209 Langchain Jobs - Page 8

Role & responsibilities Required a candidate with who has worked on GenAI, microservice, FastAPI , Langchain and Promt Engineering Preferred candidate profile Data Scientist, AI/ML Engineer Perks and benefits Hybrid Mode

Develop and optimize AI models for business-specific use cases. Perform data analysis, feature engineering, and model training. Implement and fine-tune NLP and machine learning algorithms. Evaluate model performance and ensure continuous improvements. Work with engineers to deploy models in production environments.

Role & responsibilities : Gen AI Developer Preferred candidate profile :- 3+ Years Location: Hyderabad Job Overview: Design, implement, and deploy Generative AI models (e.g., GPT, GAN) using Python. Hands-on knowledge in Langchain and other Genai tools to develop prompt. Develop and optimize machine learning and deep learning algorithms for generative tasks such as text generation, image creation, video synthesis, etc. Work closely with data engineers, and other teams to integrate AI solutions into production systems. Preprocess and analyze large datasets to train AI models. Tune and optimize model performance and ensure scalability of the deployed solutions. knowledge in OCR and other machine learning skills Perks and benefits :- Long term development project, Location:- Hyderabad - Work from office

The Team: Join our innovative and collaborative team at S&P Global's IT - Enterprise Technology department. We pride ourselves on fostering a culture that values excellence, teamwork, and continuous learning. Our team is dedicated to pushing the boundaries of AI technology and delivering impactful solutions that drive business success. Job Description: We are seeking a motivated and talented Senior Data Scientist to join our team and assist with GenAI projects. This is an excellent opportunity for someone looking to gain hands-on experience in cutting-edge AI technologies and cloud solutions. Responsibilities and Impact: Assist in the development and implementation of GenAI projects, contributing to the advancement of AI capabilities within the organization. Write clean, efficient, and maintainable code in Python to support various AI initiatives. Collaborate with the team to design and implement cloud-based solutions. Deploy and manage code using GIT, ensuring seamless integration and version control. Participate in code reviews and contribute to improving coding standards, fostering a culture of excellence. Troubleshoot and debug issues related to code and cloud infrastructure, ensuring system reliability. Document processes, code changes, and project updates to facilitate knowledge sharing and transparency. What Were Looking For: Basic Required Qualifications: Bachelors degree in Computer Science, Engineering, or a related field, or equivalent work experience. Minimum 5 to 8 years of experience in data science roles. Strong programming skills in Python. Knowledge and working understanding of ML algorithms and NLP. Advanced knowledge of various services in a Cloud platform, preferably AWS. Experience with version control systems, particularly GIT. Completed projects using open/closed source Gen AI models. Excellent problem-solving skills and attention to detail. Strong communication and teamwork skills. Additional Preferred Qualifications: Experience with AI frameworks such as Langchain, LamaIndex Knowledge of containerization technologies like Docker. Understanding of CI/CD pipelines and DevOps practices.

Job Description: Required Qualifications 5+ years of professional experience in AI/ML development/ Data scientist Strong programming skills in Python and related ML frameworks Proven track record of delivering production ready AI solutions Effective communication with client Technical Skills & Experience Overview Proficiency in Python, TensorFlow, PyTorch, Hugging Face, LangChain. Experience with APIs development and integration using Flask, FastAPI, or similar frameworks. Familiarity with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for AI applications. Experience with SQL & NoSQL databases (PostgreSQL, MongoDB, etc.). Strong knowledge of Cloud services (AWS, Azure, GCP) for AI deployment. Understanding of MLOps and CI/CD pipelines for model lifecycle management. Machine Learning & Deep Learning Strong foundation in traditional ML algorithms and statistical modeling Experience with neural network architectures and deep learning frameworks (PyTorch/TensorFlow) Practical knowledge of model optimization, hyperparameter tuning, and performance metrics Expertise in data preprocessing, feature engineering, and model validation techniques Large Language Models (LLMs) Experience working with transformer-based architectures Hands-on experience with LLM deployment and fine-tuning Understanding of prompt engineering and LLM evaluation metrics Knowledge of RAG (Retrieval-Augmented Generation) systems and vector databases AI Agents & Automation Experience in developing autonomous AI agents and workflows Understanding of agentic approaches to AI system design Knowledge of reinforcement learning and decision-making systems Experience with AI orchestration and multi-agent systems Computer Vision (Good to have) Practical experience with image processing and computer vision algorithms Knowledge of CNN architectures and modern vision transformers Experience with object detection, segmentation, and classification tasks Understanding of video processing and real-time vision systems Infrastructure & Deployment Strong experience with cloud platforms (AWS/Azure/GCP) Expertise in API development and RESTful services Knowledge of containerization and orchestration (Docker, Kubernetes) Experience with ML ops and model serving infrastructure Key Responsibilities Design and implement end-to-end AI solutions from concept to production Develop and optimize ML models for various use cases Create and maintain RAG systems for information retrieval and generation Build and deploy computer vision solutions for real-world applications Implement and manage cloud-based AI services and APIs Collaborate with cross functional teams to integrate AI solutions Mentor junior team members and contribute to technical decision making

Location: Bangalore / Hybrid Department: Data & AI Company: Resolve Tech Solutions / Juno Labs About Juno Labs: Juno Labs is at the forefront of AI-driven cloud solutions, helping businesses unlock the power of data with scalable, intelligent, and high-performance architectures. We specialize in building next-gen data platforms, leveraging cloud technologies, AI/ML, vector databases, and advanced frameworks to drive real-time insights and intelligent decision-making. Job Description: We are looking for an experienced MLOps Engineer to join our Data & AI team. This role will focus on building, deploying, and optimizing end-to-end machine learning systems with an emphasis on LLMOps (Large Language Models operationalization). The ideal candidate will have strong expertise in MLOps , LLMOps , and DevOps , with hands-on experience managing and deploying large-scale models, particularly LLMs , in both cloud and on-premise environments. The role involves not only building robust MLOps pipelines but also self-hosting models, optimizing GPU usage, and performing quantization to reduce the cost of deployment. Key Responsibilities: Design and implement scalable MLOps pipelines to deploy, monitor, and manage machine learning models, with a particular focus on LLMOps . Integrate, fine-tune, and optimize Hugging Face models (e.g., Transformers , BART , GPT-2/3 ) for diverse NLP tasks such as text generation , text classification , and NER , and deploy them for production-scale systems. Use LangChain to build sophisticated LLM-driven applications , enabling seamless model workflows for NLP and decision-making tasks. Optimize and manage LLMOps pipelines for large-scale models using technologies such as OpenAI API , Amazon Bedrock , DeepSpeed , and Hugging Face Hub . Develop and scale self-hosted LLM solutions (e.g., fine-tuning and serving models on-premises or in a hybrid cloud environment) to meet performance, reliability, and cost-effectiveness goals. Leverage cloud-native tools such as Amazon SageMaker , Vertex AI , GCP , AWS for scaling large language models, and ensure their optimization in distributed cloud environments. Use GPU-based optimization for large-scale model training and deployment, ensuring high performance and efficient resource allocation in the cloud or on- premises environments. Deploy models via containerized solutions using Docker , Kubernetes , and Helm , allowing for seamless scaling and management in both cloud and on- premise infrastructures. Implement model quantization and pruning techniques to reduce the resource footprint of deployed models while maintaining high performance. Monitor model performance in production using Prometheus , Grafana , ELK Stack , and other observability tools to track metrics such as inference latency, accuracy, and throughput. Automate the end-to-end workflow of model development and deployment via CI/CD pipelines with tools like GitLab CI , Jenkins , and CircleCI . Integrate vector databases (e.g., Pinecone , FAISS , Milvus ) for efficient storage, retrieval, and querying of model-generated embeddings. Stay up to date with the latest advancements in MLOps , LLMOps , and machine learning technologies, ensuring the adoption of best practices in model development, deployment, and optimization. Required Skills & Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or a related field. 5+ years of experience in MLOps , LLMOps , DevOps , or related roles, with a focus on deploying and managing machine learning models in production environments. Experience with cloud platforms such as AWS , GCP , Azure , and services like Amazon SageMaker , Vertex AI , TensorFlow Serving , DeepSpeed , and Amazon Bedrock . Expertise in Hugging Face models and the Transformers library, including model fine-tuning , deployment , and optimizing NLP models for large-scale production. Experience with LangChain for building and deploying LLM-based applications that handle dynamic and real-time tasks. Strong experience with self-hosting LLMs in cloud or on-premises environments using GPU-based infrastructure for training and inference (e.g., NVIDIA GPUs , CUDA ). Expertise in GPU utilization and optimization for large-scale model training, inference, and cost-effective deployment. Hands-on experience in model quantization techniques to reduce the memory footprint and inference time, such as TensorFlow Lite , ONNX , or DeepSpeed . Familiarity with distributed ML frameworks like Kubeflow , Ray , Dask , MLflow , for managing end-to-end ML workflows and large-scale model training and evaluation. Proficiency with containerization and orchestration tools such as Kubernetes , Docker , Helm , and Terraform for infrastructure automation. Knowledge of vector databases like Pinecone , Milvus , or FAISS to facilitate fast and scalable retrieval of model-generated embeddings. Expertise in setting up and managing CI/CD pipelines for model training, validation, testing, and deployment with tools like Jenkins , GitLab CI , and CircleCI . Strong programming skills in Python , Bash , and Shell scripting . Solid understanding of monitoring and logging tools such as Prometheus , Grafana , and ELK Stack to ensure high system performance, error detection, and model health tracking. Preferred Qualifications: Proven experience in deploying and managing large-scale LLMs like GPT-3 , BERT , T5 , and BLOOM in production environments using cloud-native solutions and on-premises hosting. Deep expertise in quantization , model compression , and pruning to optimize deployed models for lower latency and reduced resource consumption. Strong understanding of NLP tasks and deep learning concepts such as transformers, attention mechanisms, and pretrained model fine-tuning. Experience with Kedro for building reproducible ML pipelines with a focus on data engineering, workflow orchestration, and modularity. Familiarity with Apache Spark and Hadoop for handling big data processing needs, especially in real-time AI workloads . Familiarity with advanced data engineering pipelines and data lakes for the effective management of large datasets required for training LLMs. Why Join Us: Work with cutting-edge technologies in AI , MLOps , and LLMOps , including self- hosting and optimizing large-scale language models. Be part of an innovative, fast-growing team working on the future of AI-driven cloud solutions. Flexibility in work style with a hybrid work environment that promotes work-life balance. Competitive salary and benefits package, with opportunities for personal and professional growth.

Job Summary: As a Data Expert at SS&C, you will play a key role in the Data Platform, shaping hedge fund administration technology, streamlining daily workflows, and enhancing reporting for fund accountants, investment managers, clients, and investors. Youll be part of a dedicated and passionate team driven by intellectual curiosity, problem-solving, and a commitment to delivering impactful solutions. We seek capable leaders eager to learn new technologies, embrace best practices, and foster a collaborative, fun work environment. Join us to grow and learn while practicing continuous integration and delivery, leveraging the agile methodology, and building high-quality, valuable features using a test-driven approach. Job Title: Lead Software Engineer Key Responsibilities: Lead the development of robust, high-performance web and generative AI applications. Architect, design, and implement scalable and secure solutions aligned with business objectives. Mentor and guide a team of developers, fostering a culture of continuous learning and improvement. Design and maintain APIs, including RESTful and GraphQL interfaces, ensuring seamless data exchange with third-party services. Implement and maintain CI/CD pipelines, utilizing automation tools for seamless deployment. Collaborate with cross-functional teams, including DevOps, Security, Data Science, and Product Management. Optimize application performance through efficient resource management, load balancing, and query optimization. Ensure compliance with industry security standards such as GDPR. Stay updated with emerging technologies, especially in Generative AI, Machine Learning, cloud computing, and microservices architecture. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 6+ years of hands-on experience in Python development, with expertise in Django, Flask, or FastAPI. Ability to design and build end-to-end applications and API integrations Proven experience with large language models (LLMs) and AI model development Experience with developing retrieval-augmented generation (RAG). Experience with GenAI tools like Langchain, LlamaIndex, and open-source Vector DBs. Exposure to prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Experience with relational databases such as MS SQL Server, PostgreSQL, and MySQL. Expertise in DevOps practices, including Docker, Kubernetes, and CI/CD tools like GitHub Actions. Deep understanding of microservices architecture and distributed computing principles. Strong knowledge of security best practices in software development. Familiarity with data analytics and visualization tools such as Snowflake, Looker, Tableau, or Power BI. Excellent problem-solving skills and the ability to work independently and within a team. Strong communication and stakeholder management skills. Location: Hyderabad (Hybrid Work Model)

Senior Python Software Engineer Proficient in Python 5 years hands-on familiar with PEP standards linters ruff pylint package managers poetry uv 1 year of SQL General knowledge on databases and storage layers 3 years experience with AWS Dynamo RDS S3 Kinesis EventBridge SNS SQS Fargate Lambda Experience building and deploying applications on AWS Knowledge of AWS infrastructure and services 5 years experience with object oriented programming test driven development 5 years experience with unit integration and regression testing Experience with CICD tools such as Github Actions AzDO pipelines Experience writing Python Rest APIs FastAPI Flask Django Experience working in a team be able to read other peoples code Git at a sufficient level be able to contribute to a team repo resolve merge conflicts Docker Level of English sufficient to work in an international team B1 Soft Skills Required Ability to communicate at a high level Proactive self motivated Able to move projects forward quickly Ability to quickly learn and utilize new technologies Nice to have Golang Langchain or any other AIAgentic framework Airflow or any other orchestration tool Dagster Luigi Prefect Azure Cloud esp its AI suite AI orchestration frameworks like LangChain LangGraph MLFlow or any other model versioning tool Data science background familiarity with DS workflows problems models evaluation patterns etc Data processing frameworks PySpark Dask Ray Pandas Polars DuckDB not all of them Javascript writing github actions and frontend frameworks React Vue Sveltehtmx

Job Overview: As a Team Lead, you will play a pivotal role in guiding a talented group of developers in building and maintaining high-quality web applications. The ideal candidate will have a solid foundation in Python and Django, coupled with proven experience in team management and project delivery. This role requires a proactive approach to problem-solving and the ability to balance technical tasks with leadership responsibilities. Key Responsibilities: Lead and Mentor: Guide a team of Python & Django developers, providing mentorship, training, and technical guidance to foster professional growth and skill development. Project Oversight: Plan, organize, and oversee project tasks from concept through deployment, ensuring timely and high-quality delivery. Code Quality: Establish and enforce best practices in coding standards, testing, and version control to maintain a high standard of code quality and reliability. Collaboration: Work closely with cross-functional teams, including design, QA, and product management, to define project requirements and design solutions that align with business goals. Problem Solving: Troubleshoot and resolve complex technical issues in real-time, maintaining efficiency and minimizing downtime. Code Review: Conduct regular code reviews to ensure code quality, scalability, and performance. Project Planning: Participate in project estimation and resource planning, balancing scope with project timelines and quality standards. Technology Trends: Stay updated with emerging technologies, tools, and industry trends to introduce best practices and innovative solutions. Required Technical Skills: Python & Django Expertise: 4-6 years of hands-on experience in Python and Django, with a proven track record of delivering high-quality web applications. Web Technologies: Familiarity with front-end technologies such as JavaScript, HTML5, and CSS3 is beneficial. API Integration: Strong understanding of RESTful API design, development, and integration. Database Management: Proficiency in ORM (Object Relational Mapping) and relational databases such as MySQL, PostgreSQL, etc. Version Control: Proficient in Git and collaborative version control workflows. Cloud Exposure: Knowledge of cloud services (AWS, Azure, or GCP) is an advantage, with the ability to deploy and manage applications in cloud environments. Software Design Principles: Solid grasp of software architecture, design principles, and best practices for scalable applications. Leadership & Interpersonal Skills: Team Management: Proven experience in leading, managing, and motivating a development team. Communication Skills: Excellent communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders. Multitasking: Ability to handle multiple tasks and projects simultaneously, prioritizing effectively to meet deadlines. Mentorship: Willingness and capability to mentor junior team members, encouraging growth and development within the team. What We Offer: Competitive Salary: Competitive CTC within the range of 15-20 LPA, based on experience and skill set. Career Growth: Opportunities for personal and professional development, including training, certifications, and growth into higher leadership roles. Innovation-Driven Culture: Work in a collaborative environment that encourages innovation, experimentation, and creativity. Dynamic Team: Join a team that values knowledge-sharing, open communication, and collaborative problem-solving. Convenient Location: Based in Hyderabad, with access to all the amenities and vibrant tech community the city offers.

Job Details: Experience - 6 to 12 yrs Mandatory Skills - Machine Learning & NLP, RAG & Text-to-SQL Azure Cloud. Model Optimization & Fine-Tuning, Python (LangChain, LlamaIndex), Data Analytics & SQL Location - Mumbai, Pune, Bangalore, Chennai, Hyderabad and Kolkata location. Notice - Immediate to 30 days Job Summary: Develop and optimize AI models for business-specific use cases. Perform data analysis, feature engineering, and model training. Implement and fine-tune NLP and machine learning algorithms. Evaluate model performance and ensure continuous improvements. Work with engineers to deploy models in production environments.

Roles & Responsibilities: Designing, developing, testing, and implementing ML models. This involves understanding business objectives and requirements in collaboration with the AI team and developing solutions to solve complex problems. Analysing and interpreting complex data to identify trends, patterns, and insights. This role requires staying updated with the latest AI/ML trends, techniques, and technologies, and conducting research to implement new methodologies in AI and ML. Collaborate closely with business stakeholders and other cross-functional teams to define and prioritize AI-driven product features and capabilities based on their requirements. Ensure the scalability, reliability, and performance of the integrated GenAI solutions, optimizing software architecture and implementing best practices. Continuously monitor and evaluate the performance of AI models and processes, identifying areas for improvement and implementing necessary enhancements to ensure optimal results. Stay up-to-date with the latest advancements in GenAI, analytics, and Prompt Engineering, ensuring remains at the forefront of innovation and maintains a competitive. Participate in regular reviews and audits of AI-driven processes, providing insights and recommendations for improvements to ensure ongoing alignment with strategic goals and regulatory requirements. Ensure adherence to data privacy and security standards, safeguarding sensitive customer and business information while maintaining compliance with relevant regulations. Demonstrate the ability to work independently and take ownership of tasks, while also supporting junior team members, ensuring timely high-quality delivery. Our Customers / Stakeholders: Investment Banking Senior Management & Front-office staff, Investment Banking Transformation Leads, Investment Banking Technology Management Teams. Qualifications To be successful in this role, you should meet the following requirements: Highly numerate with strong background in mathematical disciplines e.g., computer science (AI/ML), statistics, physics, engineering. Proven experience of working with GenAI, Large Language Models (LLM), Natural Language Processing (NLP) techniques, Time-Series and Prediction Models and familiarity with TensorFlow, LangChain, PyTorch, Plotly, Dash, Scikit-learn libraries. Track record of implementing AI/ML Statistics models and GenAI solutions in strictly regulated financial organizations. Strong proficiency in software development with expertise in backend technologies, frontend frameworks, and languages, such as Python, JavaScript. Good proficiency in Database technology is recommended. Familiarity with financial data and good understanding of investment banking products and processes. Excellent communication and collaboration skills to effectively work with cross-functional teams and stakeholders. Result oriented team player who can foster strong and collaborative partnerships with key stakeholders. Location: Pune Exp: 12+ Yrs

About the Role: We are looking for an experienced AI/ML Engineer with a strong background in Generative AI (GenAI), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) implementation . You will play a key role in designing, developing, and deploying cutting-edge AI solutions that leverage state-of-the-art machine learning techniques to solve complex problems. Key Responsibilities: Design, develop, and optimize LLM-based applications with a focus on RAG pipelines, fine-tuning, and model deployment . Implement GenAI solutions for text generation, summarization, code generation, and other NLP tasks. Develop and optimize ML models , leveraging classical and deep learning techniques. Build and integrate retrieval systems using vector databases like FAISS, ChromaDB, Pinecone, or Weaviate . Optimize and fine-tune LLMs (e.g., OpenAI GPT, LLaMA, Mistral, Falcon ) for domain-specific use cases. Develop data pipelines for training, validation, and inference. Work on scalable AI solutions , ensuring performance and cost efficiency in deployment. Collaborate with cross-functional teams to integrate AI models into production applications. Required Skills & Qualifications: 3+ years of experience in AI/ML development. Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Hugging Face Transformers . Hands-on experience with LLMs, GenAI, and RAG architectures . Experience working with vector databases (e.g., FAISS, Pinecone, ChromaDB). Knowledge of ML algorithms , deep learning architectures, and NLP techniques. Familiarity with cloud platforms ( AWS, GCP, or Azure ) and AI/ML model deployment. Experience with LangChain or LlamaIndex for LLM applications is a plus. Strong problem-solving skills and the ability to work in a fast-paced environment. Nice-to-Have Skills: Experience with multi-modal AI models (text, image, video). Knowledge of MLOps tools (Kubeflow, MLflow, or Vertex AI). Familiarity with prompt engineering and fine-tuning strategies . Why Join Us? Work on cutting-edge AI projects in an innovative and collaborative environment. Opportunities for career growth and learning in the fast-evolving AI space. Competitive compensation, flexible work options, and great team culture.

Full stack Developer with AI (AM) BLR / GGN / Noida J48771 Job Description- Fullstack Developers with GenAI experience in Azure or GCP ecosystems Expert in building large scale secure chat-based web applications Expert in setting up RAG and ingestion pipelines from source (e.g. sharepoint) to vector store (e.g. cogsearch) Expert in Python, Flask, FastAPI, LlamaIndex, Langchain, React, Angular, Vue. Fluent in Document Intelligent, API Management, Function/Logic Apps, Cosmo DB Strong problem-solving skills and attention to details Required Candidate profile Candidate Experience Should Be : 7 To 10 Candidate Degree Should Be : BE-Comp/IT,BE-Other,BTech-Comp/IT,BTech-Other,MBA,MCA

Job Title: AI/ML Engineer Location: Pune (Hybrid) Join our team as a AI/ML Engineer and be a part of our cutting-edge Generative AI lab. As an AI Engineer, you will play a pivotal role in developing and implementing core AI functionalities to drive value throughout the consulting lifecycle. Your responsibilities will include innovating information extraction, synthesis, and analysis of both structured and unstructured data to derive valuable quantitative insights. Responsibilities: Develop and own AI functionalities across the lifecycle, from initial proof of concept to production-ready pipelines. Research and experiment with new and emerging AI capabilities to establish performance metrics and suitability for proof of concept. Enhance developed pipelines into production-level modules for seamless integration into user experiences. Collaborate with the product team to ensure seamless deployment and functionality of AI solutions. Stay abreast of industry trends and technological advancements to continuously improve AI capabilities. Requirements: Experience in data science, specializing in building and deploying AI/ML applications. Proficiency in Python is a must, along with experience in ML libraries like Scikit-Learn and SQL. Familiarity with cloud-based platforms such as Azure and vector databases like pinecone is preferred. Deep understanding of statistical and machine learning models, including data preparation, model selection, hyperparameter tuning, and performance evaluation. Experience in processing unstructured natural language data and text extraction. Knowledge of NLP techniques, including text processing, TF-IDF, semantic parsing, and sentiment analysis, is a plus. Previous exposure to Generative AI and large language models will be advantageous. Strong analytical and problem-solving skills, with the ability to work independently with guidance. An advanced degree in Statistics, Computer Science, Physics, or Mathematics is preferred. Benefits: Unlimited Leave Policy Flexible working Hours Supportive team for Personal and Professional Growth Joining our team means being part of a founding team where you'll have ample opportunities for personal and professional growth.

Python LLM Engineer (WFH) Experience: 3 - 5 Years Salary: INR 20,00,000-35,00,000 / year Preferred Notice Period : Within 15 days Shift : 10:30 AM to 7:30 PM IST Opportunity Type: Remote Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients.) Must have skills required : API, Communication, LangChain, LLMs, Pinecone/ Weaviate/ FAISS/ ChromaDB, rag, AWS, Python Good to have skills : CI/CD, multimodal AI, Prompt engineering, Reinforcement Learning, Voice AI Platformance (One of Uplers' Clients) is Looking for: Python LLM Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description We are seeking a highly skilled Python LLM Engineer to join our AI team. The ideal candidate should have deep expertise in large language models (LLMs), experience in building Retrieval-Augmented Generation (RAG) systems, and a strong background in AI-driven applications. This role requires hands-on experience with LangChain, multimodal AI, vector databases, agentic AI, and cloud-based AI infrastructure, particularly AWS and AWS Bedrock. Python will be the primary development language for this role. Key Responsibilities: Design, develop, and optimize applications leveraging LLMs using LangChain and other frameworks. Build and fine-tune Retrieval-Augmented Generation (RAG) based AI systems for efficient information retrieval. Implement and integrate major LLM APIs such as OpenAI, Anthropic, Google Gemini, and Mistral. Develop and optimize AI-driven voice applications and conversational agents using Python. Research and apply the latest advancements in AI, multimodal models, and vector databases. Architect and deploy scalable AI applications using AWS services, including AWS Bedrock. Design and implement vector search solutions using Pinecone, Weaviate, FAISS, or similar technologies. Develop agentic AI products that leverage autonomous decision-making and multi-agent coordination. Write efficient and scalable backend services in Python for AI-powered applications. Develop and optimize AI model fine-tuning and inference pipelines in Python. Implement end-to-end MLOps pipelines for model training, deployment, and monitoring using Python-based tools. Optimize LLM inference for performance and cost efficiency using Python frameworks. Ensure the security, scalability, and reliability of AI systems deployed in cloud environments. Required Skills and Experience: Strong experience with Large Language Models (LLMs) and their APIs (OpenAI, Anthropic, Cohere, Google Gemini, Mistral, etc.). Proficiency in LangChain and experience in developing modular AI pipelines. Deep knowledge of Retrieval-Augmented Generation (RAG) and its implementation. Experience with voice AI technologies, ASR (Automatic Speech Recognition), and TTS (Text-to-Speech), using Python-based frameworks. Familiarity with multimodal AI models (text, image, audio, and video processing) and Python libraries such as OpenCV, PIL, and SpeechRecognition. Hands-on experience with vector databases (Pinecone, Weaviate, FAISS, ChromaDB, etc.). Strong background in developing agentic AI products and autonomous AI workflows. Expertise in Python for AI/ML development, including libraries like TensorFlow, PyTorch, Hugging Face, FastAPI, and LangChain. Experience with AWS cloud services, including AWS Bedrock, Lambda, S3, and API Gateway, with Python-based implementations. Strong understanding of AI infrastructure, model deployment, and cloud scalability. Preferred Qualifications: Experience in reinforcement learning and self-improving AI agents. Exposure to prompt engineering, chain-of-thought prompting, and function calling. Prior experience in building production-grade AI applications in enterprise environments. Familiarity with CI/CD pipelines for AI model deployment and monitoring, using Python-based tools such as DVC, MLflow, and Airflow. Why Join Us? Work with cutting-edge AI technologies and build next-gen AI products. Be part of a highly technical and innovative AI-driven team. Competitive salary, stock options, and benefits. Opportunity to shape the future of AI-driven applications and agentic AI systems. Engagement Type: Direct-hire on the TBD payroll on behalf of platformance Job Type: Permanent Location: Remote Working time: 10:30 AM to 7:30 PM IST Interview Process - The HR team will conduct an initial culture fit assessment before technical rounds. Initial Technical Discussion: Live discussion to assess core competencies. Technical Assignment: Candidates will be given 4 days to complete a hands-on coding test. Final Interview (Optional): Review of the coding test and further technical discussion if required. How to Apply? Easy 3-Step Process: Step 1: Click On Apply! And Register or Login on our portal Step 2: Upload updated Resume & Complete the Screening Form Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Platformance is a Growth Technology Platform that helps brands connect with customers using a pay-per-outcome model. Platformance is a growth technology platform built to help advertisers achieve measurable business outcomes, not just marketing results. Our mission is to simplify the complexities of digital advertising while ensuring every campaign delivers tangible results. About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. ( Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Roles and Responsibilities : Design, develop, test, and deploy AIML (Artificial Intelligence Markup Language) solutions using Python programming language. Collaborate with cross-functional teams to integrate AIML models into existing systems and applications. Develop predictive models using regression techniques to solve complex business problems. Troubleshoot issues related to AIML model performance, data quality, and system integration. Job Requirements : 5-7 years of experience in developing AIML-based applications or similar technologies. Strong proficiency in Python programming language with expertise in ML libraries such as scikit-learn or TensorFlow. Experience with building predictive models using regression techniques for solving real-world problems.

Role: Agentic AI Engineer-Healthcare Exp: 4-10 years Location: Hyderabad, India (Onsite) Job Description: Role and Responsibilities: Design Agentic AI Systems for Healthcare Develop frameworks for efficient agent-to-agent communication, dynamic task assignment, and context-aware decision-making, with a focus on improving healthcare operations and patient outcomes. Leverage tools such as LangGraph, AutoGen, and OpenAI Swarm to enhance decision support systems in clinical environments. Implement Retrieval-Augmented Generation (RAG) pipelines and memory management techniques to ground agents in healthcare-specific knowledge (e.g., medical literature, patient records, treatment protocols). Build Versatile AI Capabilities for Healthcare Work with Vision-Language Models (VLMs) to analyze medical imaging (e.g., X-rays, MRIs) alongside text-based reasoning to assist in tasks such as anomaly detection, diagnosis support, and treatment planning. Create autonomous agents capable of executing complex healthcare tasks, such as data analysis, patient record management, or clinical decision support, triggered by real-time health data or environmental factors. Optimize AI for Real-World Healthcare Impact Deploy scalable AI workflows in cloud environments (AWS/GCP), ensuring robust performance for time-sensitive healthcare applications, such as real-time patient monitoring or critical care support. Implement observability tools like LangSmith to track agent behavior, identify anomalies, debug failures, and enhance the reliability and safety of AI systems in healthcare settings. Human-in-the-Loop Intelligence in Healthcare Design mechanisms to integrate human oversight into AI systems, ensuring that healthcare professionals can intervene when necessary. Implement features like bias testing, fallback protocols, and explainability to balance autonomy with safety and ethical considerations. Leverage tools like LangSmith for real-time monitoring and debugging of AI agents to optimize performance and reduce risk in clinical and healthcare-related environments. Proven AI Development Experience: Demonstrate a portfolio of projects highlighting expertise in multi-agent systems, RAG implementations, and decision automation, specifically applied to healthcare (GitHub/Kaggle links required). Proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face) with a focus on healthcare applications. Technology/Skills Required: Experience with cloud platforms (AWS, GCP) and vector databases (Pinecone, Milvus) in healthcare contexts, managing patient data, clinical workflows, and medical knowledge. Familiarity with agentic frameworks (LangChain, CrewAI) and large language model orchestration to enhance clinical decision support systems. Interested candidate can drop the CV at saepoori@theaesgroup.com or notify+JzW2LVeiJVHx@atsapplications.com

Project Description: Grid Dynamics aims building enterprise generative AI framework to deliver innovative, scalable and efficient AI-driven solutions across business functions.Due to constant scaling of digital capabilities the platform requires enhancements to incorporate cutting-edge generative AI features and meet emerging business demands. Platform should onboard brand new capabilities like Similarity Search (image,video and voice);Ontology and entity managment;voice and file mgmt [text to speech & vice-versa, metadata tagging, multi-media file support];Advanced RAG ; Multi-Modal capabilities Responsibilities: As an LLMOps Engineer, you will be responsible for providing expertise on overseeing the complete lifecycle management of large language models (LLM). This includes the development of strategies for deployment, continuous integration and delivery (CI/CD) processes, performance tuning, and ensuring high availability of our LLM services. You will collaborate closely with data scientists, AI/ML engineers, and IT teams to define and align LLM operations with business goals, ensuring a seamless and efficient operating model. In this role, you will: Define and disseminate LLMOps best practices. Evaluate and compare different LLMOps tools to incorporate the best practices. Stay updated on industry trends and advancements in LLM technologies and operational methodologies. Participate in architecture design/validation sessions for the Generative AI use cases with entities. Contribute to the development and expansion of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI. Design, implement, and oversee the infrastructure required for the efficient operation of large language models in collaboration with client entities. Provide expertise and guidance to client entities in the development and scaling of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI Serve as the expert and representative on LLMops Practices, including: (1) Developing and maintaining CI/CD pipelines for LLM deployment and updates. (2) Monitoring LLM performance, identifying and resolving bottlenecks, and implementing optimizations. (3) Ensuring the security of LLM operations through comprehensive risk assessments and the implementation of robust security measures. Collaborate with data and IT teams to facilitate data collection, preparation, and model training processes. Practical experience with training, tuning, utilizing LLMs/SLMs. Strong experience with GenAI/LLM frameworks and techniques, like guardrails, Langchain, etc. Knowledge of LLM security and observability principles. Experience of using Azure cloud services for ML Experience of using Azure cloud services for ML Min requirements: Programming languages: Python Public Cloud: Azure Frameworks: K8s, Terraform, Arize or any other ML/LLM observability tool Experience: Experience with public services like Open AI, Anthropic and similar, experience deploying open source LLMs will be a plus Tools: LangSmith/LangChain,guardrails Would be a plus: Knowledge of LLMOps best practices. Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack) We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office

Project Description: Grid Dynamics wants to build a centralized, observable and secure platform for their ML, Computer Vision, LLM and SLM models. Grid Dynamics wants to onboard a vast number of AI agents, able to cover multiple required skills, ensuring a certain level of control and security in regards to their usage and availability. The observable platform must be vendor-agnostic, easy to extend to multiple type of AI applications and flexible in terms of technologies, frameworks and data types. This project is focused on establishing a centralized LLMOps capability where every ML, CV, AI-enabled application is monitored, observed, secured and provides logs of every activity. The solution consists of key building blocks such monitor every step in a RAG, Multimodal RAG or Agentic Platform, track performances and provide curated datasets for potential fine-tuning. Alignment with business scenarios, PepVigil provides also certain guardrails that allow or block interactions user-to-agent, agent-to-agent or agent-to-user. Also, Guardrails will enable predefined workflows, aimed to give more control over the series of LLM chains. Details on Tech Stack Job Qualifications and Skill Sets Advanced degree in Data Science, Computer Science, Statistics, or a related field Setting up Agent Mesh (LangSmith) Setting up Agent communication protocols (JSON/XML etc) Setting up message queues, CI/CD pipelines (Azure Queue Storage, Azure DevOps) Setting up integrations Langgrah, LangFuse Knowledge on Observability tool Arize-Phoenix tools Managing Agent Registry, Integrating with AgentAuth framework like Composio Setting up AgentCompute (Sandpack, E2BDev, Assistant APIs) Integration with IAM (Azure IAM, OKTA) Performing/Configuring Dynamic Orchestration and agent permissions Tech Stack Required: ML MLOPs Agent (Agent / Agent Mesh) LangFuse, LanChain, LangGraph Deployments (Docker, Jenkins, Kubernetes) Cloud Platforms: Azure/AWS/GCP We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office

Summary of the Role: We are seeking an AI Prompt Engineer with expertise in Large Language Models (LLMs) and prompt engineering to support legal tech solutions, specifically in contract lifecycle management and contract-related AI implementations. The ideal candidate will have a strong background in AI, NLP, and structured prompt engineering, with a keen understanding of legal tech applications. Prior experience in the legal domain is a plus but not mandatory. What you will do: Design, develop, and refine AI prompts for legal tech applications, ensuring accuracy and contextual relevance in contract-related workflows. Work with Large Language Models (LLMs) to enhance AI-driven solutions for contract analysis, review, and automation. Optimize prompt structures and techniques to improve AI-generated outputs in contract drafting, compliance, and negotiations. Research, test, and implement best practices in prompt engineering to maximize efficiency and accuracy in contract delivery. Evaluate and refine AI-generated legal documents to align with compliance standards and client requirements. Stay updated with advancements in LLMs, prompt engineering methodologies, and AI-driven legal tech solutions. What you bring: Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. Minimum 5 years of overall professional experience, with at least 2 years in AI prompt engineering. Strong understanding of LLMs (GPT, Claude, Gemini, Llama, etc.) and their application in legal or enterprise use cases. Proven expertise in prompt design, optimization, and fine-tuning for AI-driven text generation. Hands-on experience with AI tools, frameworks, and APIs (OpenAI, Hugging Face, LangChain, etc.). Strong problem-solving skills and ability to work in a fast-paced environment. Excellent communication and collaboration skills to work with cross-functional teams. Bonus Points: Basic understanding of contracts, legal terminology, and compliance standards. Applications must be submitted exclusively through Execo's official job postings located on the following platforms: Execo Careers Website: https://www.execo.com/careers LinkedIn: https://www.linkedin.com/company/execogroup/jobs/ Indeed: US & Kenya: https://www.indeed.com/cmp/Execo-Group-Inc India: https://in.indeed.com/cmp/Execo-Group-Inc UK: https://uk.indeed.com/cmp/Execo-Group-Inc Philippines: https://ph.indeed.com/cmp/Execo-Group-Inc Singapore: https://sg.indeed.com/cmp/Execo-Group-Inc Naukri: https://www.naukri.com/

Job Summary: As the Lead AI/ML Engineer, you will be responsible for designing, developing, and implementing machine learning algorithms and AI solutions that address complex business challenges. You will lead a team of engineers collaborating with cross-functional teams to drive the successful deployment of AI initiatives. Your expertise will be crucial in shaping our AI strategy and ensuring the delivery of high-quality, scalable solutions. Key Responsibilities: Lead the design and development of machine learning models and AI solutions to solve business problems. Select appropriate machine learning or deep learning models based on problem context and data availability. Develop, train, test, and validate models using state-of-the-art methodologies and frameworks. Collaborate with analytics, developers and domain experts to acquire, clean, and preprocess large datasets. Engineer features and performs exploratory data analysis to ensure data quality and model readiness. Containerize models (Docker/Kubernetes), implement monitoring (Prometheus/Grafana), and automate pipelines (MLflow/Kubeflow). Implement models into production environments, ensuring robustness, scalability, and maintainability. Develop and maintain CI/CD pipelines for seamless model integration and deployment. Monitor and evaluate model performance post-deployment and iterate based on feedback and performance metrics. Work closely with cross-functional teams (e.g., product, engineering, Ux, Ax) to align model development with business objectives. Stay updated with emerging trends in AI/ML research and tools, integrating best practices into the development process. Document model architecture, development processes, and performance evaluations thoroughly. Share insights and technical know-how with team members to foster a culture of continuous learning and improvement. Research & Innovation: Stay ahead of AI trends (LLMs, generative AI) and advocate for ethical AI practices. Develop and implement best practices for model development, testing, and deployment. Analyze large datasets to extract insights and improve model performance. Communicate complex technical concepts to non-technical stakeholders effectively. Ensure compliance with data privacy and security regulations in all AI/ML initiatives. Qualifications: Bachelors or masters degree in computer science, Machine Learning, or a related field. Proven experience (5+ years) in AI/ML engineering, with a strong portfolio of successful projects. Proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment. Strong communication and interpersonal skills, with the ability to lead and inspire a team. Experience with version control systems (e.g., Git) and agile development methodologies is a plus.

We are seeking an enthusiastic Python Developer with expertise in Azure, Data Science, Natural Language Processing (NLP), and experience working with Streamlit, Gradio, and Flask. As a Python Developer at our company, you will be involved in building cutting-edge applications, leveraging large language models, and deploying solutions using Azure cloud technologies. If you are passionate about pushing the boundaries of AI-driven applications and have hands-on experience with Streamlit, Gradio, Flask, and Hugging Face's large language models, we would love to have you join our team. Responsibilities: 1. Collaborate with cross-functional teams to understand business requirements and design software solutions. 2. Develop and deploy Python-based applications using Streamlit, Gradio, and Flask frameworks for interactive data visualization and AI-powered interfaces. 3. Utilize Azure cloud services for seamless deployment, scaling, and management of applications. 4. Apply data science and NLP techniques to implement advanced analytics and machine learning algorithms. 5. Integrate and fine-tune large language models from Hugging Face, tailoring them to specific use cases. 6. Explore and experiment with state-of-the-art NLP models to improve application performance. 7. Work with large datasets and implement data preprocessing, cleaning, and transformation pipelines. 8. Optimize application performance, responsiveness, and scalability for large user bases. 9. Collaborate with data scientists to implement and integrate NLP-driven solutions into existing applications. 10. Ensure the security and privacy of data throughout the development process. 11. Conduct code reviews and adhere to best practices for code quality and maintainability. 12. Stay updated on the latest advancements in NLP, data science, and cloud technologies.

We are seeking experienced AI Engineer to design, develop & implement intelligent agents to enhance our video intelligence capabilities. Hands-on experience with both closed & open-source LLMs and production-grade agent implementation Required Candidate profile Experience working with LLMs (both closed models like GPT-4, Claude, & open-source models like Llama, Mistral) Production-grade agent implementation using frameworks such as LangChain, CrewAI, n8n

Job Description We are seeking a skilled Generative AI Engineer with a strong background in Python to join our dynamic team. In this role, you will integrate backend development expertise with the latest advancements in AI to create impactful solutions. If you excel in a fast-paced environment and enjoy tackling complex challenges, we encourage you to apply. Key Responsibilities: Generative AI Development Develop and implement generative AI models using frameworks like LangChain or Llama-Index. Apply prompt engineering techniques to design effective queries and ensure optimal LLM responses for diverse use cases. Master advanced LLM functionalities, including prompt optimization, hyperparameter tuning, and response caching. Implement Retrieval-Augmented Generation (RAG) workows by integrating vector databases like Pinecone, Weaviate, Supabase, or PGVector for ecient similarity searches. Work with embeddings and build solutions that leverage similarity search for personalized query resolution. Explore and process multimodal data, including image and video understanding and generation. Integrate observability tools for monitoring and evaluating LLM performance to ensure system reliability. Backend Engineering Build and maintain scalable backend systems using Python frameworks such as FastAPI, Django, or Flask. Design and implement RESTful APIs for seamless communication between systems and services. Optimize database performance with relational databases (PostgreSQL, MySQL) and integrate vector databases (Pinecone, PGVector, Weaviate, Supabase) for advanced AI workows. Implement asynchronous programming and adhere to clean code principles for maintainable, high-quality code. Seamlessly integrate third-party SDKs and APIs, ensuring robust interoperability with external systems. Develop backend pipelines for handling multimodal data processing, and supporting text, image, and video workows. Manage and schedule background tasks with tools like Celery, cron jobs, or equivalent job queuing systems. Leverage containerization tools such as Docker for ecient and reproducible deployments. Ensure security and scalability of backend systems with adherence to industry best practices. Qualications: Essential : Strong Programming Skills: Prociency in Python and experience with backend frameworks like FastAPI, Django, or Flask. Generative AI Expertise: Knowledge of frameworks like LangChain, Llama-Index, or similar tools, with experience in prompt engineering and Retrieval-Augmented Generation (RAG). Data Management: Hands-on experience with relational databases (PostgreSQL, MySQL) and vector databases (Pinecone, Weaviate, Supabase, PGVector) for embeddings and similarity search. Machine Learning Knowledge: Familiarity with LLMs, embeddings, and multimodal AI applications involving text, images, or video. Deployment Experience: Prociency in deploying AI models in production environments using Docker and managing pipelines for scalability and reliability. Testing and Debugging: Strong skills in writing and managing unit and integration tests (e.g., Pytest), along with application debugging and performance optimization. Asynchronous Programming: Understanding of asynchronous programming concepts for handling concurrent tasks eciently. Preferred: Cloud Prociency: Familiarity with platforms like AWS, GCP, or Azure, including serverless applications and VM setups. Frontend Basics: Understanding of HTML, CSS, and optionally JavaScript frameworks like Angular or React for better collaboration with frontend teams. Observability and Monitoring: Experience with observability tools to track and evaluate LLM performance in real-time. Cutting-Edge Tech: Awareness of trends in generative AI, including multimodal AI applications and advanced agentic workows. Security Practices: Knowledge of secure coding practices and backend system hardening. Certications: Relevant certications in AI, machine learning, or cloud technologies are a plus.

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.