218 Rag Jobs - Page 5

We are looking for an AI Engineer (Senior Software Engineer). Interested candidates email me resumes on mayura.joshi@lionbridge.com OR WhatsApp on 9987538863 Responsibilities: Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks. Implement and fine-tune models to improve response relevance and contextual accuracy. Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding. Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities. Integrate AI models with enterprise applications and APIs. Optimize model inference for performance and scalability. Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives. Ensure ethical AI implementation, addressing bias, explainability, and data security. Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques. Requirements: 8+ years experience in software development according to development standards. Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain. Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies. Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate. Solid understanding of NLP, deep learning, and transformer architectures. Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.). Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows. Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments. Strong problem-solving and debugging skills. Excellent communication and teamwork abilities Bachelors or Masters degree in computer science, AI, Machine Learning, or a related field.

Design and build production-grade Python APIs, integrate LLMs using LangChain/LangGraph, and develop backend systems. Requires 5+ yrs in backend dev, strong Python, hands-on LLM integration, and experience with async workflows and deployment.

Position overview: We are seeking an experienced Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 3 to 6 years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Bachelors or masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related field from reputed institutions. Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge – Python, SQL and commonly used frameworks & tools – PyTorch, Sci-kit, NumPy, Gen AI tools like langchain/llamaIndex Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines Interview will involve coding tests.

equired Skills & Qualifications Education & Experience: Bachelors or Master’s degree in Computer Science, Data Science, or a related field. 3–5 years of hands-on experience developing AI or data-driven applications in Python. Technical Expertise: LangChain: Proficiency in designing and implementing RAG pipelines. AWS Bedrock/ Azure OpenAI: Familiarity with integrating large language models. Pydantic: Solid understanding of data validation and configuration management. LangGraph: Experience with workflow orchestration and state management. FastAPI & React: Experience building RESTful APIs and integrating front-end frameworks. AWS: Practical knowledge of cloud deployment, CI/CD, and infrastructure management. Pinecone: Familiarity with hybrid retrieval techniques (sparse + dense), similarity search configurations, and metadata filtering. Soft Skills: Excellent problem-solving abilities and attention to detail. Strong communication skills, with the ability to explain complex AI concepts to non- technical stakeholders. A team player who thrives in a collaborative environment. Experience with Docker or Kubernetes for containerization and orchestration. Knowledge of MLOps tools and practices (e.g., MLflow, Airflow, etc.). Familiarity with other vector databases or vector search engines.

Job Description for GB5A(Dev) Primary Role Primarily responsible for working as Tech Lead i.e. leading the team and mentoring it technically. Provide hands-on technical leadership in the design, development, and deployment of generative AI models and systems. Serve as the technical point of contact for cross-functional teams, ensuring seamless collaboration between product, engineering, and data science teams. Responsibilities & KPIs Guiding the team technically and helping them solve the technical problems, throughout the project. Responsible for defining project goals, timelines, and deliverables in collaboration with stakeholders. Ensure scalability, robustness, and cost-efficiency of AI solutions. Conduct code reviews, provide constructive feedback, and ensure adherence to best practices in AI development. Build and maintain workflows to manage multiple POCs and project workloads efficiently. Collaborate with data scientists and domain experts to ensure model accuracy and relevance. Architect end-to-end Generative AI pipelines for model training, evaluation, and deployment using state-of-the-art tools and techniques Optimize AI models for speed, accuracy, and cost-efficiency. Ensure compliance with security and ethical standards. Address challenges like data drift and model degradation Proactively introduce innovative generative AI methodologies to address complex business challenges. Foster a culture of experimentation and continuous learning within the team. Ensure alignment between business goals and technical implementations. Desired Skills B.E./B.Tech degree in Computer Science, Information Science, or a related field from a leading institute preferred. Good leadership and people management skills. Excellent communication skills for translating technical concepts to non-technical stakeholders. Hands-on experience with Python Hands-on experience in machine learning, natural language processing, deep learning, and Generative AI technologies like LLM, RAG, Multi Modal architecture. Familiarity with frameworks like TensorFlow, PyTorch, Keras or Hugging Face. Familiarity with MLOps and CI/CD pipelines for AI workflows. Knowledge of cloud platforms (AWS, Azure, or GCP) for deploying AI solutions. Familiarity with current AI trends and open source technologies. Strong problem-solving and analytical skills. Ability to work on multiple projects simultaneously and manage priorities effectively. Exposure to financial services domains is a plus. Basic understanding of UI Frameworks (e.g. Angular) is a plus.

Are you ready to shape the future of AI? As a Mid-Level Generative AI Engineer at Techolution, you'll be at the forefront of innovation, fine-tuning cutting-edge LLMs like Falcon, LLaMA, and PaLM 2. Dive deep into the world of NLP, vector databases, and deep learning frameworks to create groundbreaking solutions. Your expertise in Python, PyTorch, and TensorFlow will drive the development of next-generation AI applications. Join our dynamic team and turn visionary concepts into reality, while collaborating with cross-functional experts to integrate ML solutions that redefine industries. Designation: Generative AI Engineer Location: Hyderabad, India Employment Type: Full Time Expertise: Mid-Level Key Responsibilities Develop and implement cutting-edge generative AI solutions, leveraging LLMs and RAG techniques to solve complex business challenges and drive innovation. Design and optimize AI agents that automate tasks, enhance decision-making processes, and improve overall operational efficiency across various departments. ¢ Spearhead the implementation of vector databases to efficiently store and retrieve high-dimensional data, enabling faster and more accurate AI model performance. ¢ Lead the fine-tuning of pre-trained models, adapting them to specific use cases and improving their performance on domain-specific tasks. ¢ Collaborate with cross-functional teams to integrate generative AI capabilities into existing products and services, enhancing user experiences and creating new value propositions. ¢ Conduct thorough research on emerging deep learning techniques and architectures, staying at the forefront of AI advancements and applying them to real-world problems. ¢ Develop and maintain scalable AI pipelines that streamline data processing, model training, and deployment processes, ensuring efficient and reliable AI operations. ¢ Demonstrate strong ownership by taking responsibility for end-to-end AI project lifecycles, from concept to production deployment and ongoing optimization. ¢ Cultivate a seeker mindset by continuously exploring new AI methodologies and tools, actively contributing to the team's knowledge base and fostering a culture of innovation. ¢ Showcase passion towards work by eagerly tackling complex AI challenges, pushing boundaries, and consistently delivering high-quality solutions that exceed expectations. Foundational Skills ¢ Large Language Models (LLMs): Proven expertise in working with state-of-the-art LLMs, including fine-tuning, prompt engineering, and integration into production systems. ¢ Retrieval-Augmented Generation (RAG): Demonstrated ability to implement RAG techniques to enhance AI model performance and accuracy in information retrieval tasks. ¢ Fine-tuning: Proficiency in adapting pre-trained models to specific domains and tasks, optimizing their performance for targeted applications. ¢ Vector Databases: Hands-on experience with vector databases for efficient storage and retrieval of high-dimensional data in AI applications. ¢ Deep Learning: Strong foundation in deep learning principles and architectures, with the ability to apply them to solve complex real-world problems. ¢ Generative AI: Comprehensive understanding of generative AI techniques and their practical applications in various industries. ¢ AI Agents: Experience in designing and implementing AI agents that can autonomously perform tasks and make decisions. ¢ Ownership: Demonstrated ability to take full responsibility for projects, driving them from conception to successful completion. ¢ Seeker Mindset: Proactive approach to learning and exploring new technologies, constantly seeking ways to improve and innovate. ¢ Passionate Towards Work: Genuine enthusiasm for AI and its potential to transform industries, reflected in a commitment to excellence and continuous improvement. ¢ Extremely Ambitious: Drive to push boundaries and set high goals, both personally and for the team, to achieve groundbreaking results in AI development. ¢ Ability to Comprehend: Exceptional skill in quickly grasping complex AI concepts and translating them into practical, impactful solutions. Advanced Skills ¢ Computer Vision: Familiarity with computer vision techniques and frameworks, enabling the integration of visual data processing capabilities into AI solutions. ¢ Cloud Deployment: Experience with deploying AI models and applications on cloud platforms, ensuring scalability and reliability in production environments. ¢ Leadership Experience: Prior experience in leading small teams or mentoring junior engineers, demonstrating potential for future growth into leadership roles within the AI department. How to Apply If you are passionate about leveraging AI technologies to create impactful solutions and meet the qualifications listed above, we invite you to apply for this exciting opportunity by sharing your video resume. We look forward to hearing your story and exploring how your skills align with the goals of our team. As an equal opportunity employer, Techolution celebrates diversity and is committed to creating an inclusive environment for all employees. About Techolution At Techolution, we specialize in building custom AI solutions that deliver innovation and drive measurable outcomes for enterprises worldwide. With our specialized expertise we help businesses take AI from their labs into the real world. What We Do As your one-stop shop engineering firm, Techolution guides you from ideation to ROI realization. We ensure real-world AI success by minimizing R&D risks for our clients with our innovative fixed-bid pricing model. Our Unique Value Proposition ¢ White Glove Service: From Ideation Innovation Integration, we lead the way to deliver meaningful outcomes, enabling your team to operate AI solutions independently. ¢ Human-AI Partnership: Our Govern Guide Control (GGC) framework ensures responsible AI governance, aligning solutions with your organizational requirements and brand identity. ¢ Customized AI Solutions: We tailor AI to your enterprise needs, delivering from concept to implementation with our turnkey approach at a guaranteed price. Our Impact Techolution has partnered with 300+ clients worldwide, including 50+ Fortune 500 companies. Our growing team works across diverse sectors such as healthcare, education, retail, media, tech, banking, fintech, government, telecom, and manufacturing. Celebrating 9+ years in business, we are committed to AI Done Right! Awards & Recognition ¢ 2024: Forbes publishes the best-selling book by our CEO, "Failing Fast?: The 10 Secrets to Succeed Faster." ¢ 2023: AI Solutions Provider of the Year - AI Summit ¢ 2022: Best in Business Award - Inc. Magazine ¢ 2021: Best Cloud Transformation Consulting - CIO Review ¢ 2019: Inc. 500 Fastest Growing Company Award Take a Look At Our Accelerators ¢ Enterprise LLM Studio ¢ AppMod.AI ¢ ComputerVision.AI ¢ Robotics and Edge Device Fabrication ¢ RLEF AI Platform Some Videos You Wanna Watch! ¢ About Techolution ¢ Transform Customer Service with Techolution ¢ GoogleNext 2023 ¢ Conversational AI for Enterprise ¢ Realytics AI Success Story Visit us at www.techolution.com to know more about our revolutionary core practices and how we enrich the human experience with technology.

Role & responsibilities Preferred candidate profile We're seeking a skilled Python developer with a focus on building advanced agentic applications. In this role, you'll architect and implement autonomous AI systems that can reason, plan, and execute complex tasks with minimal human intervention. Core Responsibilities Design and develop agentic AI applications using Python and modern frameworks Implement and optimize Retrieval-Augmented Generation (RAG) systems for knowledge-intensive applications Create scalable backend services using FastAPI and Django Collaborate with cross-functional teams to define agent architectures and workflows Develop testing frameworks to evaluate agent performance and reliability Document technical approaches, system architectures, and implementation details Technical Requirements Strong proficiency in Python programming and software engineering best practices Experience building web applications with FastAPI and/or Django frameworks Practical experience implementing RAG systems and understanding of vector databases Familiarity with prompt engineering techniques and LLM capabilities/limitations Knowledge of containerization, CI/CD pipelines, and deployment strategies Nice-to-Have Skills Experience with agentic frameworks like LangGraph or CrewAI Background in fine-tuning open-source models (e.g., Llama, Mistral, Falcon) Understanding of multi-agent systems and coordination protocols Experience with tools like LlamaIndex, LangChain, or similar LLM orchestration libraries Familiarity with reinforcement learning from human feedback (RLHF) Contributions to open-source AI projects Technical Environment You'll be working with cutting-edge technologies including: Python 3.x ecosystem FastAPI and Django for backend development Vector databases (e.g., Pinecone, Milvus, or Weaviate) LLM orchestration frameworks Modern cloud infrastructure (AWS/GCP/Azure) What We're Looking For Problem solvers who enjoy tackling complex technical challenges Self-motivated learners who stay current with rapidly evolving AI technologies Engineers who can balance theoretical understanding with practical implementation Strong communicators who can explain technical concepts to various stakeholders Join us to push the boundaries of what's possible with agentic AI systems and help shape the future of autonomous applications.

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

What Youll Own Full Stack Systems: Architect and build end-to-end applications using Flask, FastAPI, Node.js, React (or Next.js), and Tailwind. AI Integrations: Build and optimize pipelines involving LLMs (OpenAI, Groq, LLaMA), Whisper, TTS, embeddings, RAG, LangChain, LangGraph, and vector DBs like Pinecone/Milvus. Cloud Infrastructure: Deploy, monitor, and scale systems on AWS/GCP using EC2, S3, IAM, Lambda, Kafka, and ClickHouse. Real-time Systems: Design asynchronous workflows (Kafka, Celery, WebSockets) for voice-based agents, event tracking, or search indexing. System Orchestration: Set up scalable infra with autoscaling groups, Docker, and Kubernetes (PoC ready, if not full prod). Growth-Ready Features: Implement in-app nudges, tracking with Amplitude, AB testing, and funnel optimization. Tech Stack Youll Work With: Backend & Infrastructure Languages/Frameworks: Python (Flask, FastAPI), Node.js Databases: PostgreSQL, Redis, ClickHouse Infra: Kafka, Docker, Kubernetes, GitHub Actions, Cloudflare Cloud: AWS (EC2, S3, RDS), GCP Frontend React / Next.js, TailwindCSS, Zustand, Shadcn/UI WebGL, Three.js for 3D rendering AI/ML & Computer Vision LangChain, LangGraph, HuggingFace, OpenAI, Groq Whisper (ASR), Eleven Labs (TTS) Diffusion Models, StyleGAN, Stable Diffusion GANs, MediaPipe, ARKit/ARCore Computer Vision: Face tracking, real-time try-on, pose estimation Virtual Try-On: Face/body detection, cloth/hairstyle try-ons APIs Stripe, VAPI, Algolia, OpenAI, Amplitude Vector DB & Search Pinecone, Milvus (Zilliz), custom vector search pipelines Other Vibe Coding culture, prompt engineering, system-level optimization Must-Haves: 1+ years of experience building production-grade full-stack systems Fluency in Python and JS/TS (Node.js, React) shipping independently without handholding Deep understanding of LLM pipelines, embeddings, vector search, and retrieval-augmented generation (RAG) Experience with AR frameworks (ARKit, ARCore), 3D rendering (Three.js), and real-time computer vision (MediaPipe) Strong grasp of modern AI model architectures: Diffusion Models, GANs, AI Agent Hands-on with system debugging, performance profiling, infra cost optimization Comfort with ambiguity fast iteration, shipping prototypes, breaking things to learn faster Bonus if youve built agentic apps, AI workflows, or virtual try-ons

Develop and deploy AI-based applications leveraging LLMs and Generative AI models like GPT, Gemini, or similar frameworks Build scalable backend systems using Python, ensuring seamless integration with UI/UX components Design and optimize generative AI models to address diverse business challenges Fine-tune pre-trained LLMs to align with specific use cases Work closely with cross-functional teams, including data scientists, UI/UX developers, and product managers, to deliver robust solutions Collaborate with clients to gather requirements and develop customized AI capabilities Deploy solutions on cloud platforms (Azure, AWS, or GCP) and ensure system scalability and performance

Sr. GenAI Engineer Manager Role Overview: As a Sr. GenAI Engineer , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for business investments. You will leverage your extensive GenAI & engineering craftsmanship and advanced proficiency across multiple programming languages and modern frameworks, consistently demonstrating your exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player and mentor, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions. Key Responsibilities: Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations. Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, contributing to low-level architecture and component design, development, unit testing, integrations, and support. Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. Key Qualifications: A bachelors degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. Excellent software engineering foundation with deep understanding of OOP/OOD, sequence/activity/state/ER/DFD diagrams, data-structure, algorithms, code instrumentations, etc. 10-13 years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc. Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc. Strong understanding and experience in managing big data of various forms to generate insights and create intelligence. Proven experience with Angular, React, NodeJS, Python, Streamlit, C#, .NET Core, Golang, SQL/NoSQL. Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP. Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. to deliver high quality products rapidly. Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Role & responsibilities Generative AI, NLP & MLE: Design, develop, deploy, and scale advanced applications using Generative AI models (e.g., GPT, LLaMA, Mistral), NLP techniques, and MLE/MLOps best practices to solve business challenges and unlock new opportunities. Model Customization & Fine-Tuning: Apply techniques such as LoRA, PEFT, and fine-tuning of LLMs to build domain-specific models aligned with business use cases, with a focus on making them deployable in real-world environments. ML Engineering & Deployment: Implement end-to-end ML pipelinesincluding data preprocessing, model training, versioning, testing, and deploymentusing tools like MLflow, Docker, Kubernetes, and CI/CD practices. Innovative Problem Solving: Leverage cutting-edge AI and ML methodologies to solve practical business problems and deliver measurable results. Scalable AI Solutions: Ensure robust deployment, monitoring, and retraining of models in production environments, working closely with data engineering and platform teams. Data-Driven Insights: Conduct deep analysis of structured and unstructured data to uncover trends, guide decisions, and optimize AI models. Cross-Functional Collaboration: Partner with Consulting, Engineering, and Platform teams to integrate AI/ML solutions into broader architectures and business strategies. Client Engagement: Work directly with clients to understand requirements, present tailored AI solutions, andprovide advice on the adoption and operationalization of Generative AI and ML. Preferred candidate profile Overall 5-9 years of experience with real-time experience in GenAI and MLE/MLOps. Expertise in Generative AI: Hands-on experience in designing and deploying LLM-based solutions with frameworks such as HuggingFace, LangChain, Transformers, etc. MLE & Production Readiness: Proven experience in building ML models that are scalable, reliable, and production-ready, including exposure to MLE/MLOps workflows and tools. Deployment Tools & Best Practices : Familiarity with containerization (Docker), orchestration (Kubernetes), model tracking (MLflow), and cloud platforms (AWS/GCP/Azure) for deploying AI solutions at scale. Proficiency in development using Python frameworks (such as Django/Flask) or other similar technologies. In-depth understanding of APIs, microservices architecture, and cloud-based deployment strategies. Innovation & Curiosity: A passion for staying updated with the latest in Gen AI, LLMs, and ML engineering practices. Communication : Ability to translate complex technical concepts into business-friendly insights and recommendations

Job Title: Technology AI Engineer Location: Gurugram (Onsite) Experience: 2+ Years Budget: Open Job Overview: We are looking for a highly skilled Technology AI Engineer who is proficient in both front-end and back-end development. The ideal candidate should have hands-on experience working with Large Language Models (LLMs), AI architecture, data structures, and AI prompt engineering . The role requires expertise in building APIs , working with OpenAI, Llama, and Anthropic models , and creating scalable AI-powered applications. Key Responsibilities: Develop and optimize AI-based applications leveraging LLMs. Design and implement scalable AI architectures and data structures to support AI functionalities. Build and manage AI-driven APIs for back-end integration. Work with OpenAI, Llama, and Anthropic models to develop AI solutions. Collaborate with data scientists and AI researchers to fine-tune and deploy models. Develop secure and efficient backend services using modern frameworks. Implement front-end components to integrate AI capabilities into user interfaces. Monitor and improve the performance of AI-driven applications. Required Skills & Qualifications: 2+ years of experience in Full Stack Development (Frontend & Backend) Strong experience in AI Model Integration (OpenAI, Llama, Anthropic) Solid understanding of AI architecture and data structure development Expertise in API Development and AI-driven applications Proficiency in Python, JavaScript, or similar technologies Hands-on experience with cloud platforms (AWS, GCP, or Azure) Experience with Vector Databases and Retrieval-Augmented Generation (RAG) is a plus Strong problem-solving skills and ability to optimize AI workflows

Job Description : Data Engineer at Mirabel Technologies should be an avid programmer of Java, Python, R or Scala with expertise in implementing complex algorithms. Data Engineer will work on collecting, storing, processing, and analyzing huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them. You will also be responsible for integrating them with the architecture used across the company in various products. Skillset : 1. Proficient understanding of distributed computing principles 2. Ability to build, run and manage large clusters 3. Hadoop v2, MapReduce, HDFS 4. Java, Python 5. Large Scale crawling: Scrapy, Nutch and custom crawling solutions 6. Experience with Apache Solr Lucene 7. NoSQL databases, such as MongoDB, HBase, Cassandra 8. Knowledge of various ETL techniques and frameworks, such as Flume 9. Experience with NLP tools and systems for POS, NER, and Information extraction 10. Experience with Machine Learning - Regression, Classification, Decision Trees. 11. Experience with Linux / AWS. Experience : 4-5 years Key skills: NLP, LLM, AWS Sagemaker, Deep Learning, and No Sql Database.

About the role PubMatic is looking for engineers with expertise in Generative AI and AI agent development. You will be responsible for building and optimizing advanced AI agents that leverage the latest technologies in Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). You will work on developing state-of-the-art solutions that enhance Generative AI capabilities and enable our platform to handle complex information retrieval, contextual generation, and adaptive interactions. What You'll Do Be the decision maker for using right set of tools & technology to solve specific problems. Guide & Mentor different team members for using generative AI tools and help the teams build various agents. Provide technical leadership and mentorship to engineering teams while collaborating with architects, product managers, and UX designers to create innovative AI solutions that address complex customer challenges. Lead the design, development, and deployment of AI-driven features. Drive end-to-end ownershipfrom feasibility analysis and design specifications to execution and releasewhile ensuring quick iterations based on customer feedback in a fast-paced Agile environment. Spearhead technical design meetings and produce detailed design documents that outline scalable, secure, and robust AI architectures. Ensure that the solutions are aligned with long-term product strategy and technical roadmaps. Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the company’s offerings. Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency. We'd Love for You to Have Must Have Strong understanding of large language models (GPT, BERT, T5, etc.) and their underlying principles, including transformer architecture and attention mechanisms. Proven experience building AI agents with Retrieval-Augmented Generation to enhance model performance using external data sources (documents, databases). In-depth knowledge of vector databases, vector indexing algorithms, and experience with technologies like FAISS, Pinecone, Weaviate, or Milvus. Ability to craft complex prompts to guide the output of LLMs for specific use cases, enhancing model understanding and contextuality. Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience with data preprocessing, vectorization, and handling large-scale datasets. Ability to present complex technical ideas and results to both technical and non-technical stakeholders. Curiosity to learn new things and be up to date with market trends in Gen AI technology. Nice-to-Have Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Publication or contributions to research in AI, LLMs, or related fields. Proven record of building enterprise scale generative AI application with specific emphasis on accuracy & cost. Qualifications Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities.

AI Engineer Enterprise Agent Development Experience: 3 - 5 Years Exp Salary : INR 16-20 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 3:00PM to 12:00AM IST Opportunity Type: Remote Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : LangChain, LLM, ML Ops, AWS, Docker, Python Good to have skills : open-source, Palantir, privacy techniques, rag, Snowflake B2B SaaS (One of Uplers' Clients) is Looking for: AI Engineer Enterprise Agent Development 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 Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders whove built things that actually work at scale. Were not just rethinking how procurement analytics is done were redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams attention, no more clunky dashboards just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If youre ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If youre ready to help us build the future of procurement, analytics come join the ride. About the Role Were looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problemsthink automated research assistants, data-driven copilots, and workflow optimizers. Youll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 35 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iteratewithout sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and worklife balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: SenseCloud.ai is a procurement-focused data and AI company that offers a self-service analytics platform designed to simplify complex procurement processes. Their business model centers on providing intuitive, AI-driven tools that empower procurement professionals to derive insights without the need for IT or data science expertise. About Uplers: Our goal is to make hiring and getting hired 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!

As an AI/ML Engineer, you will be responsible for developing applications and systems that utilize AI and ML to improve performance and efficiency. Your typical day will involve working with LLMs, deep learning, neural networks, chatbots, natural language processing, and Cloud Data Architecture. Roles & Responsibilities: - Design and develop scalable and reliable AI-based applications and systems using Azure Cloud Data Architecture. - Collaborate with cross-functional teams to identify business requirements and translate them into technical solutions. - Implement and maintain AI models, including deep learning, neural networks, chatbots, and natural language processing. - Ensure AI-based applications and systems' performance, scalability, and reliability. - Stay updated with the latest advancements in AI and machine learning technologies and integrate innovative approaches for sustained competitive advantage. Professional & Technical Skills: - Must have Skills: Azure AI studio, Azure Open AI, and Cloud Data Architecture. - Must have experience in writing custom LLMs - Strong understanding of AI and machine learning technologies, including deep learning, neural networks, chatbots, and natural language processing. - Experience in designing and developing scalable and reliable AI-based applications and systems. - Experience in implementing and maintaining AI models. - Experience in ensuring AI-based applications and systems' performance, scalability, and reliability. - The candidate should have a minimum of 4 years of experience in AI/ML and cloud. - The ideal candidate will possess a strong educational background in computer science, AI, or a related field, along with a proven track record of delivering impactful AI-driven solutions.

Senior Generative AI Engineer We are seeking a highly skilled and motivated Senior Generative AI Engineer to join our growing AI team. In this role, you will be instrumental in designing, developing, fine-tuning, and deploying cutting-edge generative AI models and applications. You will work on challenging projects, leveraging state-of-the-art techniques like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal approaches to solve real-world problems. If you have a passion for building intelligent systems and staying at the forefront of AI advancements, we want to hear from you. Responsibilities : • Design, implement, and optimize sophisticated generative AI models (LLMs, diffusion models, transformers, etc.) for various applications. • Develop and refine techniques for fine-tuning pre-trained models on domain-specific datasets to enhance performance and relevance. • Implement and iterate on advanced Retrieval-Augmented Generation (RAG) systems, including selecting appropriate vector databases, optimizing embedding strategies, and refining retrieval/generation pipelines. • Engineer effective prompts and interaction strategies for maximizing the capabilities of generative models. • Process and prepare large datasets for training and fine-tuning generative models. • Evaluate model performance rigorously using appropriate metrics and benchmarks, focusing on accuracy, relevance, safety, and efficiency. • Collaborate with data scientists, software engineers, MLOps engineers, and product managers to integrate generative AI capabilities into products and services. • Optimize models and algorithms for efficient training and inference on cloud platforms (AWS, GCP, Azure). Job Opening • Contribute to the team's MLOps practices by versioning models/data, containerizing applications (e.g., Docker), and deploying models via established CI/CD pipelines. • Stay current with the latest research papers, open-source projects, and industry trends in generative AI, RAG, and related fields. • Troubleshoot and debug complex issues in AI models and systems. • Potentially mentor junior engineers and contribute to internal knowledge sharing. Qualifications : • Typically, 5+ years of professional experience in software engineering or machine learning, with at least 2-3 years of focused, hands-on experience building and implementing Generative AI models and systems. • Strong understanding of the fundamentals of deep learning, natural language processing (NLP), and machine learning principles. • Proven experience working with major generative AI model architectures (e.g., Transformers, GANs, VAEs, Diffusion Models) and foundational models (e.g., GPT series, Llama series, Stable Diffusion). • Hands-on experience with fine-tuning large pre-trained models. • Practical experience implementing RAG pipelines, including familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, ChromaDB, FAISS) and embedding techniques. • Expert-level programming skills in Python. • Proficiency with major AI/ML frameworks such as PyTorch or TensorFlow/Keras, and libraries within the ecosystem (e.g., Hugging Face Transformers, LangChain, LlamaIndex). • Experience using cloud platforms (AWS, GCP, or Azure) for developing, training, and deploying machine learning models (e.g., using services like SageMaker, Vertex AI, Azure ML). • Strong analytical and problem-solving skills. • Excellent communication and collaboration skills. Preferred Qualifications : • • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • • Experience with multimodal generative models (text-to-image, image-to-text, etc.). • • Familiarity with Reinforcement Learning from Human Feedback (RLHF) concepts or implementation. • • Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, DVC). • • Experience with distributed training frameworks (e.g., DeepSpeed, PyTorch Distributed). • • Experience deploying models into production using containerization (Docker, Kubernetes) and API frameworks (e.g., FastAPI, Flask). • • Contributions to open-source AI/ML projects or publications in relevant conferences/journals

Role & responsibilities Urgent Hiring for one of the reputed MNC Immediate joiners Only Females Bang / Pune / Hyd Exp - 4 - 12 Years Job Description: Senior Data Scientist - Multi-Agent AI Systems About the Role We are seeking an exceptional Data Scientist with specialized expertise in developing multi-agent AI systems. In this role, you will design, implement, and optimize complex AI ecosystems where multiple intelligent agents collaborate to solve sophisticated problems. You will leverage your deep understanding of generative AI, retrieval-augmented generation (RAG), and prompt engineering to create cutting-edge solutions that push the boundaries of artificial intelligence. Key Responsibilities Design and develop generative AI-based multi-agent systems that can collaborate, communicate, and coordinate to achieve complex objectives Architect and implement RAG-based chatbot solutions that effectively leverage knowledge bases and external data sources Create sophisticated prompt engineering strategies to optimize AI agent behavior and inter-agent communication Build, train, and fine-tune generative AI models for various applications within multi-agent systems Develop robust evaluation frameworks to measure and improve multi-agent system performance Implement efficient knowledge sharing mechanisms between AI agents Write clean, efficient, and well-documented Python code for production-ready AI systems Collaborate with cross-functional teams to integrate multi-agent systems into broader product ecosystems Stay at the forefront of AI research and incorporate state-of-the-art techniques into our solutions Required Qualifications Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field 4+ years of professional experience in data science or machine learning engineering Extensive experience with Python programming and related data science/ML libraries Demonstrated expertise in developing and deploying generative AI models (e.g., LLMs, diffusion models) Proven experience building RAG-based systems and implementing vector databases Strong background in prompt engineering for large language models Experience designing and implementing generative AI-based multi-agent architectures Excellent problem-solving skills and ability to optimize complex AI systems Preferred candidate profile Experience with LangChain, AutoGPT, CrewAI, or similar frameworks for building agent-based systems Familiarity with orchestration tools for managing complex AI workflows Knowledge of agent communication protocols and collaborative problem-solving frameworks Experience with distributed systems and cloud computing platforms (AWS, GCP, Azure) Contributions to open-source AI projects or research publications in relevant fields Experience with knowledge graphs and semantic reasoning systems Familiarity with MLOps practices and deployment of AI systems at scale

ZENSAR - OPPORTUNITY FOR Gen AI with Python Engineer” Apply Here: - https://forms.office.com/r/nVP0Mg5eeE Dear Aspirant, Greetings from Zensar!! We are thrilled to offer you an excellent opportunity to join our team as a Gen AI with Python Engineer professional . Experience Required: 6 - 9 Years Location: Pune, Bangalore, Chennai, Hyderabad (Hybrid) LLM Applications & Agentic Frameworks Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP. Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks. Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports. Rapidly explore and showcase the art of the possible through functional, demonstrable POCs Advanced AI Experimentation Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use. Create and leverage synthetic datasets to simulate edge cases and scale training. Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability) Evaluate emerging agent communication standards — A2A (Agent-to-Agent) and MCP (Model Context Protocol) Business Alignment & Cross-Team Collaboration Translate ambiguous requirements into structured, AI-enabled solutions. Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders Good-To-Have Microsoft Copilot Studio DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Qualifications 6–9 years of experience in software development or AI/ML engineering At least 3 years working with LLMs, GenAI applications, or agentic frameworks. Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration Proven track record of developing functional AI prototypes beyond notebooks. Strong presentation and storytelling skills to clearly convey GenAI concepts and value. Ability to independently drive AI experiments from ideation to working demo. Role & responsibilities Preferred candidate profile

Exp - 6- 10 Years Level - Senior Consultant Skill - ML OPS with Gen AI Location - Bengaluru Event on 9th May in Bangalore location Hybrid Mode (2 days WFO in a week) Education - B.Tech/B.E/MS/MBA ML OPs Engineer Required: 6-10 years of Consulting, Data, and Analytics experience Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production. Strong knowledge of Python or R Programming experience with Node.js, SQL, Java, JavaScript OR PERL Experience in cloud-based data platforms on AWS, GCP and Azure Understanding of multi-tier application architectures Ability to develop, test and maintain programming environments and architectural standards Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket) Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo Experience on code quality assessment tools and integration with CI tool Strong logical structuring and problem-solving skills Strong verbal, written and presentation skills Preferred Additional Experience in using Spark either with Scala or Python Experience with different database types like RDS and NoSQL Experience in cloud deployments Knowledge of working in a Linux environment Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS Experience in Docker /Swarm / Kubernetes Experience or exposure to Test Driven Development Experience (Junit / TestNG) Experience on Behavior Driven Development Experience (Cucumber / Selenium) Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI Experience with real time data movement solutions that use security and encryption protocols while data is in transit

Should have 5+ years of experience in GenAI. Should have experience in Python , Typescript, RAG Architecture Design, GraphRAG, Agentic Architecture, SQL, Milvus, Graph DB, Vision Models, Restful API, Fast API

Hexaware is conducting Walkin Interview for Data Scientist (GENAI)/ Lead Data Scientist (GENAI)/ Data Scientist Architect (GENAI) _Noida Location_12th April 2025 (Saturday) We urgently looking for Immediate joiners/Early joiners. Interested Candidates can share CV at umaparvathyc@hexaware.com MUST HAVE 1. Strong experience in Data Scientist (GENAI) 2. Strong hands-on experience in GenAI LLM models (ChatGPT, LLAMA 2, etc.), Vector databases, LangChain, LangGraph, and LlamaIndex, Azure/AWS, Bedrock, GPT-4. 3. Strong in python, Machine learning, deep Learning architecture, NLP, and OCR. Primary Skills Good understanding of GenAI LLM models (ChatGPT, LLAMA 2, etc.), Vector databases, LangChain, and LlamaIndex. Hands-on experience with Deep Learning architecture, NLP, and OCR. Python Fast API experience, SDA based implementations for all the APIs Architect should be hand-on to review the code developed by the developers Should be able to take and work on spike stories assigned to him/her.

Prompt Engineer Job Summary: Prompt Engineer, Gen AI, GPT 4, Python, NLP, Azure. Prompt engineers having AI and NLP AI models and Python skills Expertise in Prompt Engineering worked on GPT4 and other variants of GPT model Developing testing and refining AI generated text prompts Collaborating with content product and data teams to align prompts with the user needs Continuously improving prompt quality performance and the overall AI prompt generation process Prompt tuning in context Learning Prompt modification Python GenAI Engineer Job Summary: AI Engineer, Gen AI, NLP, Python, RAG, Azure, ML, Deep Learning AI Engineer, Python and GenAI Developed multiple products features Deep Learning, NLP, Graph analytics, Cognitive search, Image Process Automation, LangGraph and LangSmith Expertise in building services to scale the AI model capabilities Python Azure function SQL DB Cognitive search Evaluation Metrics RAGAS Advance RAG AI/ML+ RAG Engineer Job Summary: Machine Learning & NLP, RAG & Text-to-SQL, Azure Cloud, Model Optimization & Fine-Tuning, Python (LangChain, LlamaIndex),Data Analytics & SQL 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.

Primary Role Primarily responsible for working as Tech Lead i.e. leading the team and mentoring it technically. Provide hands-on technical leadership in the design, development, and deployment of generative AI models and systems. Serve as the technical point of contact for cross-functional teams, ensuring seamless collaboration between product, engineering, and data science teams. Responsibilities & KPIs Guiding the team technically and helping them solve the technical problems, throughout the project. Responsible for defining project goals, timelines, and deliverables in collaboration with stakeholders. Ensure scalability, robustness, and cost-efficiency of AI solutions. Conduct code reviews, provide constructive feedback, and ensure adherence to best practices in AI development. Build and maintain workflows to manage multiple POCs and project workloads efficiently. Collaborate with data scientists and domain experts to ensure model accuracy and relevance. Architect end-to-end Generative AI pipelines for model training, evaluation, and deployment using state-of-the-art tools and techniques Optimize AI models for speed, accuracy, and cost-efficiency. Ensure compliance with security and ethical standards. Address challenges like data drift and model degradation Proactively introduce innovative generative AI methodologies to address complex business challenges. Foster a culture of experimentation and continuous learning within the team. Ensure alignment between business goals and technical implementations. Desired Skills B.E./B.Tech degree in Computer Science, Information Science, or a related field from a leading institute preferred. Good leadership and people management skills. Excellent communication skills for translating technical concepts to non-technical stakeholders. Hands-on experience with Python Hands-on experience in machine learning, natural language processing, deep learning, and Generative AI technologies like LLM, RAG, Multi Modal architecture. Familiarity with frameworks like TensorFlow, PyTorch, Keras or Hugging Face. Familiarity with MLOps and CI/CD pipelines for AI workflows. Knowledge of cloud platforms (AWS, Azure, or GCP) for deploying AI solutions. Familiarity with current AI trends and open source technologies. Strong problem-solving and analytical skills. Ability to work on multiple projects simultaneously and manage priorities effectively. Exposure to financial services domains is a plus. Basic understanding of UI Frameworks (e.g. Angular) is a plus.