696 Langchain Jobs - Page 21

Job Title: AI ML Engineer Job Summary: We are looking for a passionate and innovative AI/ML Engineer LLM & NLP with strong expertise in artificial intelligence, natural language processing (NLP), and large language models (LLMs). The focus is on crafting, optimizing, and scaling AI-driven interactions that improve system performance, enhance user experience, and deliver measurable business value across a variety of applications. Key Responsibilities: Design, test, and refine prompts to optimize performance of LLMs such as GPT-4, Claude, Gemini, and open-source models. Collaborate with cross-functional teams (product, design, engineering, marketing) to develop AI-driven features and tools. Conduct experiments and evaluate to test the accuracy, safety, and quality of AI-generated outputs, learning best practices along the way. Automate prompt workflows and integrate prompt chains with APIs and tool stacks. Fine-tune models or build retrieval-augmented generation (RAG) pipelines when needed. Stay curious and keep learning about the latest advancements in generative AI, NLP, and prompt engineering through hands-on practice and research Contribute to building internal documentation, prompt templates and reusable libraries. Required Skills & Qualifications: Bachelor’s degree in computer science. 2 years of experience working with LLMs, AI systems, NLP frameworks. Strong understanding of transformer models and training. Experience using OpenAI (ChatGPT, GPT API), Anthropic, Cohere, Hugging Face, or similar platforms. Strong proficiency in Python, with hands-on experience using leading AI frameworks and libraries such as LangChain, LlamaIndex, and others commonly used in LLM and NLP development. Background in UX, technical writing, or content design is a plus.

Job Title : AI Engineer Location: Chennai Experience: 5+ Years (Hands-On Data Science & AI) Employment Type: Full-Time Work type - Work from office. About the Role We are seeking a skilled AI Engineer with deep hands-on experience in ML, NLP, LLMs, GenAI, and Agentic AI to join our technology team focused on automating US mortgage loan processing workflows. This role involves designing intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure. Key Responsibilities Design and implement ML/NLP/GenAI pipelines for automating loan origination, underwriting, and document intelligence processes. Develop and deploy LLM-based solutions using tools like Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks. Build and orchestrate Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents. Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering. Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models. Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services). Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions. Leverage prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores for contextual mortgage document workflows. Required Skills & Qualifications 5+ years of hands-on experience in Machine Learning, NLP, or LLM-based systems. Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design. Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers. Strong knowledge of Azure Cloud including Azure ML, Azure Functions, Azure DevOps. Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models into production-scale environments. Nice to Have Understanding of US mortgage or lending workflows (1003, 1008, bank statements, etc.). Experience with OCR, document intelligence tools (Azure Form Recognizer, Amazon Textract). Exposure to Agentic AI concepts such as autonomous agents, planning, memory chaining. Knowledge of privacy and compliance frameworks (HIPAA, SOC2) in AI deployments. What We Offer Opportunity to lead GenAI and Agentic AI initiatives for mortgage automation. Access to top-tier tools, frameworks, and cloud platforms. Remote flexibility and career growth in an innovation-first team. Impactful work transforming legacy loan operations through AI. Interested candidates kindly share your resume to SGrace@ca-usa.com.

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Manager - Agentic AI Solution Architect In this role, you%27ll be part of Genpact%27s transformation under GenpactNext , as we lead the shift to Agentic AI Solutions&mdashdomain-specific, autonomous systems that redefine how we deliver value to clients. You%27ll help drive the adoption of innovations like the Genpact AP Suite in finance and accounting, with more Agentic AI products set to expand across service lines. Responsibilities: Lead end-to-end implementation of agentic AI solutions across business units. Collaborate with cross-functional teams to define AI agent objectives , autonomy levels, and execution logic. Design, prototype, and deploy agentic AI systems that interact autonomously with users, APIs, data sources, and tools. Translate business requirements into technical design for agent behavior, workflows, and decision-making processes. Evaluate and select frameworks and tools for agentic systems (e.g., LangChain , AutoGPT , CrewAI , ReAct , etc. equivalent in marketplace). Conduct testing, performance optimization, and monitoring of deployed AI agents. Train internal stakeholders on interacting with and supervising AI agents. Stay current on industry trends and emerging technologies in autonomous AI and agent architectures. Qualifications we seek in you! Minimum Qualifications Proven experience in AI/ML solution delivery with a focus on agentic or autonomous systems. Strong understanding of LLMs, orchestration frameworks ( LangChain , Semantic Kernel), APIs, and cloud deployment equivalent in marketplace. Functional knowledge of business domains (finance, HR, logistics , etc.) and ability to map AI capabilities to them. Experience with implementation methodologies and change management. Strong communication and stakeholder management skills . Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up . Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Role Overview We are seeking a highly skilled AI Engineer with 8-12 years of experience to lead the development of Generative AI (GenAI) and Machine learning solutions for internal projects. This role requires a self-driven leader with exceptional communication, strategic thinking, and expertise in data analytics and visualization to deliver innovative GenAI tools tailored to internal team needs while driving cross-functional collaboration. Key Responsibilities - GenAI Development: Design and develop advanced GenAI models (e.g., LLMs, DALL E models) and AI Agents to automate internal tasks and workflows. Exposure to LLMs: Utilize Azure Open AI APIs, experience on models like GPT4o, O3 , llama3 Enhance the existing RAG based application: In depth understanding of stages of RAG - chunking, retrieval etc. - Cloud Deployment: Deploy and scale GenAI solutions on Azure Cloud services (e.g., Azure Function App) for optimal performance. In depth understanding of ML models like linear regression, random forest, decision trees. In depth understanding on clustering and supervised models. - AI Agent Development: Build AI agents using frameworks like LangChain to streamline internal processes and boost efficiency. - Data Analytics: Perform advanced data analytics to preprocess datasets, evaluate model performance, and derive actionable insights for GenAI solutions. - Data Visualization: Create compelling visualizations (e.g., dashboards, charts) to communicate model outputs, performance metrics, and business insights to stakeholders. Stakeholder Collaboration: Partner with departments to gather requirements, align on goals, and present technical solutions and insights effectively to non-technical stakeholders. - Model Optimization: Fine-tune GenAI models for efficiency and accuracy using techniques like prompt engineering, quantization, and RAG (Retrieval-Augmented Generation). LLMOps Best Practices: Implement GenAI-specific MLOps, including CI/CD pipelines (Git, Azure DevOps) - Leadership: Guide cross-functional teams, mentor junior engineers, and drive project execution with strategic vision and ownership. Helicopters, strategic Thinking**: Develop innovative GenAI strategies to address business challenges, leveraging data insights to align solutions with organizational goals. - Self-Driven Execution: Independently lead projects to completion with minimal supervision, proactively resolving challenges and seeking collaboration when needed. - Continuous Learning: Stay ahead of GenAI, analytics, and visualization advancements, self-learning new techniques to enhance project outcomes. Required Skills & Experience - Experience: 8-12 years in AI/ML development, with at least 4 years focused on Generative AI and AI agent frameworks. - Education: BTech/BE in Computer Science, Engineering, or equivalent (Masters or PhD in AI/ML is a plus). - Programming: Expert-level Python proficiency, with deep expertise in GenAI libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, Open AI SDK) and data analytics libraries (e.g., Pandas, NumPy), sk-learn. Mac - Data Analytics: Strong experience in data preprocessing, statistical analysis, and model evaluation to support GenAI development and business insights. - Data Visualization: Proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau) to create dashboards and reports for stakeholders. - Azure Cloud Expertise: Strong experience with Azure Cloud services (e.g., Azure Function App, Azure ML, serverless) for model training and deployment. - GenAI Methodologies: Deep expertise in LLMs, AI agent frameworks, prompt engineering, and RAG for internal workflow automation. - Deployment: Proficiency in Docker, Kubernetes, and CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production-grade GenAI systems. - LLMOps: Expertise in GenAI MLOps, including experiment tracking (e.g., Weights & Biases), automated evaluation metrics (e.g., BLEU, ROUGE), and monitoring. Soft Skills: - Communication: Exceptional verbal and written skills to articulate complex GenAI concepts, analytics, and visualizations to technical and non-technical stakeholders. - Strategic Thinking: Ability to align AI solutions with business objectives, using data-driven insights to anticipate challenges and propose long-term strategies. - Problem-Solving: Strong analytical skills with a proactive, self-starter mindset to independently resolve complex issues. - Collaboration: Collaborative mindset to work effectively across departments and engage colleagues for solutions when needed. Preferred Skills - Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). - Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. - Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. - Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data scien

* Design, develop & maintain Python applications using Langchain & LLMS. * Optimize database performance with PostgreSQL & MySQL. Implement and integrate Retrieval-Augmented Generation (RAG) pipelines using LLMs Provident fund Health insurance

Role: ML Engineer. Exp : 5 Years to 10 Years Location : Hyderabad. Job Overview: Were seeking a ML Engineer / Data Scientist to architect agentic AI solutions and own the full ML lifecycle—from proof-of-concept to production. You’ll operationalize LLMs, build agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks. Key Responsibilities: Operationalize large language models and agentic workflows (LangChain, LangGraph, LlamaIndex) to automate security decision-making and threat response. Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response. Build proof-of-concept GenAI solutions and evolve them into production-ready components on AWS (Bedrock, SageMaker, Lambda, EKS/ECS) using reusable best practices. Implement CI/CD pipelines for model training, validation, and deployment with GitHub Actions, Jenkins, and AWS CodePipeline. Manage model versioning with MLflow and DVC, set up automated testing, rollback procedures, and retraining workflows. Automate cloud infrastructure provisioning with Terraform and develop REST APIs and microservices containerized with Docker and Kubernetes. Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyze performance and optimize costs and SLA compliance. Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows. Qualifications: Bachelor’s or master’s in computer science, Data Science, AI or related quantitative discipline. 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures. In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG). Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI or equivalent agentic frameworks. Strong proficiency in Python and production-grade coding for data pipelines and AI workflows. Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices. Extensive AWS experience with Bedrock, SageMaker, Lambda, EKS/ECS, S3 (Athena, Glue, Snowflake preferred). Infrastructure as Code skills with Terraform. Experience building REST APIs, microservices, and containerization with Docker and Kubernetes. Solid data science fundamentals: feature engineering, model evaluation, data ingestion. Understanding of cybersecurity principles, SIEM data, and incident response. Excellent communication skills for both technical and non-technical audiences. Preferred Qualifications: AWS certifications (Solutions Architect, Developer Associate). Nice to have Experience with Model Context Protocol (MCP) and RAG integrations. Nice to have Experience in Crew.AI Familiarity with workflow orchestration tools (Apache Airflow). Experience with time series analysis, anomaly detection, and machine learning.

Job Title: Generative AI Specialist Experience: Total 7+ Years | Relevant - 3 to 5 Years Location: Hyderabad Employment Type: Full-Time Job Description We are seeking a highly skilled and innovative Generative AI Engineer to join our team. The ideal candidate will have a strong background in designing, developing, and deploying AI models, particularly in the domain of generative AI and large language models (LLMs). Key Responsibilities Design & Development: Architect and build generative AI models, algorithms, and frameworks. Model Implementation: Integrate AI models into existing systems and applications. LLM Expertise: Work with tools like LangChain, Haystack, and apply prompt engineering techniques. Data Handling: Preprocess and analyze data for model training and evaluation. Cross-functional Collaboration: Partner with data scientists, product managers, and other stakeholders. Testing & Deployment: Evaluate model performance and deploy models to production. Monitoring & Optimization: Track model performance and continuously improve results. Research & Innovation: Stay updated with the latest advancements in generative AI. Required Skills Proficiency in Python for AI development. Strong understanding of Generative AI , NLP , and LLMs . Experience with RAG pipelines and vector databases . Familiarity with frameworks like LangChain , Haystack , and other open-source libraries. Knowledge of prompt engineering and tokenization . Experience in fine-tuning and integrating AI models in production. Excellent communication and problem-solving skills. Optional Skills Experience with cloud platforms (GCP, AWS, Azure). Familiarity with MLOps and DevOps practices. Why Join Us? Work on cutting-edge AI technologies. Collaborate with a passionate and talented team. Opportunity to innovate and shape the future of AI applications. How to Apply Interested candidates can apply directly through Naukri or send your updated resume to shilpa.shapur@Excelra.com

Experience required: 7+ years Core Generative AI & LLM Skills: * 5+ years in Software Engineering, 1+ year in Generative AI. * Strong understanding of LLMs, prompt engineering, and RAG. * Experience with multi-agent system design (planning, delegation, feedback). * Hands-on with LangChain (tools, memory, callbacks) and LangGraph (multi-agent orchestration). * Proficient in using vector DBs (OpenSearch, Pinecone, FAISS, Weaviate). * Skilled in Amazon Bedrock and integrating LLMs like Claude, Titan, Llama. * Strong Python (LangChain, LangGraph, FastAPI, boto3). * Experience building MCP servers/tools. * Designed robust APIs, integrated external tools with agents. * AWS proficiency: Lambda, API Gateway, DynamoDB, S3, Neptune, Bedrock Agents * Knowledge of data privacy, output filtering, audit logging * Familiar with AWS IAM, VPCs, and KMS encryption Desired Skills: * Integration with Confluence, CRMs, knowledge bases, etc. * Observability with Langfuse, OpenTelemetry, Prompt Catalog * Understanding of model alignment & bias mitigation

Job Description: AI Engineer (Junior / Associate Level) About the Role We are looking for a passionate and hands-on AI Developer with around 3 years of experience in building and deploying machine learning models and working with the latest AI tools and frameworks. You will be working closely with our data science and engineering teams to develop smart, scalable, and production-ready AI solutions. Key Responsibilities Design, develop, test, and deploy machine learning models for classification, regression, recommendation, or NLP tasks. Work with state-of-the-art AI tools and libraries such as LangChain, Hugging Face, OpenAI, LlamaIndex, etc. Integrate Large Language Models (LLMs) into applications via APIs or custom fine- tuning. Build data pipelines for training and inference, ensuring model performance and robustness. Collaborate with software developers, product managers, and data engineers to turn AI models into usable products. Stay updated with the latest research and innovations in the AI/ML space and bring new ideas into development. Optimize model performance and scale AI solutions for production. Required Skills & Experience Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. 2 to 4 years of hands-on experience in machine learning and deep learning. Proficiency in Python and libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy. Good understanding of LLMs and experience working with platforms like OpenAI, Claude, Cohere, or Hugging Face Transformers. Experience in prompt engineering, fine-tuning, or using frameworks like LangChain, LlamaIndex, or Haystack. Exposure to cloud platforms (AWS, GCP, Azure) and tools like Docker, Git, CI/CD workflows. Strong analytical and problem-solving skills. Understanding of data preprocessing, feature engineering, and model evaluation techniques. Good to Have Experience building AI chatbots or virtual assistants. Knowledge of Vector databases (e.g., Chroma, Pinecone, Weaviate). Familiarity with MLOps tools like MLflow, Kubeflow, Vertex AI, etc. Experience with RESTful APIs or microservices architecture. Participation in Kaggle competitions or open-source AI projects. What We Offer Opportunity to work on real-world AI applications and products. A collaborative, learning-first environment. Exposure to enterprise-grade AI deployments and tools. Flexible working hours and remote work options. Competitive compensation and career growth path.

Req ID: 328577 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 Systems Integration Specialist to join our team in Bangalore, Karn?taka (IN-KA), India (IN). Job Title: Data Scientist Location: Bangalore (Hybrid) Experience: 5-7 years Job Summary: We are looking for a versatile and innovative Data Scientist with experience in Azure Cloud , .NET , ReactJS , and Python (LangChain & FastAPI) to join our cross-functional team. This role blends data science expertise with full-stack development and cloud deployment, enabling intelligent solutions that scale. Key Responsibilities: Design and implement machine learning models and NLP pipelines using Python, LangChain, and FastAPI. Develop and deploy data-driven applications on Microsoft Azure , leveraging services like Azure ML, Azure Functions, and Azure Data Lake. Collaborate with backend developers using .NET and frontend developers using ReactJS to integrate AI models into scalable web applications. Build APIs and microservices to serve ML models and data insights. Perform data wrangling, feature engineering, and model evaluation. Create dashboards and visualizations to communicate insights to stakeholders. Ensure security, scalability, and performance of deployed solutions in the Azure environment. Required Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Strong experience with Python , especially LangChain , FastAPI , and data science libraries (pandas, scikit-learn, etc.). Proficiency in .NET (C#) for backend development. Experience with ReactJS for building interactive UIs. Hands-on experience with Azure Cloud Services (e.g., Azure ML, Azure Functions, Azure DevOps). Solid understanding of RESTful APIs, microservices, and CI/CD pipelines. Strong problem-solving and communication skills. Preferred Qualifications: Experience with LLMs, vector databases, and prompt engineering. Familiarity with containerization (Docker, Kubernetes). Knowledge of MLOps practices and tools. Exposure to Agile/Scrum methodologies. 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.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients . Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Principal Consultant , Generative AI + Agentic AI ! In this role, we are seeking a highly skilled and experienced AI Engineer with hands-on expertise in Generative AI, AWS Bedrock, Azure Open AI, Document Intelligence tools, Huggingface , Agentic AI, and Advanced Data Pipelines . It%27s platforms semantic kernel, autogen , langchain . Responsibilities Architect and implement advanced generative AI models, focusing on applications such as image and text generation, image and document extraction, RAG, Prompt engineering, and synthetic data generation. Advanced Prompt Engineering techniques. Stay at the forefront of AI/ML and generative AI advancements, driving the adoption of new technologies and best practices within the team. Develop, fine-tune, and optimize generative AI models, ensuring they meet performance, scalability, and business objectives . Firm grasp on tools to compare outputs of each model and compare against each other. Apply solid data science principles to enhance AI/ML models, using statistical analysis and machine learning techniques to improve model accuracy and efficiency. Work closely with data engineers, software developers, and product managers to integrate generative AI models into products and services, aligning with business objectives . Ensure that AI models are designed and deployed with ethical considerations, adhering to industry standards and regulatory requirements. Qualifications we seek in you! Minimum Q ualifications / Skills B achelor&rsquos or M aster&rsquos degree in computer science, AI, Machine Learning, Data Science, or a related field, with 5+ years of experience in AI/ML, particularly with generative AI models. Strong expertise in developing and deploying generative AI models. Proficiency in Python and experience with AI development libraries such as TensorFlow and PyTorch . Experience with Azure OpenAI, Open Source LLMs, and LangChain . Solid experience in applying data science principles, including statistical analysis, data preprocessing, and machine learning, to enhance AI/ML models. Preferred Q ualifications / Skills Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning. Familiarity with NLP or computer vision related to generative AI applications. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. For more information, visit Follow us on X , Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training .

Responsibilities Job Responsibilities: Lead the development of Gen AI solutions, including design, implementation, and deployment of AI models and systems Collaborate with cross-functional teams to identify business problems and develop AI-powered solutions to drive growth and efficiency Design and implement scalable and efficient AI solutions, leveraging technologies such as LangChain, Agentic AI, RAG, Event driven architecture using Kafka etc. Develop and maintain large-scale AI systems, ensuring high performance, reliability, and security Lead and mentor a team of AI developers, providing guidance and expertise to ensure high-quality deliverables Stay up-to-date with the latest advancements in Gen AI, Prompt Engineering, and related technologies, applying this knowledge to drive innovation and improvement Develop and maintain technical documentation, including architecture diagrams, design documents, and technical guides Participate in code reviews, ensuring high-quality code and adherence to coding standards and best practices Additional Responsibilities: Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or related field (B.E/B.Tech/M.E/M.Tech/MCA) At least 5-8 years of experience in software development, with a minimum of 2 years of experience in Gen AI Strong proficiency in LangChain, Python, Gen AI, Agentic AI, and Prompt Engineering Excellent communication, teamwork, problem-solving, and leadership skills Technical and Professional Requirements: Preferred Qualifications: Experience with Agentic Frameworks such LangGraph, AutoGen, CrewAI Experience with cloud-based AI platforms, such as AWS or Azure Knowledge of containerization technologies, such as Docker Familiarity with agile development methodologies, such as Scrum or Kanban Experience with AI-related tools and frameworks, such as TensorFlow or PyTorch Strong understanding of software design patterns, principles, and best practices Experience with DevOps practices, including continuous integration and continuous deployment (CI/CD) Certification in AI, machine learning, or related fields, such as Certified Data Scientist or Certified AI Engineer Preferred Skills: Technology->OpenSystem->Python - OpenSystem->Flask Technology->Artificial Intelligence->Artificial Intelligence - ALL Technology->Machine Learning->Python Technology->Programing language C->go lang Technology->Machine Learning->Generative AI->retrieval augmented generation (rag) Educational Requirements Bachelor of Engineering Service Line Information Systems

Role & responsibilities Lead End-to-End ML Projects: Own the full lifecycle of ML solutions from problem scoping, data exploration, model development, deployment, and post-deployment monitoring. Own the Gen AI Strategy: Define and drive the technical vision and execution strategy for Gen AI use cases across the organization. Architect Scalable Solutions: Design robust ML systems and pipelines that integrate seamlessly into production environments. Team Leadership: Mentor and guide a team of ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning. Modeling & Research: Stay up to date with the latest advancements in ML/AI and guide experimentation with novel algorithms (e.g., deep learning, NLP, GenAI, reinforcement learning). Build RAG & Prompt Engineering Pipelines: Design scalable architectures for RAG, vector search, prompt tuning, and prompt chaining with tools like LangChain, LlamaIndex, and FAISS. Stakeholder Collaboration: Work closely with product managers, engineers, and domain experts to translate business problems into technical solutions. Operationalize ML: Partner with MLOps/DevOps teams to deploy, monitor, and maintain ML models in production, ensuring reliability and scalability. Preferred candidate profile Bachelors or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (PhD is a plus). 8+ years of hands-on experience in machine learning, with at least 1–2 years in a leadership or mentorship role. Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, HuggingFace Transformers, etc. Strong understanding of statistics, optimization, and model evaluation techniques. Experience with cloud platforms (AWS, GCP, or Azure) and tools like Docker, Kubernetes, MLflow, or Kubeflow. Proficiency in Python and Gen AI frameworks such as LangChain, Crew AI, or similar. Proven track record of deploying ML models into production at scale. Excellent communication and leadership skills.

About Client Hiring for One of the Most Prestigious Multinational Corporations Job Title: Generative AI Engineer Experience: 8 to 13 years Key Responsibilities : Research, design, and implement Generative AI solutions using foundation models like GPT, PaLM, Claude, or open-source LLMs (e.g., LLaMA, Falcon). Build and fine-tune custom models using Transfer Learning , RLHF , or LoRA for domain-specific applications. Develop intelligent applications using Natural Language Processing (NLP) , Computer Vision , or Multimodal AI . Apply data science techniques for feature engineering, model evaluation, and experimentation. Architect scalable ML pipelines using tools such as MLflow , Kubeflow , Vertex AI , SageMaker , or equivalent. Collaborate with cross-functional teams to understand business challenges and deliver GenAI-driven solutions. Ensure responsible AI practices by implementing explainability, bias detection, and governance mechanisms. Stay up to date with the latest research and trends in AI/ML, LLMs, and GenAI technologies. Technical Skills: Strong hands-on experience with core AWS services: EC2, S3, RDS, Lambda, IAM, VPC, CloudWatch, CloudTrail, ECS/EKS, etc. Expert in Infrastructure as Code (IaC) using Terraform , CloudFormation , or AWS CDK . Strong scripting and automation skills in Python , Bash , or Shell . Experience with containerization and orchestration tools ( Docker , Kubernetes /EKS). Solid understanding of networking, load balancing, and security concepts in the cloud. Experience with monitoring/logging tools like CloudWatch , Prometheus , Grafana , or ELK stack Knowledge of DevOps and CI/CD tools (Jenkins, GitLab CI, AWS CodePipeline, etc.). Familiarity with Agile/Scrum methodologies NOTE : Only immediate and 15 days joiners Notice period : Only immediate and 15 days joiners Location: Bangalore Mode of Work : WFO(Work From Office) Thanks & Regards, SWETHA Black and White Business Solutions Pvt.Ltd. Bangalore,Karnataka,INDIA. Contact Number:8067432433 rathy@blackwhite.in |www.blackwhite.in

JD: 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. Role & responsibilities Preferred candidate profile

We are seeking a passionate and driven Generative AI Engineer to design, develop, and deploy innovative AI applications using Large Language Models (LLMs). The ideal candidate will have hands-on experience with prompt engineering, Python programming, and foundational knowledge of AI orchestration frameworks like LangChain and LangGraph. Experience with the Model Context Protocol (MCP) is a significant advantage. You will work closely with senior AI engineers and cross-functional teams to bring cutting-edge generative AI solutions to life Role & responsibilities Generative AI Application Development: Design, build, and deploy AI applications leveraging LLMs for various use cases such as RAG (Retrieval-Augmented Generation) based chatbots, intelligent agents, content generation, and more. Prompt Engineering: Develop, test, and optimize advanced prompt engineering techniques (e.g., few-shot, Chain-of-Thought, ReAct) to enhance LLM performance, accuracy, and user experience. LLM Orchestration with LangChain & LangGraph: Utilize LangChain and LangGraph to build robust, stateful, and multi-agent AI systems, managing complex conversational flows and integrating external tools and data sources. Python Development: Write clean, efficient, and well-documented Python code for AI model integration, data preprocessing, API development, and general application logic. Model Context Protocol (MCP): Implement and leverage MCP for seamless interaction between LLMs and external systems, ensuring efficient context management and secure communication (if applicable to project needs). Model Evaluation & Testing: Assist in evaluating the performance of generative AI models, defining relevant metrics, and conducting rigorous testing to ensure reliability and effectiveness. Collaboration: Work collaboratively with data scientists, machine learning engineers, product managers, and other stakeholders to translate business requirements into technical solutions. Research & Innovation: Stay updated with the latest advancements in generative AI, LLMs, and related frameworks, and actively experiment with new approaches to improve existing solutions. Deployment & MLOps (Basic): Contribute to the deployment of AI models and understand basic MLOps practices for model versioning, monitoring, and continuous improvement. . Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related quantitative field. 1-3 years of hands-on experience in machine learning, software development, or data science, with exposure to AI/ML projects. Strong proficiency in Python programming and familiarity with relevant libraries (e.g., NumPy, Pandas). Proven experience with LangChain for building LLM-powered applications and chaining together various components. Familiarity with LangGraph for orchestrating complex, stateful multi-agent workflows. Hands-on experience with prompt engineering and optimizing prompts for LLMs. Understanding of Large Language Models (LLMs) and their underlying concepts. Experience or strong understanding of Model Context Protocol (MCP) for connecting LLMs with external tools and data sources. Excellent problem-solving skills and a proactive approach to challenges. Strong communication and interpersonal skills, with the ability to articulate technical concepts clearly.) Preferred Skills : Experience with cloud platforms (Azure, AWS, GCP) for deploying AI/ML solutions. Microsoft Certified: Azure AI Engineer Associate (AI-102) or similar AI/ML certification. Familiarity with vector databases (e.g., Pinecone, Chroma, FAISS). Experience with deep learning frameworks such as TensorFlow or PyTorch. Knowledge of Natural Language Processing (NLP) techniques beyond LLMs. Experience in building conversational AI systems or chatbots

JOB DESCRIPTION Title: Senior Software Engineer - Data Science Full time Chennai Data Scientist Role Type: Location: Reports to: Summary of the profile: We are seeking a highly motivated and innovative Data Scientist with 3-5 years of experience to join our team, with a focus on leveraging Generative AI and Large Language Models (LLMs). The ideal candidate will be passionate about exploring the potential of these cutting-edge technologies to solve complex problems and create impactful solutions. You will collaborate with cross-functional teams to research, develop, and deploy generative AI models and LLM-powered applications. What youll do here: Explore and experiment with various generative AI models (e.g., GANs, VAEs, diffusion models) and LLMs (e.g., GPT, BERT, Llama). ¢ Fine-tune pre-trained LLMs for specific tasks and domains. Develop and implement generative models for tasks like data augmentation, content generation, and synthetic data creation. ¢ ¢ ¢ Prompt engineering, and prompt iteration. Collect, clean, and preprocess large text datasets for LLM training and evaluation. Perform natural language processing (NLP) tasks such as text classification, sentiment analysis, and entity recognition. ¢ ¢ Use LLMs to assist in data cleaning and data understanding. Develop and evaluate machine learning models, including those leveraging generative AI and LLMs. ¢ Evaluate model performance using relevant metrics and techniques, including those specific to LLMs (e.g., perplexity, BLEU score). ¢ ¢ Tune hyperparameters to optimize model performance. Create compelling visualizations and reports to communicate insights from generative AI and LLM experiments. ¢ ¢ Present findings to both technical and non-technical audiences. Collaborate with engineers, product managers, and researchers to define project requirements and deliver solutions. ¢ ¢ Communicate effectively with team members and stakeholders, both verbally and in writing. Stay up-to-date with the latest advancements in generative AI and LLMs. Copyright © RESULTICKS Solution Inc 1 ¢ ¢ Assist in deploying generative AI models and LLM-powered applications to production environments. Monitor model performance and retrain models as needed. What you will need to thrive: ¢ ¢ 3-5 years of professional experience in data science, with a growing interest in Generative AI and LLMs. Proficiency in Python and relevant libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers). ¢ ¢ ¢ ¢ ¢ ¢ Experience with NLP techniques and libraries. Understanding of machine learning algorithms and statistical concepts. Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI). Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience with Prompt engineering, version control systems like Git and cloud platforms like GCP, AWS or Azure is a plus Preferred Skills: ¢ ¢ ¢ ¢ ¢ ¢ Experience with fine-tuning LLMs for specific tasks. Experience with deploying LLMs in production environments. Knowledge of deep learning architectures relevant to generative AI and LLMs. Familiarity with vector databases. Experience with RAG (Retrieval Augmented Generation) architectures. Experience with the Langchain Library. Education: ¢ Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. Core competencies: ¢ Communication, Analytical & Problem-Solving Skills Copyright © RESULTICKS Solution Inc 2 About RESULTICKS RESULTICKS is a fully integrated connected experience platform for Real Time Audience Engagement. RESULTICKS empowers brands to create data-driven communications to their audiences and drives business decisions through its award-winning, AI-powered big data cloud solution. Supported by the worlds first customer data blockchain, RESULTICKS unlocks incredible digital transformation possibilities by delivering the full 360 view of the customer through data consolidation and omnichannel orchestration. Built from the ground up by experts in marketing, technology, and business management, RESULTICKS enables brands to make a transformational leap to conversion- driven, growth-focused personalized engagement. With an advanced CDP at its core. RESULTICKS offers AI-powered omnichannel orchestration, complete analytics, next-best engagement, attribution at the segment-of-one level, and the worlds first marketing block chain. ¢ RESULTICKS has been named to the Gartners Magic Quadrant 2021 for Multichannel Marketing Hubs for five years in a row and has been awarded with the Microsoft Elevating Customer Experience with AI award. ¢ Headquartered in Singapore and New York City, RESULTICKS is one of the top global martech solutions servicing both B2B/B2B2C and B2C segments. RESULTICKS global presence includes the United States, India, Singapore, Indonesia, Malaysia, Vietnam, Thailand, and the Philippines. Watch video on RESULTICKS - https://www.youtube.com/watch?v=G_OwGy6unP8 Copyright © RESULTICKS Solution Inc 3

Role & responsibilities We are looking for Senior Gen AI Engineer permanent position with MNC company for Remote. Preferred candidate profile Senior Gen AI Engineer GenAI / ML (Python, Langchain) Full Time Focus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5 to 5 years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like ML flow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills. Preferred candidate profile

3 - 5 years of experience in AI/ML development, with at least 1 year specifically working with LLMs or autonomous systems Strong programming skills in Python and familiarity with ML frameworks (PyTorch, TensorFlow) Experience with various models available and deployments on AWS, Azure, and GCP. Experience using pre-trained models and training models when required. Experienced with Azure AI platform. Experience working with modern language models (e.g., GPT-4, Claude, LLaMA, Mistral) Knowledge of prompt engineering, chain-of-thought reasoning, and LLM fine-tuning Understanding of agent frameworks such as LangChain, AutoGPT or similar. Experienced with integration platforms like UI-path, Alteryx etc. Familiarity with reinforcement learning and/or reinforcement learning through human feedback techniques Excellent understanding of REST APIs Skills: aws,modern language models , ui-path , gcp , alteryx , pytorch , ai / ml development , autogpt , ml , azure , integration platforms,prompt engineering,agent frameworks,azure ai platform,reinforcement learning,model training,llm fine-tuning,python,rest apis,pre-trained models,langchain,tensorflow

Role: AIML Engineer Experience: 2 to 8 Yrs Notice period: 0- 10 Days Job Location: Hyderabad and Bangalore. (Hybrid) Job Description: Strong proficiency in Python for AI/ML development. Hands-on experience with OpenAI, GPT models, and LangChain or LlamaIndex. Deep understanding of Retrieval-Augmented Generation (RAG) concepts and implementations. Familiarity with vector databases like FAISS, Pinecone, or Weaviate. Good knowledge of data engineering principles (ETL, data modeling, batch/streaming pipelines). Experience with cloud platforms (Azure, AWS, or GCP) for deploying AI/ML solutions. Proficient in tools like Pandas, NumPy, Scikit-learn, and MLflow. Exposure to LLMOps, model versioning, and monitoring is a plus.

We are seeking a skilled and motivated Python Developer with 4–9 years of hands-on experience in designing, developing, and deploying robust backend solutions. The ideal candidate will have a strong foundation in Python, a passion for clean code. Required Candidate profile AI Capabilities - NLPs & RAG - Fine-Tuning: PEFT - Transformers & Vectorization: Hugging Face, TF-IDF, Embeddings, Qdrant, Pinecode - LLMs: OpenAI, Claude - Interactive AI Apps: Streamlit, FastAPI

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Our client is leading Global IT Service and Consulting Organization Role : Gen AI Lead/ Architect Exp : 10+ years Location. : Bangalore, Chennai, Hyderabad NP: Immediate to 30 days Job Description : Mandatory Skills : Gen AI, LLM, ML/DL/NLP, RAG, Lang chain, Mistral, Llama, Hugging Face, Python, Tensorflow, Pytorch, Django, Vector DB, Preferred Skills : GCP/Azure/AWS, Databricks, MLOps (tools like Kubeflow/ Mlflow) , Kubernetes, GitHub/Bitbucket, ADO, GPT-4