7 Langraph Jobs

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.

Position Summary: As a member of Redaptive's AI team, you will be driving Agentic AI and Generative AI integration across all of Redaptives business units. You will drive AI development and integration across the organization, directly impacting Redaptives global sustainability efforts and shaping how we leverage AI to serve Fortune 500 clients. Responsibilities and Duties: Strategic Leadership (10%): Champion the AI/ML roadmap, driving strategic planning and execution for all initiatives. Provide guidance on data science projects (Agentic AI, Generative AI, and Machine Learning), aligning them with business objectives and best practices. Foster a data-driven culture, advocating for AI-powered solutions to business challenges and efficiency improvements. Collaborate with product management, engineering, and business stakeholders to identify opportunities and deliver impactful solutions Technical Leadership (40%): Architect and develop Proof-of-Concept (POC) solutions for Agentic AI, Generative AI, and ML. Utilize Python and relevant data science libraries, leveraging MLflow. Provide technical guidance on AI projects, ensuring alignment with business objectives and best practices. Assist in developmentand documentation of standards for ethical and regulatory-compliant AI usage. Stay current with AI advancements, contributing to the team's knowledge and expertise. Perform hands-on data wrangling and AI model development Operational Leadership (50%): Drive continuous improvement through Agentic AI, Generative AI, and predictive modeling. Participate in Agile development processes (Scrum and Kanban). Ensure compliance with regulatory and ethical AI standards. Other duties as assigned Required Abilities and Skills: Agentic AI development and deployment. Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Working with large datasets on AWS and Databricks Strong hands-on experience with: Agentic AI development and deployment. Working with large datasets on AWS and Databricks. Desired Experience: Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Experience integrating AI with IoT/event data. Experience with real-time and batch inference integration with SaaS applications. International team management experience. Track record of successful product launches in regulated environments Education and Experience: 5+ years of data science/AI experience Bachelor's degree in Statistics, Data Science, Computer Engineering, Mathematics, or a related field (Master's preferred). Proven track record of deploying successful Agentic AI, Generative AI, and ML projects from concept to production. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences.

Job Description & Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

We are seeking a proficient AI/ML Engineer responsible for testing, deploying, and hosting various Large Language Models (LLMs). The role involves monitoring deployed agentic services, ensuring their optimal performance, and staying abreast of the latest advancements in AI technologies. Key Responsibilities: LLM Deployment & Hosting Evaluate, test, and deploy diverse LLMs on cloud-based and on-premise infrastructures. Optimize model performance for scalability and efficiency. Implement secure API endpoints and model-serving pipelines. Strong CI/CD skills and knowledge of CI/CD tools like Jenkins, GitHub Actions, CircleCI etc. Agentic AI Services Deploy and maintain AI agents using frameworks such as CrewAI, Agnos(Phi Data), AutoGen etc. Integrate LLMs into business workflows and automation tools. Design, monitor, and enhance agentic services for real-world applications. Monitoring & Optimization Utilize advanced observability tools to monitor model performance, latency, and cost efficiency. Implement tools like AgentOps, OpenLIT, Langfuse, and Langtrace for comprehensive monitoring and debugging of LLM applications. Develop logging, tracing, and alerting systems for deployed models and AI agents. Conduct A/B testing and gather user feedback to refine AI behavior. Address model drift and retrain models as necessary. Best Practices & Research Stay updated with the latest advancements in AI, LLMs, and agentic systems. Implement best practices for prompt engineering, reinforcement learning from human feedback (RLHF), and fine-tuning methodologies. Optimize compute costs and infrastructure usage for AI applications. Collaborate with researchers and ML engineers to integrate state-of-the-art AI techniques. Strong knowledge on version control tools like GitHub Qualifications & Skills: Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, or Meta AI models. Strong programming skills in Python and experience with deep learning libraries (PyTorch, TensorFlow, JAX). Experience with cloud platforms (AWS, Azure, GCP) and model deployment tools (Docker, Kubernetes, FastAPI, Ray Serve). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG) techniques. Hands-on experience with monitoring tools such as AgentOps, OpenLIT, Langfuse, and Langtrace. Understanding of prompt engineering, LLM fine-tuning, and agent-based automation. Excellent problem-solving skills and the ability to work in a dynamic AI research and deployment team. Preferred Qualifications: Experience in reinforcement learning, fine-tuning LLMs, or training custom models. Knowledge of security best practices for AI applications. Contributions to open-source AI/ML projects or research publications in the field.

As a Engineer, you will be joining a team transforming healthcare and improving the lives and vitality of the millions of members we serve. We leverage cutting edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop solutions for automated document processing and customer service chat bots. We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a background in backend engineering or data engineering with a strong foundation in Python and system integrations. The candidate should have hands-on experience in developing applications with advanced Python concepts, as well as expertise in integrating systems both in cloud and on-prem environments. You will be instrumental in building scalable, robust systems while integrating AI-based capabilities into our solutions. Key Responsibilities: Develop and maintain backend applications using Python, ensuring high performance and scalability. Implement advanced Python concepts such as Gang of Four patterns, asynchronous programming, and decorators to optimize application efficiency. Build and maintain APIs using frameworks like FastAPI and Django. Use Pydantic for data validation and modeling. Integrate various systems, including databases and APIs, both within cloud environments and on-premises systems. Handle transaction management, failure handling, validation, and retries to ensure reliability and fault tolerance. Work with cloud services, preferably AWS, for building and deploying scalable systems. Collaborate with cross-functional teams to integrate AI features into applications. Work with tools like Langchain, Langraph, and Agentic (experience is a plus) to enhance AI capabilities. Desired Qualifications: 11 to 13 years of application development experience with a focus on backend engineering or data engineering and transitioned into AI. Atleast 3+ years of Hands-on experience with Python frameworks such as FastAPI, Django, and Pydantic. Strong proficiency in Python and experience with advanced programming concepts. Experience in system integration across cloud and on-premises platforms. Familiarity with transaction management, failure handling, validation, and retries. Experience with cloud platforms, particularly AWS. Knowledge of AI tools and libraries (Langchain, Langraph, Agentic) is a plus. Solid understanding of backend application development principles and best practices. Strong problem-solving skills and the ability to adapt to new challenges in a fast-paced environment. Education and Training Required: Degree in Computer Science, Artificial Intelligence, or a related field.

We are looking for an experienced and proactive Technical Product Owner (System Analyst) to join our AI-focused team. As a key liaison between the onshore Product Owner and the offshore development and QA team, you will be responsible for owning the product roadmap, defining technical requirements, and driving the implementation of backend and AI initiatives. This role is ideal for someone with strong technical expertise, exceptional communication skills, and a passion for delivering high-quality products in collaboration with cross-functional teams. Key Responsibilities: Collaborate with the onshore Product Owner to translate business objectives into detailed technical requirements and actionable tasks. Own the product roadmap and backlog, ensuring alignment with business priorities and team capacity. Act as the primary point of contact for the offshore development and QA team, ensuring clear communication of requirements, priorities, and timelines. Work closely with developers and QA engineers to design, validate, and deliver high-quality AI-integrated backend systems and workflows. Define acceptance criteria and review deliverables to ensure they meet functional, technical, and business requirements. Facilitate sprint planning, daily stand-ups, retrospectives, and other Agile ceremonies for the offshore team. Drive the adoption of best practices for backend development, system integration, and AI implementation. Monitor and report on the progress of initiatives, identifying risks and ensuring timely resolution of blockers. Maintain a strong understanding of the technical stack, including Python-based backend systems, APIs, and cloud services (preferably AWS). Advocate for continuous improvement in processes, tools, and team collaboration. Qualifications: 8 to 11 years of experience as a Technical Product Owner, System Analyst, or similar role in a technology-focused environment. Strong technical background, with experience in backend systems, APIs, and cloud platforms. Excellent understanding of Agile methodologies and experience working in Agile teams. Proven ability to write clear and concise user stories, technical requirements, and acceptance criteria. Hands-on experience collaborating with development and QA teams, especially in offshore/onsite models. Knowledge of Python, system integrations, and cloud services like AWS is a significant advantage. Exposure to AI tools and workflows (e.g., Langchain, Langraph, Agentic) is a plus. Exceptional communication and leadership skills, with the ability to influence and motivate cross-functional teams. Strong problem-solving and analytical skills, with a focus on delivering high-quality solutions. What We Are Looking For: A proactive leader capable of owning the product and driving initiatives from concept to delivery. A collaborative team player who can bridge the gap between business stakeholders and technical teams. Someone with a passion for technology, particularly AI, and a desire to continuously improve products and processes. Education and Training Required: Degree in Computer Science, Artificial Intelligence, or a related field.

JD for Gen AI Developer About V Group V Group Inc., an IT-based solution entity based out of New Jersey. With multiple offshore sites (Pune and Bhopal) in India. With offerings ranging from IT infrastructure to Product development, V Group Inc provides a compliant service in numerous industry sectors while maintaining structure, stability, and core values. Ranked by INC5000 in 2020 - Fastest Growing IT Co. in the USA. Current business groups include e-commerce, Digital, Professional services, IT projects, and Products. Join our team of innovative technical and business-savvy people; with a passion for creating solutions! Visit us at: https://www.vgroupinc.com (Corporate website) || https://www.webstorevgroup.net (Ecommerce Store) || https://www.vgroupdigital.com/portfolio (Digital Products). Job Details: Position Title : Gen AI Developer Job Locatio n: Bengaluru (Bellandur Hybrid) Experience : 5+ years Roles And Responsibilities: Design, develop, and optimize generative AI models using AWS Bedrock. Collaborate with cross-functional teams to understand project requirements and deliver AI-driven solutions. Conduct research and stay up-to-date with the latest advancements in generative AI and machine learning. Implement and maintain AI-centric libraries and frameworks such as langchain, langraph etc Perform data pre-processing, augmentation, and generation of synthetic data to enhance model performance. Evaluate and fine-tune AI models to ensure high-quality, creative content generation. Utilize AWS Bedrock to experiment with and evaluate top foundation models, customize them with your data, and build agents that execute tasks using your enterprise systems and data sources. Document and present findings, methodologies, and results to stakeholders. Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI model performance and accuracy. Perks & Benefits Health & Accident Insurance Paid Leaves and Sick Leaves Education sponsorship / Certification Reimbursement Free Training Platforms Internet Reimbursement Gym membership EPF, Gratuity.