30 Langraph Jobs

As a Platform Development and Machine Learning expert at Adobe, you will play a crucial role in changing the world through digital experiences by building scalable AI platforms and designing ML pipelines. Your responsibilities will include: - Building scalable AI platforms that are customer-facing and evangelizing the platform with customers and internal stakeholders. - Ensuring platform scalability, reliability, and performance to meet business needs. - Designing ML pipelines for experiment management, model management, feature management, and model retraining. - Implementing A/B testing of models and designing APIs for model inferencing at scale. - Demonstrating proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. - Serving as a subject matter expert in LLM serving paradigms and possessing deep knowledge of GPU architectures. - Expertise in distributed training and serving of large language models and proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. - Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results. - Reducing training and resource requirements for fine-tuning LLM and LVM models. - Having extensive knowledge of different LLM models and providing insights on the applicability of each model based on use cases. - Delivering end-to-end solutions from engineering to production for specific customer use cases. - Showcasing proficiency in DevOps and LLMOps practices, including knowledge in Kubernetes, Docker, and container orchestration. - Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Your skills matrix should include expertise in LLM such as Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama, LLM Ops such as ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI, Databases/Datawarehouse like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery, Cloud Knowledge of AWS/Azure/GCP, Dev Ops knowledge in Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus, and Cloud Certifications (Bonus) in AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert. Proficiency in Python, SQL, and Javascript is also required. Adobe is committed to creating exceptional employee experiences and values diversity. If you require accommodations to navigate the website or complete the application process, please contact accommodations@adobe.com or call (408) 536-3015.,

The Data Science Analyst role is a developing professional position within the GWFO team, focusing on applying specialized knowledge in machine learning, statistical modeling, and data analysis. This role involves monitoring, assessing, analyzing, and evaluating processes and data to drive business outcomes and generate actionable insights through advanced analytics. The Data Science Analyst will work on identifying opportunities to enhance business decision-making capabilities, automate processes, and develop innovative AI solutions. Key Responsibilities: - Gather and analyze operational data from various stakeholders to assess past business performance and identify areas for improvement. - Utilize machine learning techniques to identify data patterns and trends, providing insights to enhance decision-making in areas such as business planning, process improvement, and solution assessment. - Develop and implement machine learning models for predictive analytics, forecasting, and optimization. - Design and deploy Generative AI solutions to enhance customer experience, automate tasks, and personalize interactions. - Experiment with agentic AI frameworks to create autonomous systems that can learn, adapt, and solve complex problems. - Evaluate the performance and impact of AI solutions, translating data into actionable insights for targeting and segmentation strategies. - Collaborate with internal and external stakeholders to build, implement, track, and improve decision strategies. - Ensure compliance with applicable laws, rules, and regulations, safeguarding Citigroup's reputation and assets. Skills and Experience: - 7+ years of relevant experience in data science, machine learning, or related fields. - Strong process management skills with attention to detail. - Curiosity and willingness to learn new skill sets, particularly in artificial intelligence. - Proficiency in Python programming and relevant data science libraries like scikit-learn, TensorFlow, PyTorch, and Transformers. - Experience in statistical modeling techniques, including regression, classification, and clustering. - Knowledge of building GenAI solutions using LLMs and vector databases. - Familiarity with agentic AI frameworks and data visualization tools like Tableau or Power BI. - Strong logical reasoning, willingness to learn, and effective communication and presentation skills. Education: - Bachelor's/University degree or equivalent experience This job description offers an overview of the primary responsibilities and requirements for the Data Science Analyst role within the Decision Management job family, specialized in Specialized Analytics (Data Science/Computational Statistics).,

You will be serving as a Gen AI Technical Developer for our client, a trusted global innovator of IT and business services. Your primary responsibility will be to design, develop, and optimize generative AI models using AWS Bedrock. Collaboration with cross-functional teams to comprehend project requirements and deliver AI-driven solutions will be a key aspect of your role. Your experience should include a minimum of 7 years in hands-on Gen AI Technical development. You will be expected to conduct thorough research to remain informed about the latest advancements in generative AI and machine learning. Additionally, it will be crucial for you to implement and maintain AI-centric libraries and frameworks such as langchain and langraph. Data pre-processing, augmentation, and generation of synthetic data to enhance model performance will also be part of your duties. You will evaluate and fine-tune AI models to guarantee high-quality content generation. Furthermore, experimenting with top foundation models, customizing them with your data, and building agents to perform tasks using enterprise systems and data sources through AWS Bedrock will be one of your responsibilities. Documentation and presentation of findings, methodologies, and results to stakeholders are also expected from you. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI model performance and accuracy. Moreover, writing clean, high-quality, high-performance, and maintainable code will be essential. Supporting software development, database integration, interfaces, and new functionality enhancements are part of the role. Collaboration with cross-functional teams, ensuring projects meet business objectives and compliance standards, supporting the testing and deployment of new products and features, and participating in code reviews will be key responsibilities. A Bachelor's degree in Computer Science or a related field is a required qualification for this position.,

Senior Data Scientist(6-8 Yrs) Data Scientist Manager (Architect Exp is mandatory) :- 8-12 Yrs As a Senior Data Scientist/Manager specializing in Generative AI, you will: Shape Next-Generation Solutions : Partner with cross-functional teams to design and implement AI-driven systems that transform user experiences and streamline business processes. Enhance AI Through Data : Employ data-centric methodologies to improve model accuracy and responsiveness by curating high-quality datasets and optimizing real-time performance. Finetune Industry-Specific Gen AI Models : Adapt and fine-tune large language models for domain-specific applications using advanced techniques like instruction tuning, domain adaptation, and reinforcement learning from human feedback (RLHF). Develop Intelligent AI Agents : Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications : Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology : Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency. Key Responsibilities Design AI Systems : Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization. Develop NLP Pipelines : Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation. Integrate Multi-Modal Systems : Combine data modalities such as text, images, and metadata for enriched user interactions and insights. Optimize AI Pipelines : Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production. Collaborate on AI Innovation : Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions. EXPERIENCE BS/MS in Computer Science, Math, Physics, Engineering, Statistics, or another quantitative or computational field. Advanced degrees preferred. Fine tuning experience of Large Language models (LLMs, VLLMs, or Vision model) Distributed training or inference experience with frameworks like Ray, vllm, openllm, bentoML etc. Experience with frameworks like like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. Deployment experience or optimized hosting experience of Large Language models (LLMs, VLLMs, or Vision model) Experience working with any Vector database like Milvus, FAISS, ChromaDB etc Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc Experience with prompt engineering Keeping up with latest market trends Experience working with open source large language models from HuggingFace Experience working with atleast one public cloud provider such as Azure, AWS or GCP Experience working with container technology like Docker, ECS etc Experience with DevOps practices and CI/CD pipelines for data solutions Experience in deploying solutions to production with Kubernetes or OpenShift Experience with managing ML workflows with MLFlow or KubeFlow

As a Data Science Subject Matter Expert (SME) at Citi, you will play a crucial role in applying advanced data science techniques to enhance the control environment. Your primary responsibility will involve leading data analysis and modeling efforts to identify opportunities for improving control processes and mitigating risks. Leveraging your expertise, you will develop and implement cutting-edge machine learning and AI algorithms to automate tasks, enhance decision-making, and increase overall control effectiveness. In addition, you will design and build innovative AI solutions using generative AI and agentic AI frameworks tailored for Control Automation. Furthermore, as a subject matter expert in data science and control automation, you will provide technical guidance and mentorship to team members. You will evaluate new data sources, tools, and technologies to enhance the performance and capabilities of AI solutions continuously. Collaboration with cross-functional teams, including business stakeholders, technology partners, and control functions, will be vital to align data science initiatives with business objectives effectively. Your role will also involve conducting rigorous testing and validation of AI models to ensure accuracy, reliability, and compliance with regulatory requirements. It is essential to communicate complex technical concepts and findings to non-technical audiences, offering insights and recommendations to drive strategic decision-making. Staying updated with the latest developments in data science, machine learning, and AI will be crucial to fostering innovation in control automation. Moreover, you must adhere to Citi's risk management policies and guidelines, ensuring responsible and ethical conduct in all data science activities. The ideal candidate for this position should possess 6 to 9 years of relevant experience in data science, machine learning, or a related field. Strong process management skills, attention to detail, and a keen interest in developing new skill sets in artificial intelligence, especially control automation, are essential. Proficiency in Python programming and relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers is required. Experience with statistical modeling techniques, data visualization tools like Tableau or Power BI, as well as exposure to GenAI and agentic AI frameworks, will be advantageous. In addition, having a Bachelor's/University degree in a quantitative field like computer science, statistics, mathematics, or engineering is necessary, with a Master's degree being preferred. If you have a disability and require accommodations to utilize search tools or apply for career opportunities at Citi, please review the Accessibility at Citi guidelines. You can also refer to Citi's EEO Policy Statement and the Know Your Rights poster for further information.,

Job Description Youll be a core member of our AI team, designing, implementing, and optimizing GenAI applications for live, real-time deployments. Our projects frequently involve prompt engineering , vector databases , frameworks like LangChain , Langraph , and agentic tools such as AutoGen and Crew . Youll help build production-ready solutions for tasks like text generation, summarization, and Q&A systemsoften within a cloud environment like Azure, AWS and/or GCP. Responsibilities Advanced Python Proficiency: Write clean, efficient, and maintainable Python code for data preprocessing, model training, and integration with production systems. Prompt Engineering: Design, test, and refine prompts to produce optimal AI-driven outputs (chatbots, content generation, etc.). Retrieval-Augmented Generation (RAG): Implement techniques that combine model outputs with external data sources to improve accuracy in real-world scenarios. LangChain & Langraph Integration: Leverage these libraries to build modular, scalable AI pipelines for language-based tasks. Vector Database Management: Work with databases like Pinecone, Faiss, or other vector stores to store embeddings and enable efficient semantic search. Chunking Techniques: Develop methods to split large documents into manageable sections, ensuring more accurate and efficient retrieval and generation. Streamlit (or Similar) Prototyping: Create user-facing dashboards or internal tools to visualize and interact with AI functionalities. Metrics & Performance Tracking: Implement monitoring and logging solutions to track performance metrics (response time, accuracy, user engagement) and identify areas of improvement. Collaboration & Documentation: Participate in code reviews, maintain thorough documentation, and share best practices with cross-functional teams. What Were Looking For Education: Bachelors degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience). AI/ML Foundations: Familiarity with NLP, machine learning fundamentals, and deep learning frameworks (e.g., PyTorch or TensorFlow). Programming Skills: Solid Python background; comfort with libraries like NumPy, pandas, and familiarity with concurrency or parallelism is a plus. Hands-On Project Experience: Coursework or personal projects involving LLMs, vector databases, or text analysis; experience deploying real-time AI solutions is a bonus. Cloud Familiarity: Exposure to either Azure or AWS; ability to learn how to set up virtual machines, container services, or serverless functions. Adaptability: Excitement about experimenting with new libraries (LangChain, Langraph) and emerging large language models. Curiosity & Team Spirit: Eagerness to learn, collaborate, iterate quickly, and stay current on GenAI trends. Good to Have Agentic Frameworks: Experience or interest in frameworks like AutoGen, Crew, or other agentic systems for automating AI-driven tasks. MLOps & Tooling: Familiarity with containerization (Docker), CI/CD pipelines, or other DevOps practices for robust AI model deployment. Advanced Python Libraries: Proficiency in data processing libraries (e.g., pandas, Dask) and knowledge of parallelization techniques. Cloud Deployment: Use either Azure or AWS to configure and deploy AI models, ensuring scalability, security, and optimal performance for live applications. Full-Stack Knowledge: Understanding of front-end technologies for better integration of AI-backed features in web or mobile interfaces. About Us Emids is a leading provider of digital transformation solutions to the healthcare industry, serving payers, providers, life sciences, and technology firms. Headquartered in Nashville, Emids helps bridge critical gaps in providing accessible, affordable, and high-quality healthcare by providing digital transformation services, custom application development, data engineering, business intelligence solutions, and specialized consulting services to all parts of the healthcare ecosystem. With nearly 2000 plusprofessionals globally, Emids leverages strong domain expertise in healthcare-specific platforms, regulations, and standards to provide tailored, cutting-edge solutions and services to its clients. At Emids, we are guided by our core values of "Trusted guides", "Impact obsessed" and " Inclusive innovators". We expect all Emidsians, including our candidates and partners, to embody these values in their day-to-day work. We&aposre not scared of differences. It&aposs how we break new ground. As we scale and elevate the experience of our clients in the healthcare and life sciences space and ultimately have an impact on every patient from every walk of life, the team we build must reflect the diversity that we serve. Together, we&aposve built and will continue to grow, a diverse and inclusive culture where everyone has a seat at the table and the space to be their most authentic self. Emids believes in being an Equal Opportunity Employer and we support, celebrate, and cherish all the things that make our teammates who they are. Show more Show less

The Spec Analytics Intmd Analyst role is a developing professional position where you deal with most problems independently and have the latitude to solve complex issues. By integrating in-depth specialty area knowledge with a solid understanding of industry standards and practices, you contribute to achieving the objectives of the sub function/job family. Your analytical thinking and knowledge of data analysis tools and methodologies are crucial, requiring attention to detail to make informed judgments and recommendations based on factual information. You will typically handle variable issues with potential broader business impact, applying professional judgment when interpreting data and results in a systematic and communicable manner. Developed communication and diplomacy skills are essential to exchange potentially complex/sensitive information and have a moderate but direct impact on the businesses" core activities. The quality and timeliness of service you provide will affect the effectiveness of your team and other closely related teams. Responsibilities: - Work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies - Identify and compile data sets using various tools (e.g. SQL, Access) to predict, improve, and measure the success of key business outcomes - Document data requirements, data collection/processing/cleaning, and exploratory data analysis, which may involve utilizing statistical models/algorithms and data visualization techniques - Specialize in marketing, risk, digital, and AML fields - Appropriately assess risk when making business decisions, ensuring compliance with applicable laws, rules, and regulations, safeguarding Citigroup, its clients, and assets Skills and Experience: - 5+ years of relevant experience in data science, machine learning, or a related field - Advanced process management skills, organized, and detail-oriented - Curiosity in learning and developing new skill sets, particularly in artificial intelligence - Positive outlook with a can-do mindset - Strong programming skills in Python and proficiency in relevant data science libraries like scikit-learn, TensorFlow, PyTorch, and Transformers - Experience with statistical modeling techniques, including regression, classification, and clustering - Experience building GenAI solutions using LLMs and vector databases - Experience with agentic AI frameworks such as Langchain, Langraph, MLOps - Experience with data visualization tools like Tableau or Power BI - Must-have skills: Strong logical reasoning capabilities, willingness to learn new skills, good communication and presentation skills Education: - Bachelors/University degree or equivalent experience This job description offers a high-level overview of the work performed, and additional job-related duties may be assigned as required.,

AlgoAnalytics is seeking a Data Scientist with a strong passion for developing AI/ML solutions and working on cutting-edge projects in Gen AI. The ideal candidate should have a minimum of 3 years of experience in AI/ML, including Deep Learning, and exposure to Gen AI/LLM. Proficiency in tools, technologies, and libraries such as Agentic AI, Dify/Autogen, Langraph, etc., is required. Additionally, a detailed understanding of Cloud technologies and deployment, along with hands-on experience, is considered a significant advantage. As a Data Scientist at AlgoAnalytics, your responsibilities will include developing Gen AI/LLM models using OpenAI, Llama, or other open-source/offline models. You will leverage Agentic AI frameworks and tools like Dify, Autogen, Langraph to build intelligent systems. Your role will also involve prompt engineering, fine-tuning, and dataset-specific model optimization. Implementing cutting-edge research from AI/ML and Gen AI domains and working on cloud-based deployments of AI/ML models for scalability and production readiness are crucial aspects of this position. In terms of leadership and mentoring, you will troubleshoot AI/ML, Gen AI, and cloud deployment challenges. Additionally, you will mentor junior team members, contribute to their skill development, and identify team members for mentoring, hiring, and technical initiatives. Ensuring smooth project execution, deadline management, and positive client interactions are key components of your role. Your involvement in research and innovation will entail exploring and implementing recent AI/ML research in practical applications. Furthermore, you will contribute to research publications, internal knowledge-sharing, and AI innovation efforts. To qualify for this position, you should have 2-3 years of hands-on experience in Machine Learning, Deep Learning, and Gen AI/LLMs. A Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or Statistics (with strong programming knowledge) is required. Your skills should include strong expertise in Python and relevant ML/AI libraries for programming. Deep understanding of Machine Learning, Deep Learning, and Generative AI/LLMs is essential. Experience with Agentic AI tools like Dify, Autogen, Langraph, and similar technologies is highly valued. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps deployment pipelines is also expected. Effective communication, leadership abilities, team management skills, meeting project deadlines, and collaborating with clients are crucial attributes for this role. Please note that preference will be given to candidates based in Pune, and candidates available to join immediately will be prioritized.,

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

Must Have Skills: 2+ years of hands-on experience in agentic AI / multi-agent systems. Proficiency with LangChain, Langraph, CrewAI, AutoGen, Haystack, or equivalent frameworks. Strong background in Python and experience with prompt engineering, tools integration, and chaining logic. Solid understanding of LLM APIs, RAG, vector stores, tool use, and memory architectures. Hands-on experience with open-source and commercial LLMs (e.g., GPT-4, Claude, Gemini, Mistral). Experience deploying AI agents in cloud-native environments (AWS, GCP, Azure). Ability to lead architectural discussions, PoCs, and hands-on development in fast-paced environments. Model-cost profiling and budgeting (API call minimization, batch vs. streaming) Latency tuning for real-time agents, Autoscaling strategies." Exposure to Autonomous AI agents (AutoGPT, BabyAGI, CAMEL, MetaGPT). Understanding of LLM fine-tuning, adapters, and RLHF. Experience with agent simulation, environment modeling, or reinforcement learning is a plus. Familiarity with compliance, privacy, and safety in GenAI deployments. Prior experience in building domain-specific agents (Lifescience, healthcare, Pharma). Key Responsibilities: Architect and implement agentic AI systems using modern LLM orchestration frameworks (LangChain, CrewAI, AutoGen, etc.). Design multi-agent collaboration models including planner-solver, autonomous teams, and goal decomposition agents. Build reusable tooling, APIs, and memory architectures for agent interaction, coordination, and context persistence. Lead hands-on development and deployment of GenAI applications (e.g., assistants, copilots, decision support). Evaluate and integrate LLMs (OpenAI, Claude, Mistral, LLaMA, etc.), vector databases (Pinecone, Weaviate, FAISS), and retrieval systems (RAG). Optimize agent performance for real-time environments, reliability, scalability, and ethical constraints. Guide teams in adopting agent frameworks, best practices, prompt engineering, and model fine-tuning. Collaborate with stakeholders to translate business requirements into technical solutions using agent-based paradigms. Continuously monitor trends in multi-agent systems, cognitive architectures, and open-source AI frameworks.

Crew AI Engineer Remote Contractual-6 months Job Description : We are looking for people with strong python skills, knowledge of multi agent frameworks like Crew AI, knowledge of RAG concepts mandatory. Good conceptual knowledge of LLM concepts Langraph and Langchain Required Skills : 5-8 years of experience in AI/ML or automation engineering. Strong hands-on experience with CrewAI or other LLM orchestration frameworks like LangChain, AutoGen, or Semantic Kernel. Proficiency in Python, including experience with async programming and API integration. Deep understanding of LLMs (OpenAI, Anthropic, Mistral, etc.) and prompt engineering. Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and embeddings. Experience building and deploying production-ready agent-based solutions. Strong problem-solving skills and ability to translate business requirements into technical implementations.

The Specialized Analytics Manager provides full leadership and supervisory responsibility. You will provide operational/service leadership and direction to team(s). You will apply in-depth disciplinary knowledge through provision of value-added perspectives or advisory services. You may contribute to the development of new techniques, models, and plans within the area of expertise. Excellent communication and diplomacy skills are required for this role. You will generally have responsibility for volume, quality, timeliness of end results, and shared responsibility for planning and budgets. Your work will affect an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family. You will have full supervisory responsibility, ensuring motivation and development of the team through professional leadership. This will include duties such as performance evaluation, compensation, hiring, disciplinary and terminations, as well as direction of daily tasks and responsibilities. The Data Science Analyst is a developing professional role within the GWFO team. In this role, you will apply specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. You will identify opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, you will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications. You will work with cross-functional stakeholders to gather and process operational data from various sources to examine past business performance and identify areas for improvement. As a successful candidate, you should ideally have 7+ years of relevant experience in data science, machine learning, or a related field. You should possess advanced process management skills, be organized and detail-oriented, curious about learning and developing new skill sets, particularly in the area of artificial intelligence, have a positive outlook with a can-do mindset, and strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers. Experience with statistical modeling techniques, building GenAI solutions, agentic AI frameworks, and data visualization tools such as Tableau or Power BI is required. Strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are also essential. You should have a Bachelors/University degree or equivalent experience. This job description provides a high-level review of the types of work performed, and other job-related duties may be assigned as required. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster.,

As a part of the global leader in Cloud, AI, and Digital technologies, you will be responsible for leveraging GenAI models and frameworks to enhance the efficiency and productivity of businesses worldwide. Your role will involve serving as the primary technical expert for GenAI technologies, focusing on developing, implementing, and optimizing advanced AI models and solutions to expand our GenAI footprint across clients. You will provide technical leadership, drive innovation, and ensure the successful integration of AI technologies into our IT services for clients. Your responsibilities will include defining best practices, standards, and templates for AI solutions, conducting workshops, demos, and client presentations on GenAI use cases, and collaborating closely with cross-functional teams to identify, evaluate, and implement use cases across different customers. In addition, you will evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities, provide technical leadership, mentorship, and guidance to teams, troubleshoot and resolve complex platform integration and functionality issues. You will also be hands-on in independently building quick prototypes and demonstrating them to key decision-makers. To be successful in this role, you should have 10+ years of total IT experience with at least 3-4 years of hands-on experience with AI/GenAI technologies. Expertise in NLP, NLU, NLQ, and NLG technologies is essential, along with Core Python proficiency to build applications and engineer GenAI solutions at an enterprise scale. You must have delivered production-grade projects on agentic AI frameworks, as well as hands-on experience with agentic AI frameworks such as Autogen, Langraph, or Crew.AI. Experience with NLQ to SQL-based GenAI applications using core Python tools and frameworks, databases, data warehouses, and data lakes on cloud platforms is required. Deep knowledge of architecting product-scale GenAI applications on Microsoft Azure Cloud, AWS Cloud, or GCP cloud environments is a must. Strong programming skills in Python, Node.js, Java, or similar, API programming, familiarity with LLMs, prompt engineering, fine-tuning, and embeddings are desired. Excellent problem-solving skills, solution architecture capabilities, and client-facing communication skills are essential. The ability to translate business needs into technical solutions, manage multiple projects and priorities in a fast-paced environment, and work with cloud platforms is crucial. Moreover, expertise in building technical proposals with winning engineering architectures and technical articulation for CXO level audience, and experience in developing fast PoVs and blueprints on new and emerging GenAI models, tools, frameworks, and other stack will be advantageous for this role.,

The Data Science Analyst role at Citi within the GWFO team is a developing professional position that involves applying specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. The main responsibilities include identifying opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, the individual in this role will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications, while collaborating with cross-functional stakeholders. As a Data Science Analyst at Citi, you will be expected to: - Gather and process operational data from various cross-functional stakeholders to examine past business performance and identify areas for improvement. - Apply machine learning techniques to identify data patterns and trends and provide insights to enhance business decision-making capabilities in various areas. - Develop and implement machine learning models for predictive analytics, forecasting, and optimization. - Design, build, and deploy Generative AI solutions to enhance customer experience, automate tasks, and personalize interactions. - Experiment with agentic AI frameworks to create autonomous systems that can learn, adapt, and solve complex problems. - Develop tools and techniques to evaluate the performance and impact of AI solutions. - Translate data into consumer or customer behavioral insights to drive targeting and segmentation strategies and effectively communicate findings to business partners and senior leaders. - Continuously explore and evaluate new data sources, tools, and capabilities, focusing on cutting-edge AI technologies to improve processes and strategies. - Collaborate closely with internal and external business partners to build, implement, track, and enhance decision strategies. Skills and Experience: - 5+ years of relevant experience in data science, machine learning, or a related field. - Advanced process management skills, organized and detail-oriented. - Curiosity about learning and developing new skill sets, particularly in the area of artificial intelligence. - Positive outlook with a can-do mindset. - Strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers. - Experience with statistical modeling techniques, including regression, classification, and clustering. - Experience building GenAI solutions using LLMs and vector databases. - Experience with agentic AI frameworks, such as Langchain, Langraph, MLOps. - Experience with data visualization tools such as Tableau or Power BI. - Other skills required include strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills. Education: - Bachelor's/University degree or equivalent experience in a quantitative field such as computer science, statistics, mathematics, or engineering. Master's degree preferred. Working at Citi offers more than just a job - it means joining a global family of dedicated individuals where you can grow your career, contribute to your community, and make a real impact.,

The Data Science Analyst is a developing professional role within GWFO team. This role applies specialized knowledge in machine learning, statistical modeling, and data analysis to monitor, assess, analyze, and evaluate processes and data. You will identify opportunities to leverage advanced analytics to improve business outcomes, automate processes, and generate actionable insights. Additionally, you will contribute to the development and deployment of innovative AI solutions, including generative AI and agentic AI applications. Working with cross-functional stakeholders, you will gather and process operational data to examine past business performance and identify areas for improvement. Utilizing machine learning techniques, you will identify data patterns and trends, providing insights to enhance business decision-making capabilities in various areas such as business planning, process improvement, and solution assessment. Your responsibilities will include developing and implementing machine learning models for predictive analytics, forecasting, and optimization. You will design, build, and deploy Generative AI solutions to enhance customer experience, automate tasks, and personalize interactions. Furthermore, you will experiment with agentic AI frameworks to create autonomous systems that can learn, adapt, and solve complex problems. Developing tools and techniques to evaluate the performance and impact of AI solutions will be part of your role. You will translate data into consumer or customer behavioral insights to drive targeting and segmentation strategies, communicating findings clearly and effectively to business partners and senior leaders. Continuous improvement is key, and you will explore and evaluate new data sources, tools, and capabilities with a focus on cutting-edge AI technologies. Collaboration with internal and external business partners in building, implementing, tracking, and improving decision strategies will be essential. As a successful candidate, you should ideally have 7+ years of relevant experience in data science, machine learning, or a related field. You should possess advanced process management skills, be organized and detail-oriented, and have a curious mindset for learning and developing new skill sets, particularly in artificial intelligence. Strong programming skills in Python and proficiency in relevant data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers are required. Experience with statistical modeling techniques, GenAI solutions, agentic AI frameworks, and data visualization tools like Tableau or Power BI is beneficial. Other essential skills include strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills. A Bachelors/University degree or equivalent experience is necessary for this role.,

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/TbiZ5o9oN2ZtJSpKA 5+ years of experience as a backend or full-stack developer, with strong focus on backend systems. Advanced proficiency in Python, including building scalable, production-grade applications. Hands-on experience integrating large language models (LLMs) using tools like LangChain, LangGraph, RAG pipelines, or similar frameworks. Proven track record of deploying LLM-based systems in real-world production environments (beyond just chatbots or academic projects). Good understanding of machine learning engineering concepts (preferred but not mandatory). Strong expertise in designing robust APIs and backend services, including async processing and microservices. Solid knowledge of deployment workflows, CI/CD, cloud infrastructure, observability, and performance optimization. *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply. Must possess strong communication skills , both written and verbal. Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

You will be responsible for leveraging GenAI models and frameworks to build applications and optimize AI solutions for clients. As the primary technical expert in GenAI technologies, you will focus on enhancing the GenAI footprint by developing and implementing advanced AI models. Your role will involve defining best practices, conducting workshops and demos, collaborating with cross-functional teams, and integrating emerging GenAI technologies for improving conversational AI capabilities. Additionally, you will provide technical leadership, mentorship, and guidance to teams, troubleshoot platform integration issues, and independently build prototypes to demonstrate to key decision-makers. To excel in this position, you should have at least 10 years of IT experience, with 3-4 years specifically in AI/Gen AI technologies such as OpenAI, Anthropic, or Hugging Face. Proficiency in NLP, NLU, NLQ, NLG technologies, and core Python expertise for building enterprise-scale applications are essential. You must have delivered production-grade projects on agentic AI frameworks, hands-on experience with frameworks like Autogen, Langraph, or Crew.AI, and expertise in NLQ to SQL-based GenAI applications using Python tools. Experience with cloud platforms like Microsoft Azure, AWS, or GCP, API integrations, and programming skills in Python, Node.js, or Java are also required. Moreover, you should possess strong problem-solving skills, solution architecture capabilities, and client-facing communication abilities to translate business requirements into technical solutions effectively. The ability to manage multiple projects in a fast-paced environment and experience working with cloud platforms will be beneficial. Additionally, expertise in building technical proposals, fast PoVs, and blueprints on new GenAI models and tools are desired for this role.,

The Spec Analytics Intmd Analyst role is a developing professional position where you will independently handle most problems and have the freedom to solve complex issues. You will utilize your in-depth specialty knowledge along with industry standards to integrate with the team and achieve sub-function/job family objectives. Your role will involve applying analytical thinking and data analysis tools to make judgments and recommendations based on factual information with attention to detail. You will be dealing with variable issues that could have broader business impacts and will have a direct influence on the core activities of the business through close contact. Your communication and diplomacy skills will be crucial to exchange potentially complex information effectively. Responsibilities: - Working with large and complex data sets to evaluate, recommend, and support business strategies - Identifying and compiling data sets using tools like SQL and Access to predict, improve, and measure business outcomes - Documenting data requirements, data collection, processing, cleaning, and exploratory data analysis - Specializing in marketing, risk, digital, and AML fields - Assessing risk in business decisions with consideration for the firm's reputation and compliance with laws and regulations Skills and Experience: As a successful candidate, you should ideally have: - 5+ years of experience in data science, machine learning, or related fields - Advanced process management skills, detail-oriented, and organized - Curiosity and willingness to learn new skill sets, particularly in artificial intelligence - Strong programming skills in Python and proficiency in data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers - Experience with statistical modeling techniques, data visualization tools, and GenAI solutions - Familiarity with agentic AI frameworks and MLOps Education: - Bachelors/University degree or equivalent experience This job description provides an overview of the work performed, and additional duties may be assigned as needed.,

The Data Science Analyst role at Citi, located in Gurgaon, is a developing professional position within the GWFO team. As a Data Science Analyst, you will utilize specialized knowledge in machine learning, statistical modeling, and data analysis to evaluate processes and data, identifying opportunities for leveraging advanced analytics to enhance business outcomes. You will play a key role in automating processes, generating actionable insights, and developing innovative AI solutions to contribute to the organization's success. Collaboration with cross-functional stakeholders is a fundamental aspect of this role. In this position, your responsibilities will include gathering and processing operational data from various stakeholders, applying machine learning techniques to identify data patterns and trends, developing and implementing machine learning models for predictive analytics, and designing Generative AI solutions to enhance customer experience. You will also experiment with agentic AI frameworks, develop tools to evaluate AI solutions" performance, and translate data into consumer insights to drive targeting and segmentation strategies. Effective communication of findings to business partners and senior leaders is essential for success in this role. The ideal candidate should possess 5+ years of relevant experience in data science or a related field, advanced process management skills, a curious mindset for learning new skill sets, and strong programming skills in Python. Proficiency in relevant data science libraries, experience with statistical modeling techniques, and familiarity with data visualization tools are required. Additionally, strong logical reasoning capabilities, willingness to learn new skills, and good communication and presentation skills are essential for this position. A Bachelor's/University degree or equivalent experience in a quantitative field is necessary, with a Master's degree being preferred. Working at Citi offers more than just a job it provides the opportunity to join a global family of dedicated individuals, grow your career, contribute to your community, and make a meaningful impact. If you require a reasonable accommodation due to a disability to access our search tools or apply for a career opportunity, please review the Accessibility at Citi information. For more details, you can refer to Citis EEO Policy Statement and the Know Your Rights poster.,

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/TbiZ5o9oN2ZtJSpKA 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

Role & responsibilities Must Haves Proven track record of project delivery for 1+ years Good coding (Preferably Python) skills and DSA Good problem solving and communication skills. Good Knowledge of Gen-AI technologies (LLM prompt engineering) Familiarity with React, HTML, CSS, JS or similar frameworks Familiarity with HTTP, REST, microservices, concurrency and Multithreading Willingness to work in a dynamic and fast paced environment. 4-6 years of experience with a Bachelor / Master's Degree in Computer Science or equivalent. Ownership and commitment towards work

* If you are 5+ years experienced and Immediate joiner , please apply: https://forms.gle/9n6GFcewkBo9VBNF8 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

* If you are 3+ years experienced and Immediate joiner , please apply: https://docs.google.com/forms/d/e/1FAIpQLScorR1zEgu9FvDHO-4gjJEOPhk_2tJE6cgftARiy9rwcVcDHg/viewform 3+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 3+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Timings: 8 hrs/day, Mon-Fri Preferred candidate profile : Immediate Joiners Fully remote, 3 months contract in the starting

Key Responsibilities: Agentic AI solution implementation leveraging Azure ecosystem, open-source RPA tools and scripting solutions where needed. Automation Solution Development : Create, deploy, and optimize automation workflows and BOTs using Agentic AI frameworks like Autogen. Leverage AI-driven processes to enable smart automation in business operations. Hands-on Cloud Integration : Design and implement automation solutions that integrate seamlessly with Microsoft Azure services (such as Azure Functions , Logic Apps , Azure Storage ) and other cloud-based tools to improve scalability and performance. AI and Python Libraries : Utilize Agentic AI frameworks for enhancing automation processes, and use Python libraries like Playwright for web automation, browser interaction, and testing. Implement machine learning models or AI algorithms where applicable to automate decision-making and data processing tasks. Scripting & Customization : Develop custom scripts in languages such as Python , PowerShell , JavaScript , and others to extend the functionality of RPA solutions, optimize workflows, and troubleshoot complex scenarios. Stakeholder Engagement : Collaborate with business analysts, IT teams, and key stakeholders to gather requirements, align automation goals with business priorities, and ensure automation solutions meet the desired business outcomes. Process Optimization : Continuously monitor, analyze, and optimize existing automation systems to enhance performance, reduce processing times, and ensure robustness. Identify opportunities to further automate manual processes across departments. Technical Leadership & Mentorship : Provide leadership, mentorship, and training to Agentic AI developers and junior engineers. Share best practices and foster a collaborative environment to ensure high standards of automation development.

Key Responsibilities: 1. Model Development and Deployment: Design, develop, and deploy generative AI models using cutting-edge techniques and frameworks. Utilize tools like LangChain, LangGraph, LangSmith to enhance model functionality and performance. Build models on complex RAG Architecture & should be able to incorporate AI security by design. 2. Agentic AI and Intelligent Systems: Develop and integrate intelligent agents and agentic AI systems to automate and optimize processes. Collaborate with cross-functional teams to implement agent-based solutions in various applications. 3. Research and Innovation: Stay updated with the latest advancements in AI and machine learning. Experiment with new algorithms and methodologies to improve existing models and systems. 4. Collaboration and Technical Leadership: Work closely with data scientists, software engineers, and product managers to ensure AI solutions meet business needs. Provide technical guidance and mentorship to junior team members. 5. Performance Optimization and Scalability: Optimize models for efficiency, scalability, and robustness in production environments. Monitor and evaluate system performance, implementing improvements as necessary. 6. Documentation and Knowledge Sharing: Document model architectures, processes, and key findings. Share insights and advancements with the team and stakeholders. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proven experience in developing and deploying generative AI models and machine learning systems. Proficiency in programming languages such as Python, with expertise in frameworks like TensorFlow, PyTorch, or Keras. In-depth knowledge of LangChain, Langraph, LangSmith, Agents, Agentic AI, and MCP. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes). Strong analytical and problem-solving skills. Excellent communication skills and ability to work collaboratively in a tea Mandatory Skills: Generative AI.Experience3-5 Years.