10 Lang Graph Jobs

Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What we're looking for Bachelor's/Master’s degree in computer science, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). Experience with LLM-specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Role Description Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation.

Gainwell Technologies LLC Summary Gainwell Technologies is seeking a highly skilled AI Engineer to design, develop, and deploy advanced AI and Generative AI (Gen AI) solutions, across our healthcare technology platforms. This role involves building and optimizing AI / GEN AI technologies, integrating them into existing systems, and ensuring their effectiveness in improving healthcare outcomes and operational efficiency while maintaining compliance with industry standards. Your role in our mission AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js What we're looking for Master’s or Ph.D in Computer Science, AI, Data Science, or a related field. 4+ years of experience in AI/ML engineering, with a focus on developing and deploying AI solutions. Hands-on expertise in machine learning, deep learning, Gen AI ( multi modal LLMs), NLP, and computer vision. Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. Experience developing, deploying and finetuning LLMs (GPT, Gemini, Claude or similar) for real world applications including prompt engineering, model optimization and inference efficiency. Experience with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments. Proficiency in working with big data technologies (Spark, Hadoop, SQL, NoSQL databases). Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Performance Optimization – Continuously monitor, refine, and optimize AI / GEN AI models for accuracy, efficiency, and speed, leveraging ML Ops and LLM Ops best practices. AI Research & Innovation – Stay updated with the latest AI/ML/ GEN AI advancements, exploring new technologies and methodologies to enhance solution effectiveness. Compliance & Security – Ensure AI implementations adhere to healthcare industry regulations, ethical AI principles, and data privacy standards. Automation & Workflow Enhancement – Identify opportunities to automate workflows and optimize business processes using AI-driven solutions. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js

Role & responsibilities Machine Learning, Data Science, Model Customization [4+ Years] Exp with performing above on cloud services e.g AWS SageMaker and other tools AI/ Gen AI skills: [1 or 2 years] MCP, RAG pipelines, A2A, Agentic / AI Agents Framework Auto Gen, Lang graph, Lang chain, codeless workflow builders etc. Preferred candidate profile Build working POC and prototypes rapidly. Build / integrate AI driven solutions to solve the identified opportunities, challenges. Lead cross functional teams in identifying and prioritizing key business areas in which AI solutions can result benefits. Proposals to executives and business leaders on broad range of technology, strategy and standard, governance for AI. Work on functional design, process design (flow mapping), prototyping, testing, defining support model in collaboration with Engineering and business leaders. Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation. Relevant IT Experience: - 10+ years of relevant IT experience in given technology

Design and develop high-quality software using Core Java and Python. Collaborate with cross-functional teams to define, design, and ship new features. Design and implement RESTful APIs and microservices. Experience with CI/CD pipelines and tools. Minimum 5 yrs of experience in Java/Python development. Knowledge of Agentic frameworks like Lang graph is added advantage.

Role & responsibilities Role Overview We are seeking a Senior Associate Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 6 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI , including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Good to Have Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Soft Skills & Team Expectations Strong written and verbal communication; able to explain complex models to business stakeholders. Ability to independently document work, manage requirements, and self-drive technical discovery. Desire to innovate, improve, and automate existing processes and solutions. Active contributor to team knowledge sharing, technical forums, and innovation drives. Strong interpersonal skills to build relationships across cross-functional teams. A mindset of continuous learning and technical curiosity. Preferred Certifications (at least two are preferred) Certifications in Machine Learning, Deep Learning, or Natural Language Processing. Python programming certifications (e.g., PCEP/PCAP). Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc. Why Join PwC CTIO? Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges. Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development. Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains. Operate in a startup-like environment within the safety and structure of a global enterprise. Accelerate your career as a deep tech leader in an AI-first future. Shift:11am-8pm

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 Position (Title): Agentic AI Experience Required: 3 - 9 Years No of Position: 4 Job Type: FTE Location: Hyderabad Required Skills 3 to 7 years of hands-on experience in AI/ML, with at least 12 years specifically in Agentic AI or autonomous agents. Strong proficiency in Python and familiarity with AI libraries such as Hugging Face Transformers, LangChain, and OpenAI APIs. Experience with tools like AutoGen , CrewAI , and LangGraph . Deep understanding of RAG pipelines , LLM fine-tuning , and embedding-based retrieval systems . Hands-on experience with vector databases like FAISS, Pinecone, or similar. Solid foundation in machine learning, NLP, and data structures. Excellent communication skills and ability to work in a collaborative environment Role and Responsibilities Design, build, and deploy intelligent autonomous agents using Agentic AI frameworks like AutoGen , CrewAI , and LangGraph . Implement RAG (Retrieval-Augmented Generation) pipelines to enhance response accuracy and contextual relevance. Work with vector databases (e.g., FAISS, Pinecone, Weaviate) for knowledge storage and semantic search. Fine-tune large language models (LLMs) for specific tasks using tools like LoRA, PEFT, or full model training. Collaborate with product, research, and engineering teams to understand user needs and create agent-based workflows. Integrate APIs and services to create complex multi-agent systems capable of task delegation and coordination. Continuously evaluate and improve system performance, scalability, and reliability. Preferred Qualifications Prior experience deploying LLM-based agents in production. Knowledge of prompt engineering and agent orchestration. Contributions to open-source AI/agent frameworks.

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.

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

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649