209 Langchain Jobs - Page 4

Job Summary We are hiring a Junior AI Engineer to design and implement AI-driven automation solutions. You'll work with cross-functional teams to streamline operations and reduce manual tasks using machine learning, APIs, and scripting. Training will be provided , making this a great opportunity for candidates with a strong foundation and a desire to grow in AI and automation. Responsibilities Automate repetitive tasks using AI/ML or Python scripting. Integrate AI features into web apps with development teams. Connect ML models to systems like Frappe/ERPNext via APIs. Build and maintain clean, well-documented automation workflows. Prototype tools using speech-to-text , OCR , or computer vision . Stay updated on new AI tools and suggest improvements. Qualifications: Proficient in Python and basic scripting. Exposure to AI/ML through projects, coursework, or certifications. Familiar with OpenCV, Numpy, Pandas, or PyTorch. Experience or familiarity with Large Language Models (LLMs) and Generative AI technologies (e.g., GPT, Grok). Hands-on experience or understanding of LangChain and its applications in building LLM-powered workflows. Understanding of APIs and web integrations. Bachelors degree (or pursuing) in Computer Science, Data Science, Engineering, or a related field. Strong problem-solving skills and eagerness to learn.

Python -GenAI and ML - J49048 Key Responsibilities End-to-End GenAI Development o Design and build GenAI applications using LLMs (e.g., LLaMA, Mistral, GPT-J, Falcon, Claude, etc.) o Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases like FAISS, ChromaDB, or Weaviate o Create and tune prompt templates, guardrails, and output parsers using tools like LangChain, Haystack, or LlamaIndex Agentic AI & Autonomy o Develop AI agents that use planning, memory, tools, and self-reflection (e.g., using AutoGen, CrewAI, or LangGraph) o Build task-oriented chains with autonomous behaviors for decision-making and workflow automation Model Training & Fine-Tuning o Perform SFT on open-source models using libraries like HuggingFace Transformers, PEFT, LoRA, or QLoRA o Evaluate model performance using GenAI metrics and frameworks (e.g., DeepEval, TruLens) ML System Integration o Use ML libraries like Scikit-learn, TensorFlow, PyTorch, and XGBoost to integrate traditional ML pipelines alongside GenAI components o Develop APIs and microservices (using FastAPI, Flask) to expose GenAI/ML services Security, Observability & Control Required Candidate profile Candidate Experience Should Be : 1 To 3 Candidate Degree Should Be : BE-Comp/IT

Key deliverables: Develop AI automation scripts using Python and OpenAI API Deploy GenAI solutions and workflows in Azure Implement LLM-powered applications with Langchain Integrate AI tools with Azure Cognitive and Bot Services Role responsibilities: Design and build scalable AI/ML models and pipelines Lead Azure-based GenAI deployments and orchestration Collaborate with data scientists and developers on solution design Optimize model performance and ensure reliability in production

Key deliverables: Develop AI automation scripts using Python and OpenAI API Deploy GenAI solutions and workflows in Azure Implement LLM-powered applications with Langchain Integrate AI tools with Azure Cognitive and Bot Services Role responsibilities: Design and build scalable AI/ML models and pipelines Lead Azure-based GenAI deployments and orchestration Collaborate with data scientists and developers on solution design Optimize model performance and ensure reliability in production

Key deliverables: Develop AI automation scripts using Python and OpenAI API Deploy GenAI solutions and workflows in Azure Implement LLM-powered applications with Langchain Integrate AI tools with Azure Cognitive and Bot Services Role responsibilities: Design and build scalable AI/ML models and pipelines Lead Azure-based GenAI deployments and orchestration Collaborate with data scientists and developers on solution design Optimize model performance and ensure reliability in production

Key Responsibilities: Deliver engaging and interactive training sessions (24 hours total) based on structured modules. Teach integration of monitoring, logging, and observability tools with machine learning. Guide learners in real-time anomaly detection, incident management, root cause analysis, and predictive scaling. Support learners in deploying tools like Prometheus, Grafana, OpenTelemetry, Neo4j, Falco, and KEDA. Conduct hands-on labs using LangChain, Ollama, Prophet, and other AI/ML frameworks. Help participants set up smart workflows for alert classification and routing using open-source stacks. Prepare learners to handle security, threat detection, and runtime anomaly classification using LLMs. Provide post-training support and mentorship when necessary.

Job Title: AI/ML and Chatbot Lead Experience Level: 10+ Years (Lead/Architect level) Location: Remote Employment Type: Full-time No. of Positions: 1 Job Overview: We are seeking a visionary and hands-on AI/ML and Chatbot Lead to spearhead the design, development, and deployment of enterprise-wide Conversational and Generative AI solutions. This role will establish and scale our AI Lab function, define chatbot and multimodal AI strategies, and deliver intelligent automation solutions that enhance user engagement and operational efficiency. Key Responsibilities Define and lead the enterprise-wide strategy for Conversational AI, Multimodal AI, and Large Language Models (LLMs). Build an AI/Chatbot Lab , creating a roadmap and driving innovations across in-app, generative, and conversational AI. Architect scalable AI/ML systems including presentation, orchestration, AI, and data layers. Collaborate with business stakeholders to assess needs, conduct ROI analyses, and deliver impactful AI use cases. Identify and implement agentic AI capabilities and SaaS optimization opportunities. Deliver POCs, pilots, and MVPs owning the design, development, and deployment lifecycle. Lead, mentor, and scale a high-performing team of AI/ML engineers and chatbot developers . Build multi-turn, memory-aware conversations using frameworks like LangChain or Semantic Kernel . Integrate bots with platforms like Salesforce, NetSuite, Slack , and custom applications via APIs/webhooks. Implement and monitor chatbot KPIs using tools like Kibana , Grafana , and custom dashboards. Champion ethical AI , governance, and data privacy/security best practices. Must-Have Skills 10+ years in AI/ML; demonstrable success in chatbot, conversational AI , and generative AI implementations. Experience building and operationalizing an AI/Chatbot architecture framework used enterprise-wide. Expertise in: Python , LangChain, ElasticSearch, NLP (spaCy, NLTK, Hugging Face) LLMs (e.g., GPT, BERT), RAG, prompt engineering Chatbot platforms (Azure OpenAI, MS Bot Framework), CLU, CQA AI solution deployment and monitoring at scale Familiarity with: Machine learning algorithms, deep learning, reinforcement learning NLP techniques for NLU/NLG Cloud platforms ( AWS, Azure, GCP ), Docker , Kubernetes Vector DBs (Pinecone, Weaviate, Qdrant) Semantic search, knowledge graphs, intelligent document processing Strong grasp of AI governance , documentation, and compliance standards Excellent team leadership, communication, and documentation skills Good-to-Have Skills Experience with Glean , Perplexity.ai , Rasa , XGBoost Familiarity with Salesforce , NetSuite , and business domains like Customer Success Knowledge of RPA tools like UiPath and its AI Center Role & responsibilities Interested candidate can call at 7087707007

Minimum experience: 5 years. Basic Guidelines : Ensure all submitted CVs are up to date. Maximum Notice Period 3 weeks Willingness to go for face 2 face interview in 24 hours. Employment verification 5 years and 7 years criminal background check. No fake and proxy interviews. Vendors will be blacklisted by TSI/ our Client, if guilty. Maintain the below tracker. Java Fullstack developer Primary skills: Java 8/11, Spring boot, Microservices, Rest API, UI REACT JS, REDUX Location: Bangalore and Chennai 2. Python + UI/API developer Primary skills: Python, Rest API, UI REACT JS, REDUX Location: Gurgaon 3.UI Engineer Primary skills: UI REACT JS, REDUX, JavaScript,ES6/Typescript,HTML5,CSS3,Bootstrap) Secondary skills: Java 8/11, Spring boot, Microservices, Rest API Location: Gurgaon and Bangalore 4. API Automation tester + Java scripting API Automation testing, Java scripting, SQL, MongoDB, Selenium Secondary skills: Rest assured / karate, Cucumber framework. DB Concepts, json queries Location: Bangalore and Gurgaon Job Description: 5+ years in Quality Assurance and testing. Demonstrated experience with Java or Python. Good experience in API automation using Selenium (Rest Assured or any other framework for automation and POSTMAN for manual). Preferably worked on creating frameworks. Must be well versed in BDD Cucumber frameworks. Working knowledge of MySQL and its implementation. Experience in creating scripts through REST APIs. Able to manage multiple work streams, independent, able to communicate well. Required Details Candidate's Full Name (As per passport): Contact Number: Email ID: Passport: LinkedIn ID link: Location (City & State): Relocation (Yes / No): Availability to join the project: Total working Experience: Currently on project (Yes/No): Have you Ever worked with Client: (If yes details) Any Interviews Pending: Any Offers in hand: Have you been submitted by Client: Any Issue with BGC: Bachelors details: Masters details: Rate: please submit your resumes to Naveen@tanishasystems.com

Job Description: Oracle Cloud Infrastructure (OCI) is a pioneering force in cloud technology, merging the agility of startups with the robustness of an enterprise software leader. Within OCI, the Oracle Generative AI Service team spearheads innovative solutions at the convergence of artificial intelligence and cloud infrastructure. As part of this team, you'll contribute to large-scale cloud solutions utilizing cutting-edge machine learning technologies, aimed at addressing complex global challenges. Join us to create innovative solutions using top-notch machine learning technologies to solve global challenges. We're looking for an experienced Principal Applied Data Scientist to join our OCI Gen-AI Solutions team for strategic customers. In this role, you'll collaborate with applied scientists and product managers to design, develop, and deploy tailored Gen-AI solutions with an emphasis on Large Language Models (LLMs), Agents, MPC and Retrieval Augmented Generation (RAG) with large OpenSearch clusters. As part of the OCI Gen AI and Data Solutions for strategic customers team, you will be responsible for developing innovative Gen AI and data services for our strategic customers.As a Principal Applied Data Scientist, you'll lead the development of advanced Gen AI solutions using the latest ML technologies combined with Oracle's cloud expertise. Your work will significantly impact sectors like financial services, telecom, healthcare, and code generation by creating distributed, scalable, high-performance solutions for strategic customers. Work directly with key customers and accompany them on their Gen AI journey - understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers. You will dive deep into model structure to optimize model performance and scalability. You will build state of art solutions with brand new technologies in this fast-evolving area. You will configure large scale OpenSearch clusters, setting up ingestion pipelines to get the data into the OpenSearch. You will diagnose, troubleshoot, and resolve issues in AI model training and serving. You may also perform other duties as assigned. Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Be an enthusiastic, self-motivated, and a great collaborator. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications and experience Bachelors or master's in computer science or equivalent technical field with 10+ years of experience Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations). Demonstrated experience in designing and implementing scalable AI models and solutions for production,relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams. Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming. Practical experience with setting up and finetuning large OpenSearch Clusters. Experience in setting up data ingestion pipelines with OpenSearch. Experience with search algorithms, indexing, optimizing latency and response times. Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts. Familiarity with Agents and Agent frameworks and Model Predictive Control (MPC) Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences. Ability and passion to mentor and develop junior machine learning engineers. Proficient in Python and shell scripting tools. Preferred Qualifications : Masters or Bachelor's in related field with 5+ years relevant experience Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus. Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus. Experience with semantic search, multi-modal search and conversational search. Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities.Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc. Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies. Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers. Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers). Experience in diagnosing, fixing, and resolving issues in AI model training and serving. Career Level - IC4

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Key Responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcedeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

Role: AI Engineer Microsoft CoPilot Experience: 4 - 8 Years Location: Pune. Mandatory Skills: Microsoft Copilot, Gen AI, Azure AI, LLM, Langchain, RAG. Notice Period: Immediate Joiners Job Description: Requirements: Bachelors or Master’s degree in Computer Science, Data Science, or a related field. Proven experience in developing and deploying AI/ML models in real-world applications. Strong programming skills, especially in Python, and familiarity with version control systems like Git. Extensive experience in the Microsoft environment, with expertise in CoPilot and related technologies. Excellent problem-solving and communication skills. Ability to work independently and collaboratively in a fast-paced, dynamic environment. Responsibilities: Agent Development: Design, implement, and optimize AI agents using Microsoft CoPilot and related technologies. Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration: Deploy AI solutions within client environments, ensuring scalability and seamless integration with exiiting systems. Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation: Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support: Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement: Stay updated on advancements in AI, machine learning, and Microsoft’s AI technologies. Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills: Strong knowledge of Microsoft Power Automate, Azure AI, and CoPilot features. Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. Understanding of conversational AI technologies and chatbot frameworks. Experience with data analysis tools and techniques to uncover insights and optimize models.

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Hiring AI & Data Retrieval Engineer with expertise in NLQ, Text-to-SQL, LLMs, LangChain, pgVector, PostgreSQL, vector search, Python, AI libraries, Agentic AI & API integration. Exp with NLP, RAG, BI tools, live projects & LLM fine-tuning preferred.

Role - Senior Data Scientist / Senior Gen AI Engineer Exp Range - 8 to 18 yrs Position - Permanent Fulltime Company - Data Analytics & AIML MNC Location - Hyderabad, Pune, Bangalore (Relocation accepted) About the Role: We are seeking a Software Engineer with expertise in Generative AI and Microsoft technologies to design, develop, and deploy AI-powered solutions using the Microsoft ecosystem. You will work with cross-functional teams to build scalable applications leveraging generative AI models and Azure services. Skills Required: Experience with Large Language Models (LLMs) like GPT, LLaMA, Claude, etc. Proficiency in Python for building and fine-tuning AI/ML models Familiarity with LangChain , LLMOps , or RAG (Retrieval-Augmented Generation) pipelines Experience with Vector Databases (e.g. FAISS, Pinecone, Weaviate) Knowledge of Prompt Engineering and model evaluation techniques Exposure to cloud platforms (Azure, AWS or GCP) for deploying GenAI solutions Preferred Skills: Experience with Azure OpenAI , Databricks or Microsoft Fabric Hands-on with Hugging Face Transformers , OpenAI APIs or custom model training

Preferred candidate profile 1. LLM Basics : (Llama, Gemini ) : Understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks. One should know what the data is trained on and any potential biases/issues that there may be with the data . Knowledge on know exactly how big LLMs can be, how computationally expensive training will be, and the differences between training LLMs and machine learning models. 1. Prompt Engineering : Knowledge on designing inputs for LLMs once theyre developed. 2. Prompt Engineering with OpenAI : As a leading figure in LLMs and generative AI, it’s important to know how to use prompt engineering specifically with OpenAI tools, as you’ll likely be using them at some point in your career. 3. Question-Answering :Question-answering (QA) LLMs are a type of large language model that has been trained specifically to answer questions. 4. Fine-Tuning : Knowledge on Fine-tuning to improve the performance of an LLM on a variety of tasks, including text generation, translation, summarization, and question-answering. Customize LLMs for specific applications, such as customer service chatbots or medical diagnosis systems. Awareness on supervised learning. This involves providing the LLM with a dataset of labelled data, where each data point is a pair of input and output.. 1. Lang Chain : To architect complex LLM pipelines by chaining multiple models together (Classification, text generation, code generation, etc.)`Agents` to interact with all these external systems to execute actions dictated by LLMs. 2. Parameter Efficiency/Tuning : LORA 3. RAG Building : Generative AI, mastering RAG building—short for Retrieval-Augmented Generation—is becoming increasingly crucial 4. ML OPS and in particular LLMOps : Large Language Model Operations, is the practice of managing and maintaining large language models (LLMs) in a production setting 5. TensorFlow i s like a versatile toolbox for creating intelligent programs that can learn and understand various concepts, including machine learning, deep learning, and data science

Job Type: Full Time Job Description: We are seeking an experienced AI Engineer with 4-5 years of hands-on experience in designing and implementing AI solutions. The ideal candidate should have a strong foundation in developing AI/ML-based solutions, including expertise in Computer Vision (OpenCV). Additionally, proficiency in developing, fine-tuning, and deploying Large Language Models (LLMs) is essential. As an AI Engineer, candidate will work on cutting-edge AI applications, using LLMs like GPT, LLaMA, or custom fine-tuned models to build intelligent, scalable, and impactful solutions. candidate will collaborate closely with Product, Data Science, and Engineering teams to define, develop, and optimize AI/ML models for real-world business applications. Key Responsibilities: Research, design, and develop AI/ML solutions for real-world business applications, RAG is must. Collaborate with Product & Data Science teams to define core AI/ML platform features. Analyze business requirements and identify pre-trained models that align with use cases. Work with multi-agent AI frameworks like LangChain, LangGraph, and LlamaIndex. Train and fine-tune LLMs (GPT, LLaMA, Gemini, etc.) for domain-specific tasks. Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM inference. Develop NLP-based GenAI applications, including chatbots, document automation, and AI agents. Preprocess, clean, and analyze large datasets to train and improve AI models. Optimize LLM inference speed, memory efficiency, and resource utilization. Deploy AI models in cloud environments (AWS, Azure, GCP) or on-premises infrastructure. Develop APIs, pipelines, and frameworks for integrating AI solutions into products. Conduct performance evaluations and fine-tune models for accuracy, latency, and scalability. Stay updated with advancements in AI, ML, and GenAI technologies. Required Skills & Experience: AI & Machine Learning: Strong experience in developing & deploying AI/ML models. Generative AI & LLMs: Expertise in LLM pretraining, fine-tuning, and optimization. NLP & Computer Vision: Hands-on experience in NLP, Transformers, OpenCV, YOLO, R-CNN. AI Agents & Multi-Agent Frameworks: Experience with LangChain, LangGraph, LlamaIndex. Deep Learning & Frameworks: Proficiency in TensorFlow, PyTorch, Keras. Cloud & Infrastructure: Strong knowledge of AWS, Azure, or GCP for AI deployment. Model Optimization: Experience in LLM inference optimization for speed & memory efficiency. Programming & Development: Proficiency in Python and experience in API development. Statistical & ML Techniques: Knowledge of Regression, Classification, Clustering, SVMs, Decision Trees, Neural Networks. Debugging & Performance Tuning: Strong skills in unit testing, debugging, and model evaluation. Hands-on experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone). Good to Have: Experience with multi-modal AI (text, image, video, speech processing). Familiarity with containerization (Docker, Kubernetes) and model serving (FastAPI, Flask, Triton).

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

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

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

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

Seeking a highly skilled and motivated Senior Generative AI Developer with approximately 2 years of hands-on experience in developing and deploying AI models, particularly in the generative space (e.g., NLP, AL/ML, AWS, Python, RASA, MCP, Flutter). Required Candidate profile 2+ yrs of exp in AI/ML dev, with focus on gen models. Prog skills in Python & ML libraries/frameworks Langchain, spacy, NLTK, Hugging Face Exp in AI bot/agent platforms like Make, POE, RetellAI

In this role you will: Develop and fine-tune LLMs for contract analysis, regulatory classification, and risk assessment. Implement Retrieval-Augmented Generation (RAG) using vector embeddings and hybrid DB-based querying to power DPIA and compliance workflows. Build AI-driven contract analysis systems to detect dark patterns, classify clauses, and provide remediation suggestions. Develop knowledge graph-based purpose taxonomies for privacy policies and PII classification. Automate data discovery for structured and unstructured data, classifying it into PII categories. Optimize sliding window chunking, token-efficient parsing, and context-aware summarization for legal and compliance texts. Build APIs and ML services for deploying models in a high-availability production environment. Collaborate with privacy, legal, and compliance teams to build AI solutions that power Privy s data governance tools. Stay ahead of the curve with agentic RAG, multi-modal LLMs, and self-improving models in the compliance domain. Skills Required: LLM , RAG , AgenticAI , NLP , Python , Problem solving Candidate Attributes: Must-Have Skills 3-5 years of experience in Machine Learning, NLP, and LLM-based solutions. Strong expertise in fine-tuning and deploying LLMs (GPT-4, Llama, Mistral, or custom models). Experience with RAG-based architectures, including vector embeddings (FAISS, ChromaDB, Weaviate, Pinecone, or similar). Hands-on with agentic RAG, sliding window chunking, and efficient context retrieval techniques. Deep understanding of privacy AI use cases, including contract analysis, regulatory classification, and PII mapping. Proficiency in Python and frameworks like PyTorch, TensorFlow, JAX, Hugging Face, or LangChain. Experience in building scalable AI APIs and microservices. Exposure to MLOps practices, including model monitoring, inference optimization, and API scalability. Experience working with at least one cloud provider (AWS, GCP, or Azure). Good-to-Have Skills Experience in hybrid AI architectures combining vector search + relational databases. Familiarity with functional programming languages (Go, Elixir, Rust, etc.). Understanding of privacy compliance frameworks (DPDP Act, GDPR, CCPA, ISO 27701). Exposure to Kubernetes, Docker, and ML deployment best practices. Contributions to open-source LLM projects or privacy AI research.

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

Role & responsibilities Expertise in Data Analysis, Statistics, Computer Vision, AI & Machine Learning Concepts Unflinching zeal to learn, to try out Proof of Technology for new and emerging AI/ML Design and develop applications powered by Large Language Models (LLMs) like GPT-4, Claude, Gemini, and open-source models (LLaMA, Mistral, etc.) Implement RAG pipelines using LangChain and LangGraph for production-ready applications. Build and orchestrate autonomous and tool-using LLM agents. Integrate with vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS) for semantic search and memory storage. Use tools like OpenAI Function Calling, React, or LangGraph Agents for decision-based workflows. Deploy applications using cloud platforms (Azure, AWS, GCP) with APIs, microservices, or serverless functions. Collaborate with product and design teams to develop chatbots, copilots, and multimodal interfaces. Monitor performance, cost, latency, and evaluate prompt effectiveness through prompt engineering best practices. Fine-tune, quantize, or use adapters (LoRA, PEFT) for open-source models where applicable. Stay up-to-date with the latest advancements in Gen AI, MLOps, and AI safety principles. Preferred candidate profile Bachelor's/Master's degree in Computer Science, Mathematics, Statistics, or a related field. 4-9 years of experience as a Data Scientist with strong skills in Python, NLP, Deep Learning, and Statistics. Hands-on experience with Generative AI, LangChain, LangGraph, and building LLM Agents for real-world AI applications. Strong Python skills with experience in deploying Gen AI apps using frameworks like FastAPI or Streamlit. Expertise in Retrieval-Augmented Generation (RAG) and working with vector databases like Pinecone, FAISS, or Chroma. Deep understanding of prompt engineering, OpenAI function calling, and chaining logic for dynamic interactions. Familiarity with cloud platforms such as Azure and AWS and deploying models to these platforms. Strong problem-solving and analytical skills with excellent communication and presentation skills. Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances

We're building an AI-first SEO Agent that acts, not just audits. Looking for a Co-Founder & CTO to lead dev, shape product, and co-invest. Equity + capital upside. Required Candidate profile Co-Founder & CMO at SEO Scientist Having 6 years of expereince in the SEO & Marketing domain Perks and benefits Remote, flexible, fast-paced, equity, real AI