133 Langgraph Jobs - Page 2

As a skilled and visionary AI Lead at Matellio, you will be responsible for driving the development of advanced AI solutions. This dual role will require you to provide technical leadership and hands-on development expertise, making it an ideal position for individuals who excel at solving complex problems using machine learning, NLP, and LLM technologies. Your key responsibilities will include leading and mentoring a team of 45 AI/ML engineers, overseeing the entire project lifecycle from research to production deployment. You will be tasked with designing and owning high-level and low-level architecture for AI and GenAI-based applications, ensuring scalability, performance, and maintainability. Collaboration with sales and business development teams to create technical proposals, solution designs, and architecture diagrams for Sales Qualified Leads (SQLs) will also be part of your role. Additionally, you will work as an individual contributor when necessary, focusing on developing key components of solutions to accelerate delivery and establish best practices. Your responsibilities will extend to researching, designing, and implementing machine learning and deep learning models, including fine-tuning and deploying LLMs like GPT and BERT for production use cases. Building NLP pipelines and retrieval-augmented generation (RAG) systems using tools such as LangChain, LangGraph, and vector databases like FAISS, Pinecone, and Weaviate will also be crucial. You will be expected to apply statistical techniques to feature engineering, model evaluation, and performance optimization, ensuring adherence to code quality, testing, CI/CD, and documentation standards. Staying up-to-date with the latest advancements in AI/ML and proposing innovative solutions will be essential. Conducting code reviews, promoting peer learning, and fostering a strong engineering culture will also be part of your responsibilities. To qualify for this role, you should hold a Bachelors, Masters, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. Additionally, you should have at least 7 years of hands-on experience in AI/ML model development and deployment. Proven expertise in leading technical teams and delivering production-grade AI/ML solutions is required. Strong architectural skills with experience in designing end-to-end solutions involving cloud, APIs, and ML models are essential. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn is necessary, along with hands-on experience in NLP tools like HuggingFace Transformers, SpaCy, and NLTK. Practical knowledge of fine-tuning and deploying LLMs, as well as building GenAI solutions, is expected. Familiarity with tools like LangChain, LangGraph, and vector stores (e.g., FAISS, Pinecone) will be advantageous. A solid understanding of classical ML algorithms (SVM, Decision Trees, etc.) and when to utilize them, experience deploying models and services using REST APIs, Docker, and CI/CD pipelines, and exposure to cloud platforms such as AWS, GCP, or Azure are highly desirable. Excellent analytical thinking, problem-solving, and communication skills will be crucial for success in this role.,

The Senior Data Scientist - R01551342 position is for a Data Science Lead with expertise in problem formulation, OKR validation, data wrangling, data storytelling, problem solving, Excel VBA, data curiosity, technical decision making, communication & articulation, business acumen, design thinking, and data literacy. As the Agentic AI Lead, you will play a crucial role in researching, developing, and deploying semi-autonomous AI agents to address complex enterprise challenges. You will be required to leverage LangGraph, lead projects aimed at constructing multi-agent AI systems with enhanced autonomy and decision-making capabilities. The ideal candidate should possess in-depth knowledge of LLM orchestration, knowledge graphs, reinforcement learning, and real-world AI applications. You will be tasked with designing, scaling, and optimizing agentic AI workflows to align with business objectives and drive innovation in AI automation. Key Responsibilities: 1. Architecting & Scaling Agentic AI Solutions: - Design and develop multi-agent AI systems using LangGraph for workflow automation and decision-making. - Create memory-augmented AI agents capable of planning, reasoning, and executing tasks across various domains. - Implement scalable architectures for LLM-powered agents that integrate seamlessly with enterprise applications. 2. Hands-On Development & Optimization: - Develop and optimize agent orchestration workflows with LangGraph for high performance and scalability. - Use knowledge graphs and retrieval-augmented generation techniques to enhance agent reasoning. - Apply reinforcement learning methodologies for improved decision-making. 3. Driving AI Innovation & Research: - Lead AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. - Stay updated on advancements in multi-agent systems and goal-directed behavior to apply best practices in enterprise AI solutions. - Prototype self-learning AI agents for autonomous adaptation based on real-time feedback. 4. AI Strategy & Business Impact: - Translate Agentic AI capabilities into enterprise solutions for automation, efficiency, and cost savings. - Lead proof-of-concept projects to demonstrate business impact and scale successful prototypes into production. 5. Mentorship & Capability Building: - Mentor AI Engineers and Data Scientists to build expertise in LangGraph and multi-agent architectures. - Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. This role requires a strategic thinker with strong technical skills and a passion for innovation in AI technologies. The successful candidate will drive AI initiatives, lead research efforts, and mentor a team to deliver impactful solutions in a fast-paced environment.,

As a Backend Developer, your primary responsibility will be to develop and maintain backend services using Python, with a strong emphasis on FastAPI, NumPy, and Polars for efficient handling of data. You will be tasked with building and managing agentic workflows utilizing LangChain, LangGraph, and MCP Agents to facilitate dynamic, multi-step reasoning. Additionally, you will design and execute RAG pipelines for contextual information retrieval and response generation. Integration and optimization of MongoDB or similar vector databases like FAISS and Pinecone for semantic search and embedding storage will also fall under your purview. Collaboration with cross-functional teams to deploy scalable AI services in production will be a crucial part of your role. Furthermore, you will be responsible for conducting performance tuning, testing, and deployment of AI components, while also keeping abreast of the latest developments in GenAI, LLMs, and agentic architectures. The ideal candidate for this position should possess a minimum of 3-6 years of experience in backend development using Python. You should have hands-on experience with FastAPI for constructing RESTful APIs, as well as proficiency in NumPy and Polars for numerical and tabular data processing. A solid understanding of Generative AI concepts is essential, along with practical experience in working with LangChain, LangGraph, and MCP Agents. Experience in building and deploying agentic RAG systems and familiarity with MongoDB or other vector databases for semantic search and retrieval will be advantageous. Knowledge of cloud platforms such as Azure and containerization tools like Docker/Kubernetes will be considered a plus. To qualify for this role, you should hold a Bachelors or Masters degree in computer science, data science, mathematics, or a related field.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Job Title: Senior Back End Engineer Company Name: TechnoGen India Pvt. Ltd. Location: Remote (Hiring from Hyderabad, India) Job Type: Full-Time Experience Required: 5 15 years Contact Email: goutham.s@technogenindia.com Job Description: TechnoGen India is hiring a Senior Back End Engineer to join our high-performing Engineering team. You will work closely with the Head of Engineering and Product Team to develop and maintain scalable AI-based applications. Key Responsibilities: Design, develop, and maintain robust server-side logic and backend architecture. Ensure high performance and responsiveness for AI-driven platforms. Define system requirements and propose reliable solutions. Troubleshoot, debug, and optimize backend systems. Write unit and integration tests to ensure product reliability. Work with Docker, Kubernetes, and Google Cloud infrastructure. Implement and manage CI/CD pipelines using Jenkins, GitLab, or CircleCI. Stay updated with the latest trends in backend and AI technologies. Required Skills & Qualifications: 5+ years of experience in backend development, with 2+ years in a lead role. Strong proficiency in Python and backend architectural design. Experience with AI tools such as LangChain, LangGraph, LangSmith . Proficient in SQL/NoSQL databases and microservices architecture. Familiarity with CI/CD tools and public cloud platforms (especially GCP ). Work Location: Remote (India-based) Preference for candidates based in or near Hyderabad How to Apply: Send your resume to goutham.s@technogenindia.com with the subject line: Senior Back End Engineer Application

Key Responsibilities: Design and Implement RAG-Based Solutions: Lead the development of a robust RAG-based system that seamlessly integrates generative AI models with retrieval mechanisms, ensuring optimal accuracy, performance, and scalability. Agent-Based Solution Development : Build AI agents that can autonomously perform tasks using information retrieval, language models, and multi-turn interactions using AutoGen, LangGraph frameworks. Generative AI Integration : Leveraging LLMs (e.g., GPT, Anthropic, Llama, Deepseek etc.) for generating high-quality, contextually accurate content in response to user queries. Prompt Engineering: Strong proficiency in prompt engineering to design, test, and optimize prompts for large language models, ensuring effective agent behavior and task completion Data & Knowledge Integration : Work on integrating structured and unstructured data sources into the RAG framework to improve model outputs. Collaborate with Teams : Work closely with product, engineering, and data science teams to ensure seamless integration of AI capabilities into broader products. Security & Compliance : Ensure following best practices in data security, privacy, and compliance, particularly in AI-driven applications. Model Evaluation : Implement strategies for continuous evaluation, monitoring, and tuning of models to ensure high-quality outputs. Data Pipeline Design : Build robust data pipelines for preprocessing and integrating structured and unstructured data sources into the platform. Collaborate with Teams : Work closely with data engineers, and software engineers to ensure seamless integration of machine learning models into production environments. Performance Optimization : Implement and experiment with various techniques such as vector search , semantic search , and knowledge distillation to enhance the platforms efficiency and accuracy. Data Quality : Ensure data quality and consistency throughout the data pipeline, implementing necessary quality checks and validation processes. Requirements: 4+ years of experience with building GenAI solutions using Python and Langchain and AutoGen technologies. Agentic AI experienced developing agents using AutoGen and LangGraph frameworks. Prior experience in building GenAI solutions using effective text representation techniques and classification algorithms. Experience with ML – Model Building, Semantic extraction techniques, data structures and modelling Experience with Supervised/Unsupervised Learning, Sentiment Analysis, Statistical Analysis using NLP and Python libraries (NLTK, Spacy, Numpy, Pandas) Experienced in building Rest API’s Experience with building applications with micro services & serverless architecture Excellent communication skills Good to have: Experience with Azure cloud services Experience with Azure Foundry & Prompt flow

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

As a candidate applying for this position, you should be prepared to attend face-to-face interviews and be open to the opportunity. The role offers a 5-day work week based in the office. Your responsibilities will include architecting and implementing REST APIs, designing and implementing high-performance applications with low latency, integrating GenAI-powered capabilities into backend systems, testing software for responsiveness and efficiency, collaborating with front-end developers, and troubleshooting application-related issues. You will also be expected to take initiatives in building efficient solutions for scalability and work closely with the infrastructure team in triaging major incidents. Additionally, you should have experience in analyzing and researching solutions, as well as developing and implementing recommendations accordingly. To qualify for this position, you should hold a Bachelor's Degree in Computer Science or a related field, along with a minimum of 4 years of professional experience. Expertise in JavaScript (ES6) and Node JS is essential, as well as a strong understanding of algorithms and data structures. Proficiency in frameworks like Express JS and Restify is required, along with experience in building backend services for handling large-scale data. You should be able to architect high-availability applications and servers on the cloud following best practices, with a preference for microservices architecture. Experience with MySQL, NoSQL databases like DynamoDB and MongoDB, as well as GenAI agentic frameworks is advantageous. Additionally, you should have experience with complex SQL queries, Node JS concepts, technical deep-dives into code, and building and deploying GenAI-powered backend services or tools. Understanding communication through WebSockets, clean architecture, SOLID principles, AWS, Docker containerization, Python, AI-assisted development tools, and Git is beneficial for this role. If you meet these requirements and are ready to take on these responsibilities, we welcome your application for this exciting opportunity.,

Hi, Greetings from Sun Technology Integrators!! This is regarding a job opening with Sun Technology Integrators, Bangalore. Please find below the job description for your reference. Kindly let me know your interest and share your updated CV to nandinis@suntechnologies.com ASAP. Strong background in traditional AI/ML Experience building GenAI chatbots, agents, implementing tools with Gemini or similar vendors Fine tuning experience of LLMs Ability to work with LLM APIs Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs) Agentic Frameworks (e.g., LangGraph, CrewAI, ). Experience with prompt engineering Experience with RAG architecture Experience in Google Cloud and Vertex AI Experienced with Python Please let me know, if any of your friends are looking for a job change. Kindly share the references. Please Note: WFO- Work From Office (No hybrid or Work From Home) Shift Details: IST Shift - 12.30 PM to 9.30 PM IST -2 ways free cab facility(Pickup+Drop) Years of Exp-5 to 10 years Interview Mode- 2 rounds Virtual interview Thanks and Regards, Nandini S | Sr.Technical Recruiter Sun Technology Integrators Pvt. Ltd. nandinis@suntechnologies.com www.suntechnologies.com

Roles & Responsibilities GenAI Developer (5+ Years Experience) Minimum 5 years of overall experience , with at least 2 years of hands-on experience in building Generative AI (GenAI) solutions Strong working knowledge of Agentic AI frameworks , including experience in one or more of the following: LangGraph CrewAI Proven expertise in GenAI technologies , including: Python , LangChain , LangGraph , OpenAI APIs Azure Document Intelligence (ADI) Azure Service Bus Retrieval Augmented Generation (RAG) Experience in designing and implementing end-to-end GenAI applications with focus on scalability and enterprise-grade architecture Strong understanding of the Property & Casualty (P&C) Insurance domain and ability to apply GenAI solutions to relevant use cases Capable of integrating AI models with enterprise systems and APIs to build context-aware , intelligent applications Demonstrates clear communication skills , capable of working with technical and business stakeholders

Responsibilities: Generative AI Development: Design and implement solutions leveraging Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG (Retrieval-Augmented Generation) setup. Machine Learning Model Implementation: Implement machine learning models using scikit-learn and TensorFlow . AI/ML Frameworks: Utilize Hugging Face, LangChain, LangGraph, and PyTorch for AI/ML development. Cloud AI Services: Work with cloud AI services, particularly AWS SageMaker and AWS Bedrock . MLOps & DevOps: Contribute to MLOps and DevOps practices , including data pipeline setup, Apache Airflow, CI/CD , and containerization (Docker, Kubernetes) . API Development: Develop and maintain APIs following RESTful principles . System Integration: Integrate various systems using technical proficiency in Elastic, Python, YAML . Required Skills: Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup . Ability to design and implement machine learning models using scikit-learn and TensorFlow . Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch . Proficiency with cloud AI services, particularly AWS SageMaker and AWS Bedrock . Knowledge of MLOps and DevOps practices , including data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes) . Ability to develop and maintain APIs following RESTful principles . Technical proficiency in Elastic, Python, YAML , and system integrations. Nice to Have: Proficiency with Observability tools, Ansible, Terraform, Git, Microservices, AIOps , and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI .

5+ Years of experience in the design & development of state-of-the-art language models, Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Deep understanding of language models and a strong proficiency in designing and implementing RAG-based workflows to enhance content generation and information retrieval. Experience in building, customizing and fine-tuning LLMs via OpenAI studio extended through Azure OpenAI cognitive services for rapid PoCs Proven track record of successfully deploying and optimizing LLM models in cloud(AWS, Azure or GCP) for inference in production environments and proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. Apply prompt engineering techniques to design refined and contextually relevant prompts for language models. Monitor and analyse the performance of LLMs by experimenting with various prompts, evaluating results, and refining strategies accordingly. Building customizable, conversable AI agents for complex tasks using CrewAI and LangGraph to enhance Gen AI solutions Proficient in MCP(Model Context Protocol) for optimizing context-aware AI model performance and integration is a plus Basic Qualifications: Bachelors or Masters degree in computer science or a related discipline. Good communication & Interpersonal skills to interact with customers and partner teams Must be a quick learner & Self-starter who requires minimal supervision. Excellent Problem solving, Critical thinking & Analytics skills. Proficiency in english(Oral & Written)

Experience: 3+ years Location - Bengaluru Mode of work - Work from office Mode of interview - Face to Face Notice Period : Immediate joiners We are looking for a highly motivated and passionate AI/ML Engineer with a strong foundation in machine learning and hands-on project experience in Generative AI. will work on cutting-edge technologies involving Large Language Models (LLMs), Agentic AI, and toolkits like Lang Chain, Lang Graph, and Phi Data. Key Responsibilities Build, experiment with, and fine-tune Generative AI models using popular LLMs (e.g., OpenAI, LLaMA, Mistral, etc.). Develop agent-based workflows using tools such as LangChain, LangGraph, and PhiData. Create interactive and dynamic AI pipelines for tasks like summarization, Q&A, sentiment analysis, and more. Collaborate with the AI/ML team to design and deploy prototypes and PoCs. Write clean, modular Python code and maintain version control via Git/GitHub. Document projects clearly and effectively for internal and external stakeholders. Required Skills Solid understanding of Machine Learning, Deep Learning fundamentals, and model evaluation. Experience with Generative AI projects (transformers, text generation, prompt engineering, etc.). Familiarity with frameworks like LangChain, LangGraph, PhiData. Proficient in Python, along with common ML libraries (e.g., PyTorch, Hugging Face Transformers, scikit-learn). Good understanding of LLM APIs (OpenAI, Anthropic, Cohere, etc.). Strong problem-solving ability and communication skills. Active GitHub profile showcasing relevant projects is mandatory Good to Have Knowledge of REST APIs, basic backend frameworks like Flask or FastAPI. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Basic understanding of RAG (Retrieval-Augmented Generation) pipelines. Knowledge of prompt chaining and tool-calling via LLM agents. Knowledge on web application development

Prompt Engineering and its strategies Should know how LLM works and its hyper parameter ( temperature, top_p) Agentic AI framework like langchain, lang graph, crew ai RAG LLM evaluation and observability Python Deployment on any one of cloud services

NTT DATA is looking for a GCP Python Gen AI LLM RAG Vertex AI to join their team in Hyderabad, Telangana (IN-TG), India. As a part of this inclusive and forward-thinking organization, you will need to have 4+ years of Software Engineering experience or equivalent demonstrated through various means such as work experience, training, military experience, or education. The ideal candidate should have at least 2+ years of working experience with GCP (Google Cloud Platform) or alternate public/hybrid cloud, with a proven track record of delivering products at scale using cloud services and architectures. Additionally, you should possess 2+ years of experience with Python and 3+ years of experience with GenAI, LLMs, RAG, vector databases, and conversational bots. Exposure to Playbooks, Vertex AI, ADK, and Voice AI is also required. It would be beneficial to have knowledge of LangChain and/or LangGraph, and 4+ years of experience in the Contact Center industry, specifically in design, development, testing, integration with vendors, CRMs, and business applications. Proficiency in IVR/IVA, NLU/NLP, Real-Time Omni-channel Agent experience, and customer journey optimization using AI/ML is a plus. Furthermore, familiarity with Node JS, JAVA, Spring Boot, Kafka, Distributed Caches (GemFire, Redis), Elastic Search technologies, GraphQL, NoSQL Databases (Cassandra or Mongo), Graph Databases, and Public Cloud Marketplace services is desirable. Experience with Deep Domain Driven Design and cloud-native Microservices designed for massive scale and seamless resiliency on platforms like PCF/VMWare Tanzu, K8s, or Serverless cloud technologies will be an advantage. NTT DATA is a trusted global innovator of business and technology services, serving 75% of the Fortune Global 100. As a Global Top Employer, NTT DATA has diverse experts in over 50 countries and a robust partner ecosystem. Their services encompass business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is also a leading provider of digital and AI infrastructure worldwide, committed to helping clients innovate, optimize, and transform for long-term success. If you are an exceptional, innovative, and passionate individual looking to grow with a prestigious organization, apply now to be a part of NTT DATA's dynamic team.,

As a Senior Python Developer at Nirvana Solutions, you will have the opportunity to work on building and scaling our AI-driven Copilot platform. With over 6 years of experience in Python development, you will play a key role in designing, developing, and implementing modern AI techniques to enhance our investment management solutions. Your responsibilities will include building scalable Python applications, refining agentic flows and memory structures, and integrating with internal/external APIs. Collaboration with product managers, UX designers, and engineering teams will be essential in translating requirements into technical designs. You will also provide technical mentoring, conduct code reviews, and ensure code quality through automated testing and CI/CD processes. Monitoring system performance, identifying bottlenecks, and proposing improvements will be part of your role, along with staying updated on AI/ML advancements for integration into our architecture. The ideal candidate will have a strong expertise in Python and related libraries, experience with backend API frameworks like FastAPI, and hands-on experience with designing agentic or conversational AI architectures. Proficiency in RDBMS and NoSQL databases, cloud services, and containerization is required. Knowledge of modern AI/ML techniques, multi-tenant architectures, and secure API integrations is a must. Nice to have qualifications include exposure to investment management domain, experience with multi-modal/agentic systems frameworks, and familiarity with Kafka-based event-driven architectures. At Nirvana Solutions, you will have the opportunity to work in a test environment to enhance your skills, become a subject matter expert, and take product ownership for fast-paced growth. You will be exposed to the finance domain and have the chance to work directly with top leadership while implementing new technologies to delight clients. Join our close-knit competitive team environment at Nirvana Solutions in Gurugram, with a hybrid work model, industry-standard salary, and various employee benefits. Take advantage of the latest software engineering practices, friendly culture, and opportunities for personal and professional growth. Work in a dynamic environment where your contributions are recognized and valued.,

Job Title: GenAI Engineer (with Azure and GCP ecosystems) Duration: Full time role Location: Pune (Hybrid) Need someone who can join immediately OR at least in 30 days. Need someone who can join immediately OR at least in 30 days. Job description: GenAI Engineer with Azure and GCP ecosystems Skilled in Building complex GenAI solutions with high accuracy and complex use cases Skilled in Agentic platforms from procode (e.g. Autogen, Semantic Kernel, LangGraph) to Low Code (e.g. Crew.ai/EMA.ai). Skilled in Azure OpenAI and Google Vertex AI ecosystems and tooling (from training model, advance prompting, Assistant API, to agent curation). Fluent in Python, Llamaindex, Langchain, or other GenAI packages. Strong problem-solving skills and attention to details

Job Title: AI/ML Architect GenAI, LLMs & Enterprise Automation Location: Bangalore Experience: 8+ years (including 4+ years in AI/ML architecture on cloud platforms) Role Summary We are seeking an experienced AI/ML Architect to define and lead the design, development, and scaling of GenAI-driven solutions across our learning and enterprise platforms. This is a senior technical leadership role where you will work closely with the CTO and product leadership to architect intelligent systems powered by LLMs, RAG pipelines, and multi-agent orchestration. You will own the AI solution architecture end-to-endfrom model selection and training frameworks to infrastructure, automation, and observability. The ideal candidate will have deep expertise in GenAI systems and a strong grasp of production-grade deployment practices across the stack. Must-Have Skills AI/ML solution architecture experience with production-grade systems Strong background in LLM fine-tuning (SFT, LoRA, PEFT) and RAG frameworks Experience with vector databases (FAISS, Pinecone) and embedding generation Proficiency in LangChain, LangGraph , LangFlow, and prompt engineering Deep cloud experience (AWS: Bedrock, ECS, Lambda, S3, IAM) Infra automation using Terraform, CI/CD via GitHub Actions or CodePipeline Backend API architecture using FastAPI or Node.js Monitoring & observability using Langfuse, LangWatch, OpenTelemetry Python, Bash scripting, and low-code/no-code tools (e.g., n8n) Bonus Skills Hands-on with multi-agent orchestration frameworks (CrewAI, AutoGen) Experience integrating AI/chatbots into web, mobile, or LMS platforms Familiarity with enterprise security, data governance, and compliance frameworks Exposure to real-time analytics and event-driven architecture You’ll Be Responsible For Defining the AI/ML architecture strategy and roadmap Leading design and development of GenAI-powered products and services Architecting scalable, modular, and automated AI systems Driving experimentation with new models, APIs, and frameworks Ensuring robust integration between model, infra, and app layers Providing technical guidance and mentorship to engineering teams Enabling production-grade performance, monitoring, and governance

AI Engineer role is to design and implement intelligent systems using agentic AI capable of autonomous decision-making and task execution by integrating advanced machine learning models with reasoning, planning, and interaction capabilities

Short Description: Key responsibilities: 1. Product Strategy & Vision (AI/ML & Scale) 2. Technical Product Development & Execution Leadership 3. People Management & Team Leadership 4. Technical Expertise & Hands-On Contribution 5. Cross-functional Collaboration & Stakeholder Management Description: Product Strategy & Vision (AI/ML & Scale): Define and evangelize the product vision, strategy, and roadmap for our AI/ML platform, data pipelines, and scalable application infrastructure, aligning with overall company objectives. Identify market opportunities, customer needs, and technical trends to drive innovation and competitive advantage in the AI/ML and large-scale data domain. Translate complex technical challenges and opportunities into clear, actionable product requirements and specifications. Product Development & Execution Leadership: Oversee the entire product lifecycle from ideation and discovery through development, launch, and post-launch iteration for critical AI/ML and data products. Work intimately with engineering, data science, and operations teams to ensure seamless execution and delivery of high-quality, performant, and scalable solutions. Champion best practices for productionizing applications at scale and ensuring our systems can handle huge volumes of data efficiently and reliably. Define KPIs and metrics for product success, monitoring performance and iterating based on data-driven insights. People Management & Team Leadership: Lead, mentor, coach, and grow a team of Technical Product Managers, fostering a culture of innovation, accountability, and continuous improvement. Provide clear direction, set performance goals, conduct regular reviews, and support the professional development and career growth of your team members. Act as a leader and role model, promoting collaboration, open communication, and a positive team environment. Technical Expertise & Hands-On Contribution: Possess a deep understanding of the end-to-end ML lifecycle (MLOps), from data ingestion and model training to deployment, monitoring, and continuous improvement. Demonstrate strong proficiency in Google Cloud Platform (GCP) services, including but not limited to, compute, storage, networking, data processing (e.g., BigQuery, Dataflow, Dataproc), and AI/ML services (e.g., Vertex AI, Cloud AI Platform). Maintain a strong hands-on expertise level in Python programming , capable of contributing to prototypes, proof-of-concepts, data analysis, or technical investigations as needed. Extensive practical experience with leading AI frameworks and libraries, including Hugging Face for natural language processing and transformer models. Proven experience with LangGraph (or similar sophisticated agentic frameworks like LangChain, LlamaIndex), understanding their architecture and application in building intelligent, multi-step AI systems. Solid understanding of agentic frameworks, their design patterns, and how to productionize complex AI agents. Excellent exposure to GitHub and modern coding practices , including version control, pull requests, code reviews, CI/CD pipelines, and writing clean, maintainable code. Cross-functional Collaboration & Stakeholder Management: Collaborate effectively with diverse stakeholders across engineering, data science, design, sales, marketing, and executive leadership to gather requirements, communicate progress, and align strategies. Act as a bridge between technical teams and business stakeholders, translating complex technical concepts into understandable business implications and vice-versa. Responsibilities: Technical Skills: Deep expertise in Google Cloud Platform (GCP) services for data, AI/ML, and scalable infrastructure. Expert-level hands-on Python programming skills (e.g., for data manipulation, scripting, API interaction, ML prototyping, productionizing) Strong working knowledge of Hugging Face libraries and ecosystem. Direct experience with LangGraph and/or other advanced agentic frameworks (e.g., LangChain, LlamaIndex) for building intelligent systems. Solid understanding of software development lifecycle, GitHub , Git workflows, and modern coding practices (CI/CD, testing, code quality). Qualifications: Education: Bachelors or Master’s degree in Computer Science, Engineering, or a related technical field. Experience: 8+ years of progressive experience in technical product management roles, with a significant portion focused on AI/ML, data platforms, or highly scalable systems. 3+ years of direct people management experience, leading and mentoring a team of product managers or technical leads. Demonstrable track record of successfully bringing complex technical products from concept to production at scale. Proven ability to manage products that handle massive volumes of data and require high throughput. Extensive practical experience with AI/ML model deployment and MLOps best practices in a production environment. Leadership & Soft Skills: Exceptional leadership, communication, and interpersonal skills, with the ability to inspire and motivate a team. Strong analytical and problem-solving abilities, with a data-driven approach to decision-making. Ability to thrive in a fast-paced, ambiguous, and rapidly evolving technical environment. Excellent ability to articulate complex technical concepts to both technical and non-technical audiences.

Job Title: Python, Machine Learning & GenAI Specialist Company: Tekskills Location: Bengaluru, India Contact: shailender.b@tekskills.in Job Summary We are seeking a dynamic and experienced professional with 5+ years of hands-on expertise in Python, Machine Learning, and advanced experience in Deep Learning and Generative AI (GenAI) . This role is ideal for candidates passionate about solving complex problems, driving innovation, and implementing next-gen AI solutions for real-world applications. Key Responsibilities Design, develop, and deploy robust solutions leveraging Core Python , standard libraries, and frameworks. Build and optimize end-to-end machine learning and deep learning models for production use. Architect and implement GenAI-powered applications utilizing: Vector Databases, Langchain, Langgraph, RAG, and MCP. Integrate external data sources and APIs, and build scalable pipelines for AI model deployment. Collaborate with internal teams to translate business requirements into cutting-edge AI features. Conduct model evaluations, fine-tuning, and support ongoing model monitoring. Mentor and guide team members and contribute to best practices within the AI community. Required Skills & Qualifications Minimum 5 years of professional experience in Python development, with a focus on machine learning and deep learning. Strong understanding of core ML concepts , with proven project delivery using frameworks such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience in deep learning (CNNs, RNNs, LLMs/Transformers, or similar architectures). Demonstrable expertise in GenAI tools (Vector Databases, Langchain, Langgraph, Retrieval Augmented Generation (RAG), MCP). Introductory knowledge of AI Agents and their integration in larger workflows. Solid understanding of model deployment, API integration, version control, and containerization. Excellent communication, problem-solving skills, and a collaborative mindset. Preferred Qualifications Experience deploying AI/ML solutions in production at scale. Familiarity with cloud AI services (AWS Sagemaker, Azure ML, GCP, etc.). Exposure to LLM fine-tuning, prompt engineering, or knowledge of autonomous agent systems. How to Apply Interested candidates should submit their CV to shailender.b@tekskills.in with the subject line: Application for Python, Machine Learning & GenAI Specialist Bengaluru Join our innovative team at Tekskills and transform the future of AI-driven solutions!

NTT DATA is looking for a GCP Python Gen AI LLM RAG Vertex AI to join their team in Hyderabad, Telangana, India. As a potential candidate, you should have at least 4 years of Software Engineering experience or equivalent demonstrated through various means such as work experience, training, military experience, or education. It is essential to have a minimum of 2 years of experience working with GCP (Google Cloud Platform) or alternate public/hybrid cloud, delivering products with cloud services and cloud architectures at scale. In addition, you should have 2+ years of experience with Python and 3+ years of experience with GenAI, LLMs, RAG, vector databases, and conversational bots. Furthermore, 1+ years of experience with Playbooks and Vertex AI is required for this role. Exposure to ADK (hands-on) and Voice AI is a must. While not mandatory, having experience with LangChain and/or LangGraph is considered a plus. Additionally, 4+ years of Contact Center industry experience would be advantageous, including design, development, testing, integration with vendors, CRMs, and business applications. Proven knowledge in contact center subdomains such as IVR/IVA, NLU/NLP, Real-Time Omni-channel Agent experience, customer journey, and CX/AX experience optimization using AI/ML is beneficial. Moreover, familiarity with Node JS, JAVA, Spring Boot, Kafka, Distributed Caches (GemFire, Redis), Elastic Search technologies, GraphQL, and NoSQL Databases (Cassandra or Mongo), Graph Databases, Public Cloud Marketplace services is a good-to-have skill set. Experience with Deep Domain Driven Design with cloud-native Microservices designed and developed for massive scale and seamless resiliency, deployed on PCF/VMWare Tanzu, K8s, or Serverless cloud technologies for at least 2 years is also an added advantage. NTT DATA is a trusted global innovator of business and technology services, with a commitment to helping clients innovate, optimize, and transform for long-term success. Being a part of NTT DATA means being part of a diverse team of experts in over 50 countries, with a robust partner ecosystem. Their services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is a leading provider of digital and AI infrastructure globally, and as part of the NTT Group, they invest significantly in R&D to help organizations and society move confidently and sustainably into the digital future. Visit their website for more information.,

The company Flentas specializes in assisting enterprises in maximizing the benefits of the Cloud through their consulting and implementation practice. With a team of experienced Solution Architects and Technology Enthusiasts, Flentas is dedicated to driving significant digital transformation projects and expanding cloud operations for clients worldwide. As a Generative AI Specialist at Flentas, based in Pune, you will be responsible for implementing and optimizing cutting-edge AI solutions. Your role will involve utilizing LangChain, LangGraph, and agentic frameworks, along with hands-on experience in Python and cloud-based AI services such as AWS Bedrock and SageMaker. Additionally, experience in fine-tuning models will be advantageous as you collaborate with the team to develop, deploy, and enhance AI-driven applications. Key Responsibilities: - Designing, developing, and implementing AI solutions using LangChain, LangGraph, and agentic frameworks. - Creating and maintaining scalable AI models utilizing AWS Bedrock and SageMaker. - Building and deploying AI-driven agents capable of autonomous decision-making and task execution. - Optimizing machine learning pipelines and workflows for production environments. - Collaborating with cross-functional teams to understand project requirements and deliver innovative AI solutions. - Conducting fine-tuning and customization of generative AI models (preferred skill). - Monitoring, evaluating, and improving the performance of AI systems. - Staying updated on the latest advancements in generative AI and related technologies. Required Skills: - Proficiency in LangChain, LangGraph, and agentic frameworks. - Strong programming skills in Python. - Experience with AWS Bedrock and SageMaker for AI model deployment. - Knowledge of AI and ML workflows, including model optimization and scalability. - Understanding of APIs, data integration, and AI-driven task automation. Preferred Skills (Good To Have): - Experience with fine-tuning generative AI models. - Familiarity with cloud-based architecture and services beyond AWS (e.g., GCP, Azure). - Knowledge of advanced NLP and transformer-based architectures. Qualifications: - Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field. - 3-5 years of hands-on experience in AI development, focusing on generative models. - Demonstrated experience in deploying AI solutions in a cloud environment.,

Deliver genAI features, AI Agents and Product Infra features e2e on AWS or Azure Cloud Demonstrate resilience in driving past rigorous test cycles to verify success of genAI features. Leverage Copilot/Cursor to maximize efficiency in dev cycle Required Candidate profile 5+ y SW dev. in Python, AWS or Azure 1+ y - LLM APIs, Prompt Eng, RAG, Self Learning AI Agents, Embeddings, Vector DBs, Langgraph, Langchain (Desirable) Exp in NLP, AI/ML FWs: TensorFlow, SageMaker

Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 2 to 8 years of experience in full stack software engineering. Proven experience in building AI chatbots and deploying Agentic AI solutions. Hands-on experience with Retrieval-Augmented Generation (RAG) techniques. Proficient in programming languages such as Python, JavaScript, or similar. Experience with AI frameworks and tools such as LangChain, LlamaIndex, LangGraph, MS Autogen2, Google ADK, PydanticAI, crewAI or similar. Strong understanding of front-end technologies like React, Angular, or Vue.js. Strong understanding of backend-end technologies like FastAPI, Flask, Django etc Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Excellent problem-solving skills and attention to detail. Preferred Qualifications: Experience in agile development methodologies. Knowledge of machine learning algorithms and data structures. Strong communication and collaboration skills. Ability to work in a fast-paced, dynamic environment.