hybrid Working Policy (3 days in Mumbai office/ 2 days WFH once fully inducted) Group healthcare scheme 18 days annual leave 8 days of casual leave Extensive internal and external training Hours: This is a full-time position operating under a hybrid model, with three days in the office and up to two days working remotely. The team supports Argus key business processes every day, as such you will be required to work on a shift-based rota with other members of the team supporting the business until 8pm. Typically support hours run from 11am to 8pm with each member of the team participating up to 2/3 times a week. For more details about the company and to apply please make sure you send your CV and cover letter via our website: www.argusmedia.com/en/careers/open-positions By submitting your job application, you automatically acknowledge and consent to the collection, use and/or disclosure of your personal data to the Company. Argus is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.

Key Responsibilities: As an Infra AI Automation Programmer you will work on design development and deployment of AI systems that generate content or data often using techniques such as deep learning neural networks and generative models using Python backend coding Meet with clients in and remotely to understand their business objectives challenges and identify potential use cases for Generative AI Assess the client s existing technology infrastructure data landscape and AI maturity to determine the feasibility and best approaches for Gen AI adoption Conduct workshops and discovery sessions to brainstorm Gen AI applications across various business functions e g content creation customer service product development marketing Gen AI Strategy and Solution Design Develop tailored Gen AI strategies and roadmaps for clients in outlining specific use cases implementation plans and expected business outcomes Design Gen AI solutions architecture considering factors such as model selection e g large language models LLMs diffusion models data requirements integration with existing systems and scalability Evaluate and recommend appropriate Gen AI platforms tools and APIs e g OpenAI Google AI Azure AI open source libraries relevant to the client s needs and the Indian market Advise on prompt engineering techniques to optimize the output and performance of Gen AI models for specific client applications Technical Requirements: At least 2 years of programming experience in Python Handson experience in working on Gen AI Handson experience in Tensorflow Pytorch Langchain and Prompt Engineering Experience with vector databases and retrieval augmented generation RAG Familiarity with MLOps principles and tools for deploying and managing Gen AI models Understanding of ethical considerations and responsible AI frameworks Understanding of data structures data modelling SQL NOSQL Object oriented and functional programming GIT Knowledge of basic algorithms and object oriented and functional design principles Deep Knowledge of Mathematics Probability Statistics and Algorithms Good Communication skills Good analytical and problem solving skills Additional Responsibilities: Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile These include High analytical skills A high degree of initiative and flexibility High customer orientation High quality awareness Excellent verbal and written communication skills Preferred Skills: Technology->Machine Learning->Python,Technology->Machine Learning->TensorFlow,Technology->Machine Learning->Generative AI

Your day at NTT DATA Cloud AI/GenAI Engineer(ServiceNow) We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What youll be doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN Design, develop and deploy virtual agents using SN agent builder Integrate SN Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Education Bachelor/Masters in Computer Science, AI, ML, or related fields. Experience 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options)

Key Responsibilities: Design and development of AI-driven applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGPT, and Autogen. Build and maintain RESTful APIs, GraphQL endpoints, and gRPC services to support scalable AI features. Support the development of intelligent agents and multi-agent collaboration mechanisms. Implement reasoning techniques including ReAct, Chain-of-Thought (CoT), and Tree-of-Thought (ToT) as part of AI workflows. Contribute to retrieval-augmented generation (RAG) pipelines using vector stores like Weaviate, Pinecone, FAISS, or ChromaDB. Integrate tool-use APIs, function calling, MCP, and external workflows via tools like Zapier or N8N. Work with orchestration tools such as Airflow, Ray, or Temporal to manage agent workflows and data pipelines. Collaborate with AI/ML engineers, product managers, and other developers in building intelligent, production-grade applications. Required Qualifications: 3-5 years of backend or full-stack development experience, with working on Generative or Agentic AI solutions. Proficiency in Python (preferred), with working knowledge of TypeScript/Node.js, Go, or Java. Hands-on experience developing REST APIs, GraphQL endpoints, and/or gRPC-based services. Familiarity with integrating LLMs like GPT-4, Claude, Gemini, Mistral, or LLaMA. Exposure to frameworks such as LangChain, LlamaIndex, or CrewAI. Basic understanding of vector databases and semantic search tools (e.g., FAISS, Pinecone). Experience working in cloud environments (AWS, GCP, Azure) and with containerization tools (Docker, Kubernetes).

Azure DevOps Engineer with 5–7 yrs exp to manage CI/CD, IaC, AKS, LangChain, FastAPI, Redis, PostgreSQL, Angular in Azure. Strong in Terraform, monitoring, and AI integration. Immediate joiners only.

Requirement Role: ML Engineer/Data Scientist Experience: 3 to 15 Years Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

We are looking for a skilled AI Engineer with 3 to 8 years of experience in software engineering or machine learning to design, implement, and productionize LLM-powered agents that solve real-world enterprise problems. This position is based in Kolkata. Roles and Responsibility Architect and build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark and iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Job Requirements Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go is a bonus. Hands-on experience with at least one LLM/agent framework and platform (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar).

Role: ML Engineer Experience: 3 to 15 Years Chennai location must or relocation also fine- Hybrid mode We have good budget Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

Note: Need candidate only from Startup, Banking, Fintech, Product Based We are not looking for NIT or IIT or VIT Candidates. Please don't apply. Required Qualifications: 1+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

What You Will Do: We are seeking a detail-oriented and research-savvy Content Curator to support our enterprise Search Program within the pharmaceutical sector. This role plays a vital part in improving how scientists, researchers, clinicians, and business teams discover relevant, accurate, and well-structured information across vast internal and external data sources. Responsibilities: Curate scientific, clinical, regulatory, and commercial content for internal search platforms Source and aggregate relevant content from various platforms Ensure content is properly tagged, described, and categorized using standard metadata and taxonomies Identify and fill content gaps based on user needs and search behavior Organize and schedule content publication for consistency Analyze content performance and optimize based on insights Provide feedback on synonym lists, controlled vocabularies, and NLP enrichment tools Apply and maintain metadata standards, ontologies, and classification schemes (e.g., MeSH, SNOMED, MedDRA) Collaborate with taxonomy and knowledge management teams to improve tagging strategies Highlight high-quality content across a wide range of topics Stay updated on best practices and contribute to content strategy recommendations Edit and optimize content for SEO Conduct quality assurance checks on all content Track metrics to measure the success of content curation efforts Review and curate content from multiple categories Understand data structures and algorithms for better search optimization Manage and update digital assets, modifying accessibility and security settings as needed Secure permission clearance for publishing various media types Organize and maintain a system for digital content storage Convert digital assets into different formats; archive or discard outdated material Explore new tools and trends in digital content curation Basic Qualifications: Degree in Data Management , Mass Communication , or Computer Science & Engineering 912 years of overall software development experience 5+ years of experience in digital content curation or related roles Strong organizational and time-management skills Proficiency in data analysis and content optimization Familiarity with metadata standards, taxonomy tools, and content management systems Ability to interpret and structure scientific/clinical content for digital use Exceptional written and verbal communication skills Experience with CMS, SEO, Google Analytics, enterprise search platforms, Databricks Strong problem-solving and analytical skills Preferred Qualifications: Experience with enterprise search platforms (Lucene, Elasticsearch, Coveo, Sinequa) Experience with GCP , AWS , or Azure cloud environments Familiarity with GXP Search Engine , Solr Search Experience with databases such as PostgreSQL , MongoDB , Databricks , RDS , DynamoDB , S3 Exposure to Agile software development methodologies Good to Have Skills: Interest in working on AI-based applications Experience with large language models Familiarity with Langchain or LlamaIndex frameworks Knowledge of prompt engineering and model fine-tuning Understanding of NLP techniques for text and sentiment analysis