633 Gen Ai Jobs - Page 9

Fine-tune diffusion models to enhance image quality, resolution, and style adaptability. Optimize prompt engineering techniques to refine and control image generation outputs. Develop post-processing and ranking algorithms to improve the accuracy and aesthetics of generated images. Integrate diffusion models with other AI techniques, including GANs, transformers, and hypernetworks, to expand generative capabilities. Deploy AI models into production environments, ensuring scalability and efficiency. Utilize containerization tools (Docker, Kubernetes, etc.) to streamline AI model deployment. Collaborate with AI researchers and product teams to bring AI-powered image generation solutions into real-world applications. BTech/MTech/MS in Computer Science, AI, or a related field. 2+ years of experience working with Generative AI and Computer Vision. Strong expertise in diffusion models, generative AI, and image processing. Hands-on experience with model fine-tuning and optimization. Understanding of ControlNets, hypernetworks, and AI-based prompt engineering. Proven track record in AI model deployment and scalable pipelines. Experience working with production-grade AI workflows and cloud-based solutions. Strong debugging skills Ability to troubleshoot model failures and optimize performance. Team player mindset Comfortable working with cross-functional teams. Excellent communication & presentation skills Ability to explain research concepts clearly. Comfortable working in a high-performance, in-office environment. Takes ownership from Day 1, proactively solving challenges.

Lead GenAI Delivery Experience :10_12 years Location : Bangalore, Pune, Noida, Gurugram We are looking for a dynamic and experienced Pod Lead to manage the delivery and execution of GenAI projects for our key clients. The role requires strong project management, client interaction, and team leadership capabilities to ensure high-quality, timely, and value-driven AI solutions. Experience Required: 8-12 years ( with at least 2-3 years in leading AI/Analytics/Technology project teams, preferably in the insurance domain ) Role Overview: We are looking for a capable and experienced Pod Lead to manage the delivery and execution of GenAI projects for our strategic insurance clients. This role will lead a cross-functional pod of engineers, product managers, and QA resources to ensure high-quality, timely, and business-aligned AI solutions. Key Responsibilities: Own and drive end-to-end GenAI project deliveries within the assigned pod Work closely with internal stakeholders, product teams, and technical leads to define project goals and execution plans Act as the primary delivery contact for the pod, ensuring timelines, quality, and value delivery Lead and mentor a cross-functional team including GenAI engineers, QA, and other contributors Track KPIs, manage project milestones, and ensure alignment with broader AI team objectives Promote reuse of platform tools and maintain compliance with AI governance practices Facilitate regular reviews, risk management, and stakeholder updates Identify blockers early and help in resource planning and backlog prioritization Required Skills & Qualifications: 10-12 years of total experience with strong delivery management in enterprise tech or AI projects Proven experience in managing AI/ML/GenAI initiatives and cross-functional teams Exposure to the insurance industry (underwriting, claims, finance, or operations) is highly desirable Strong stakeholder communication and project tracking skills Comfortable working in Agile/Scrum environments with cross-region teams Ability to convert complex business requirements into actionable delivery plans

Automation Business Consultant Job Description: As a Business Analyst for Gen AI, you will play a crucial role in bridging the gap between business needs and technological solutions. You will work with cross-functional teams to identify opportunities where artificial intelligence and data-driven insights can enhance business processes and decision-making. Your primary responsibilities will include: Responsibilities : Collaborate with business stakeholders to gather and document requirements for AIdriven projects and initiatives. Analyze and interpret data to extract actionable insights and identify opportunities for AI integration. Work with data scientists and developers to design AI and machine learning solutions that align with business goals. Manage and oversee AI projects from conception to implementation, ensuring timely delivery and meeting project objectives. Establish and enforce data governance best practices to ensure data quality and compliance with regulations. Identify inefficiencies in current business processes and propose AI-driven improvements. • Communicate project progress and findings to stakeholders, including non-technical team members. Create comprehensive documentation of project requirements, processes, and outcomes. Conduct testing and validation of AI models to ensure accuracy and reliability. Stay updated with industry trends and advancements in AI and data analytics to suggest innovative solutions. Skillset Requirements: Proficiency in data analysis tools and techniques, including data visualization and statistical analysis. Strong understanding of AI and machine learning concepts and their practical applications. Excellent verbal and written communication skills to bridge the gap between technical and non-technical stakeholders. Experience in project management methodologies and tools. Familiarity with programming languages such as Python, and data manipulation libraries (e.g., Pandas). Understanding of the specific industry or domain in which the AI solutions will be implemented. Strong problem-solving skills to identify business challenges and propose AI-driven solutions. Ability to adapt to rapidly changing technology and business environments. Knowledge of ethical considerations related to AI and data privacy. Collaborative mindset to work effectively with cross-functional teams. Understanding of business operations, objectives, and strategies. Education and Experience: Bachelor's degree in a relevant field (e.g., Business, Computer Science, Data Science). Previous experience as a Business Analyst or similar role, preferably in AI or data-driven projects. Relevant certifications in AI, data analysis, or project management (e.g., CBAP, PMP, AI-related certifications). This job description and skillset requirements provide a comprehensive overview of the role of a Business Analyst for Gen AI, highlighting the key responsibilities and qualifications needed for success in this position. Tailor it to your specific organization's needs and requirements as necessary.

Role and Responsibilities Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation Develop backend APIs and services using Python frameworks like FastAPI or Flask Contribute to scalable microservice-based architectures Requirements Bachelor's degree in Computer Science, Information Technology, or a related field. 2 to 4 years in AI/ML development and backend system Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines SQL/NoSQL: Experience in querying and managing structured and unstructured data Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing Soft Skills: Strong problem-solving, communication, and collaboration abilities Good-to-Have Skills: Agentic AI Tools: Exposure to CrewAI or similar platforms for orchestrating multi-agent interactions Content Structuring: Experience in clustering, topic modeling, or organizing unstructured data ETL Enhancements: Advanced optimization techniques for faster and more efficient pipelines Domain Exposure: Prior work on projects involving customer insights, chat summarization, or sentiment analysis Role & responsibilities

AVIZVA is a Healthcare Technology Organization dedicated to simplifying, accelerating, and optimizing the way healthcare enterprises deliver care. Since its establishment in 2011, AVIZVA has been a key strategic enabler for healthcare enterprises, enhancing their overall care delivery through tailored products and services. With over 13 years of expertise, AVIZVA has successfully engineered more than 150 products for leading Medical Health Plans, Dental and Vision Plan Providers, PBMs, Medicare Plan Providers, TPAs, and other healthcare entities. As an Associate Manager - Applied Machine Learning at AVIZVA, you will play a crucial role in architecting, designing, and developing advanced GenAI products and services. This position requires a strong technical background in machine learning coupled with leadership skills to drive the team towards success. Your responsibilities will include contributing to the development of Large Language Model (LLM) based products, integrating GenAI and traditional machine learning approaches to meet key product requirements. Collaboration with cross-functional teams, such as product managers and business leaders, will be essential to deliver scalable machine-learning solutions that align with business needs. Your role will involve setting clear goals and priorities for the team, overseeing the lifecycle of GenAI projects, addressing technical and operational challenges, and ensuring seamless deployment of models into production environments. Embracing a culture of continuous improvement, you will lead the team in delivering high-quality results while maintaining a collaborative work environment. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science or a related analytical field. A minimum of one year of experience in Gen AI, Agentic AI, and Large Language Models (LLMs) is required, along with hands-on experience in building RAG (Retrieval Augmented Generation) pipelines. Proficiency in NLP, NLG, Text Analytics, and working with Transformer-based models like BERT is essential. Additionally, you should have over 10 years of experience as an Applied Machine Learning Engineer or Data Scientist, with expertise in Python, system design, and architecture. Your technical skills should encompass a strong command of Core Python, advanced Python libraries like PyTorch and FAST API, as well as experience with classification and clustering algorithms, ensemble models, and object-oriented programming. Familiarity with ORM tools, debugging, testing frameworks, front-end fundamentals, and Agile methodology will be beneficial for the role. Excellent communication and problem-solving skills are also key attributes for success in this position.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. Your unique voice and perspective are essential to help EY become even better. Join us to build an exceptional experience for yourself and contribute to creating a better working world for all. We are seeking individuals with strong Power Platform skills who are eager to learn new technologies in the process automation space such as RPA, AI/ML, Cognitive, Conversational Chat, and Gen AI. The ideal candidate should have a minimum of 3-5 years of relevant experience, with at least 3+ years of hands-on experience on Power Platform. You should have a detailed understanding of canvas apps, model-driven apps, power pages, power automate digital flows, and power automate desktop. Additionally, basic knowledge of Power BI, Power Virtual Agents, AI concepts using AI Builder and Co-Pilot, Dataverse, environment management, and database systems like SQL or Oracle is required. Your responsibilities will include interfacing with Architects and customers to understand business processes and system requirements, independently architecting and designing Power platform solutions, leading a development team, and providing technical support during engagement delivery. You should also have experience in developing solutions using automation technologies like Power Platform, AI/ML, and RPA. A certification as a PL 600 Solution Architect in Power Platform is preferred. We are looking for individuals who can mentor junior developers, have hands-on experience with Power Platform implementations, possess deep knowledge of Agile methodologies, and have experience working with JSON, XML, RESTful APIs, and object-oriented programming languages like C#, Java, or .NET full stack. Familiarity with external integrations and knowledge of RPA and DevOps tooling would be advantageous. Excellent written and verbal communication skills are a must, along with the ability to write clear and understandable logic for maintainable code. As part of our team, you will work with professionals who have commercial acumen, technical expertise, and a willingness to learn in a fast-paced environment. You will have the opportunity to collaborate with a market-leading, multi-disciplinary team and work with EY Advisory practices globally across various industries. Working at EY offers you inspiring and meaningful projects, educational opportunities, individual progression plans, challenging assignments, and an interdisciplinary environment that promotes high quality and knowledge exchange. You will receive support, coaching, and feedback from engaging colleagues, opportunities to develop new skills, and the freedom to handle your role in a way that suits you best. EY is dedicated to building a better working world by creating long-term value for clients, people, and society while fostering trust in the capital markets. Our diverse teams globally provide assurance and help clients grow, transform, and operate by asking better questions to find new answers to the complex issues facing the world today.,

Job Role & responsibilities:- Architectural Design: Develop a strategic and comprehensive automation landscape design with a mindset of end-to-end solutions that are robust, scalable, and aligned with industry best practices. • Ensure that solutions consider factors like performance, security, and data integrity. • Create comprehensive solution architecture plans that outline the technical components, integration points, and data flows required for successful automation. Architectural Roadmap and Documentation: • Develop and maintain a comprehensive technology roadmap that aligns with the organization's long-term business goals. Ensure that technology decisions and solutions fit into the strategic technology vision. • Create and maintain detailed technical documentation, including architecture diagrams, design specifications, and process workflows. Technology Selection: • Identify and recommend the most suitable automation technologies and tools, such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) considering existing automation capabilities Prototyping: • Develop prototypes and proof-of-concepts to validate the feasibility and functionality of proposed automation solutions. Integration: Define integration strategies to ensure seamless connectivity between automation solutions and existing business applications and data sources Compliance and Security: • Ensure that automation solutions adhere to industry standards, data security, and compliance requirements Scalability and Performance: • Design solutions that are scalable and capable of handling increasing workloads while maintaining optimal performance. Technical Leadership & Collaboration: • Provide technical leadership and guidance to development teams during the implementation phase, addressing any architectural concerns and ensuring adherence to architectural designs. • Collaborate with cross-functional teams, including developers, data scientists, and business analysts, to understand their automation requirements and design automation solutions that align with business objectives and allow to execute automation projects. Stakeholder Communication: • Effectively communicate complex technical concepts to non-technical stakeholders and align automation solutions with business goals. Training and Knowledge Transfer: • Support end-users and internal teams in adopting and understanding intelligent automation technologies. Technical Skills & Experience & Qualification required:- Bachelors degree in computer science, Information Technology, or a related field (Master's degree preferred). 14+ years of experience as a Solution Architect with a strong focus on intelligent automation. In-depth knowledge of automation technologies, including RPA, AI, ML, and NLP. Strong understanding of software architecture and design principles. Proficiency in system integration and API management. Experience with data security, compliance, and risk management. Excellent analytical and problem-solving skills. Strong communication and interpersonal skills. Project management experience and familiarity with project methodologies (e.g., Agile, Scrum). Experience in cloud-based architecture and DevOps practices. Certification in relevant automation technologies (e.g., TOGAF, AWS Solution Architect, UiPath, Automation Anywhere) and experience in designing automation solutions for specific industries, such as insurance, finance are a plus Immediate joiners will be preferred only who can join us in July Month

Job Description We are seeking a Senior Software Engineer to lead and guide our engineering team in building and enhancing our internal AI Gateway platform. This platform empowers internal organizations to create and deploy AI use cases, integrating with Azure OpenAI, AWS Bedrock, Databricks, and other cloud platforms. You will drive architecture, design, and implementation of scalable data/model management pipelines, agentic AI, RAGs, tracing, and MCP server components. Essential to have hands on Development experience in Python JavaScript, TypeScript, Node JS Essential to have hands on experience in building scalable GenAI applications leveraging LLMs e.g. GPT, Claude, Anthropic using various techniques e.g. RAG, Agentic AI etc. Preferred experience in Developing GenAI Solutions using frameworks e.g. Langchain, LlamaIndex. Preferred experience in building AI pipelines for interaction via Chatbots, User Interface, Autonomous Agents. Must have excellent communication skills to understand complex AI concepts & work with architects to build the solution as well as the ability to explain it to Nontechnical Stakeholders. Preferred experience of deploying solutions on AWS with best, practices. Good to have built capabilities in GenAI backed by evaluation (any existing framework for evaluation or custom built for the specific use case).Contributions to AI research, opensource models or AI hackathons are a plus. Responsib0ilities: Lead the design and development of the AI Gateway platform and its integrations (Azure OpenAI, AWS Bedrock, Databricks, etc.). Architect and implement scalable, secure, and maintainable data/model management pipelines. Guide the team in building agentic AI, RAG (Retrieval-Augmented Generation), tracing, and MCP server solutions. Mentor and upskill team members, conduct code reviews, and enforce best practices. Collaborate with product, DevOps, and data science teams to deliver robust solutions. Drive automation and CI/CD for model and data pipeline deployments. Ensure platform reliability, observability, and security. Requirements: 7+ years of software engineering experience, with at least 2 years in a technical leadership role. Strong Python (FastAPI, asyncio), cloud (Azure, AWS), and data engineering skills. Experience with LLMs, agentic AI, RAGs, and orchestration frameworks. Hands-on with cloud ML services (Azure OpenAI, AWS Bedrock, Databricks). Familiarity with CI/CD, Docker, Kubernetes, and infrastructure-as-code.

Key Responsibilities: Design, develop, and deploy scalable full-stack applications integrating Gen AI capabilities. Build front-end interfaces using modern JavaScript frameworks (e.g., React,). Develop robust back-end APIs and services in Python (FastAPI/Django/Flask). Integrate Azure OpenAI, Cognitive Services, and other Azure AI tools into solutions. Collaborate with cross-functional teams for data pipelines, prompt engineering, and LLM optimization. Ensure application performance, security, and scalability in a cloud environment. Must-Have Skills: Front-End: HTML, CSS, JavaScript/TypeScript, React.js or similar. Back-End: Python, FastAPI/Django/Flask, RESTful APIs. Gen AI Stack: Experience with Azure OpenAI, Prompt Engineering, LangChain/RAG pipelines. Cloud & DevOps: Azure Functions, Azure Storage, Azure Cognitive Services, Git, CI/CD. Database: SQL (PostgreSQL/MySQL), NoSQL (MongoDB/Cosmos DB).

Role & rJob Title: Senior Machine Learning Engineer Anomaly Detection & Time Series Forecasting Location: Bangalore Department: Engineering – AI/ML Job Overview: Resolve Tech Solutions is seeking an experienced Senior Machine Learning Engineer to drive the development of AI-driven anomaly detection, time series forecasting, and predictive analytics models for our next-generation observability platform. This role will focus on designing, building, and deploying ML models that provide real-time insights, predictive alerts, and intelligent recommendations powered by LLMs. As a key individual contributor, you will work on solving complex challenges in large-scale cloud environments while collaborating with cross-functional teams. Key Responsibilities: Develop Advanced ML Models: Design and implement machine learning models for anomaly detection, time series forecasting, and predictive analytics, ensuring high accuracy and scalability. Anomaly Detection & Root Cause Analysis: Build robust models to detect abnormal patterns in metric data, leveraging statistical methods, deep learning, and AI-driven techniques. Time Series Forecasting: Implement predictive models to forecast metric trends, proactively identifying threshold breaches and alerting users. LLM-Driven Insights: Utilize Large Language Models (LLMs) to analyze historical incidents, correlate anomalies, and provide recommendations by integrating with ITSM platforms like ServiceNow. Cloud & Big Data Integration: Work with large-scale data pipelines, integrating ML models with cloud platforms such as AWS, Azure, and GCP. Feature Engineering & Data Processing: Design and optimize feature extraction and data preprocessing pipelines for real-time and batch processing. Model Deployment & Optimization: Deploy ML models in production environments using MLOps best practices, ensuring efficiency, scalability, and reliability. Performance Monitoring & Continuous Improvement: Establish key performance metrics, monitor model drift, and implement retraining mechanisms for continuous model improvement. Collaboration & Knowledge Sharing: Work closely with product managers, data engineers, and DevOps teams to align ML solutions with business objectives and platform goals. Requirements: Experience: 5+ years of hands-on experience in machine learning, with a strong focus on anomaly detection, time series forecasting, and deep learning. ML & AI Expertise: Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, and XGBoost. Anomaly Detection: Experience with statistical techniques, autoencoders, GANs, or isolation forests for anomaly detection in time series data. Time Series Forecasting: Strong background in models such as ARIMA, Prophet, LSTMs, or Transformers for predictive analytics. LLMs & NLP: Hands-on experience in fine-tuning and integrating LLMs for intelligent insights and automated issue resolution. Cloud & Data Engineering: Familiarity with cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI) and distributed computing frameworks like Spark. MLOps & Deployment: Experience with CI/CD pipelines, Docker, Kubernetes, and model monitoring in production. Problem-Solving & Analytical Skills: Ability to analyze large datasets, derive insights, and build scalable ML solutions for enterprise applications. Communication & Collaboration: Strong verbal and written communication skills, with the ability to explain ML concepts to non-technical stakeholders. Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field. Preferred Qualifications: Experience with AIOps, observability, or IT operations analytics. Hands-on experience with reinforcement learning or graph neural networks. Familiarity with Apache Kafka, Flink, or other real-time data processing frameworks. Contributions to open-source ML projects or research publications in anomaly detection and time series analysis. Why Join Us? Opportunity to work on cutting-edge AI/ML solutions for enterprise observability. Collaborative and innovative work environment with top AI/ML talent. Competitive salary, benefits, and career growth opportunities. Exposure to large-scale, cloud-native, and AI-driven technologies. If you are passionate about AI-driven anomaly detection, time series forecasting, and leveraging LLMs for real-world enterprise solutions, we'd love to hear from you!esponsibilities Preferred candidate profile

About the job We are looking for a Product Manager with a strong track record of building product roadmaps having been involved from idea inception to go-live , with multiple iterations of product enhancements. Prior experience in creating both web and mobile interfaces for AI / Gen AI / Automation based products is required. The job entails working with cross-functional teams , including user cohorts , business leadership and technical development teams (both in-house and third-party). Job Responsibilities Define, manage, and execute a comprehensive product roadmap Ensure alignment with client/user requirements , business strategy , and emerging market trends Proven track record in driving product strategy and execution , delivering innovative solutions Create detailed BRD and FRD by working closely with internal teams and external stakeholders Lead the entire product lifecycle from ideation to launch to ongoing optimization Gather and analyze business and user requirements to drive product direction and development Actively interact with business and user cohorts to gather requirements, validate solutions, and ensure alignment with evolving needs Enhance user experience (UX) by continuously improving product feature based on feedback and data-driven insights Oversee cross-functional teams to drive development, prioritize features, and ensure timely delivery Stay updated on the latest AI/ML/RPA/Gen AI trends, tools, and frameworks, and apply them where relevant Work with Product Marketing to feature platforms and new features in various channels, and also for positioning comparative product features in user-review sites like G2, Capterra etc. Keep up to date with the latest AI/ML/RPA/Gen AI trends, tools, and frameworks, and apply them where relevant to drive innovation. Qualifications: 3-5 years of experience in product management, preferably with exposure to creating web and mobile interfaces for AI / Gen AI / Automation based products Proven track record of managing B2B products from ideation to launch and scaling scaling Experience in product feature prioritization frameworks especially those that measure commercial impact of feature sets being developed Strong experience in writing BRDs/FRDs and defining technical and functional requirements Demonstrated ability to manage the end-to-end product lifecycle effectively Excellent S Excellent Stakeholder management and communication skills Prior knowledge of AI and Gen AI tools/frameworks would be a preferred

Core Responsibilities: Deliver high-quality, scalable features using Python, Django, DRF Develop and deploy Generative AI and LLM-based applications Work with frameworks like LangChain, LangGraph , and AI agents Design and manage RESTful APIs, CI/CD pipelines, and containerized deployments Collaborate with cross-functional teams including product managers and architects Participate in agile ceremonies Scrum, sprint planning, and code reviews Write unit tests, automate testing, and ensure performance/security standards are met Work on data engineering tasks involving SQL, NoSQL, Kafka, Redis, etc. Contribute to data governance , privacy, and security compliance Required Skills & Technologies: Proficiency in Python/Django , Django Rest Framework Solid experience in RDBMS (Oracle, MySQL, PostgreSQL, HANA) Strong UI understanding: React , Angular, HTML, CSS Tools: Git, Jenkins, Docker, Kibana, Kubernetes Familiarity with test automation and TDD/BDD principles Experience with Big Data , Kafka , Redis , data security/privacy protocols Generative AI concepts: LLMs, embeddings, fine-tuning, agent orchestration Qualifications: B.E./B.Tech / M.Tech / MCA from a reputed institute (minimum 65% throughout) 4–6 years of experience in backend development and/or AI-driven applications Experience working on SaaS multi-tenant platforms is a plus Excellent communication & collaboration skills Strong attention to detail and quick learning ability

Role: Business Analyst AI-Based Solutions Experience: 2–4 Years Work Mode: Hybrid Key Responsibilities: Gather and analyze business requirements for AI-powered and data-driven projects. Collaborate with cross-functional teams including Product, Engineering, and Data Science to define and refine solutions. Work closely on AI/ML model implementation, validating outputs with stakeholders. Translate business needs into BRDs, user stories, and process flows. Conduct data analysis using Excel, SQL, or Power BI to derive actionable insights. Drive end-to-end project delivery using Agile methodologies and project tracking tools like JIRA. Communicate effectively with business users, tech teams, and leadership to ensure solution alignment. Preferred Qualifications: 2–3 years of experience as a Business Analyst, preferably in a tech-first or AI-led environment . Exposure to AI-based tools or projects (OCR, ML models, intelligent automation). Experience with data visualization (Power BI, Tableau), analytics tools, and Excel. Strong documentation skills (BRD, FRD, UAT scripts). Familiarity with Python or SQL is a plus.

Responsibilities : * Design, develop, test & maintain backend systems using Node.js, MongoDB/MySQL/PostgreSQL, ExpressJS, AWS, GIT. * Collaborate with cross-functional teams on project requirements and deliverables.

Key Responsibilities AI Architect Designs and oversees the AI strategy, ensuring solutions are scalable, adaptable, and aligned with business objectives. They establish AI frameworks, integrate systems, and provide guidance on infrastructure. AI Engineering Develops and deploys AI models, optimizing performance and ensuring seamless integration into existing workflows. They fine-tune algorithms, uses methods like RAG, Vector Databases and focus on real-world implementation. Develops and executes test plans to validate AI models, identifying performance issues and potential biases. Design and Development: Develop AI models and algorithms tailored to the specific needs of the business. Experience with Natural Language Processing (NLP), prompt engineering, etc. Works with existing data science team where applicable. AI Testing & Validation Responsibilities include: Ensure AI solutions perform reliably and ethically. Quality Assurance Conducts functional and non-functional testing, ensuring AI applications meet performance, security, and scalability requirements. Data Validation Monitors training data quality, ensuring accuracy, integrity, and consistency while minimizing errors and biases. Model Evaluation Assesses AI models through rigorous validation techniques, including cross-validation and error analysis, to refine performance. AI Ethics Auditing– Reviews AI decisions for fairness, transparency, and compliance with regulations, adjusting models where necessary. Deployment: Experience deploying models into production environments and working with teams to integrate solutions into existing software applications and platforms. Familiarity with CI/CD pipelines. Data Analysis: Analyze large datasets to extract meaningful insights and patterns; including interoperable data that may not be fully first party data. Strong understanding of supervised/unsupervised learning, neural networks, model evaluation and handling data at scale. Optimization: Have a passion for continual learning, optimizing AI models for performance and accuracy. Research: Stay updated with the latest AI advancements and integrate cutting-edge technologies into projects. Collaboration: Work closely with cross-functional teams to understand business requirements and deliver effective solutions. Documentation: Prepare comprehensive documentation for developed AI models and algorithms. Testing: Conduct rigorous testing and validation to ensure robustness and reliability of AI solutions. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or in related field. Experience: 5 to 8+ years of professional experience in software engineering, machine learning, or AI. 3+ years specifically working with generative AI models (e.g., transformers, diffusion models, LLMs like GPT, image generation models like Stable Diffusion or DALL•E). Technical Skills: Proficiency in programming languages such as Python, Java, C++, and frameworks like TensorFlow, PyTorch or Tensorflow and ML frameworks. Proficient in LLM Frameworks such as LangChain, LlamaIndex, OpenAI API. Analytical Skills: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work collaboratively in a team environment and mentor junior developers. Creativity: Ability to think creatively and develop innovative solutions. Preferred Skills and Experience Experience with cloud platforms such as AWS, Azure, or Google Cloud. Knowledge of big data technologies and databases. Familiarity with natural language processing (NLP) and computer vision. Understanding of software development lifecycle and agile methodologies. Experience with version control systems like Git.

Role & responsibilities Must Haves Proven track record of project delivery for 1+ years Good coding (Preferably Python) skills and DSA Good problem solving and communication skills. Good Knowledge of Gen-AI technologies (LLM prompt engineering) Familiarity with React, HTML, CSS, JS or similar frameworks Familiarity with HTTP, REST, microservices, concurrency and Multithreading Willingness to work in a dynamic and fast paced environment. 4-6 years of experience with a Bachelor / Master's Degree in Computer Science or equivalent. Ownership and commitment towards work

This position requires expertise in designing, developing, debugging, and maintaining AI-powered applications and data engineering workflows for both local and cloud environments. The role involves working on large-scale projects, optimizing AI/ML pipelines, and ensuring scalable data infrastructure. As a PMTS, you will be responsible for integrating Generative AI (GenAI) capabilities, building data pipelines for AI model training, and deploying scalable AI-powered microservices. You will collaborate with AI/ML, Data Engineering, DevOps, and Product teams to deliver impactful solutions that enhance our products and services. Additionally, it would be desirable if the candidate has experience in retrieval-augmented generation (RAG), fine-tuning pre-trained LLMs, AI model evaluation, data pipeline automation, and optimizing cloud-based AI deployments. Responsibilities AI-Powered Software Development & API Integration Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization. Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making. Data Engineering & AI Model Performance Optimization Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake. Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings). Microservices, APIs & Security Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication. Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices. AI & Data Engineering Collaboration Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions. Engage in Agile ceremonies, backlog refinement, and collaborative problem-solving to scale AI-powered workflows in areas like fraud detection, claims processing, and intelligent automation. Cross-Functional Coordination and Communication Collaborate with Product, UX, and Compliance teams to align AI-powered features with user needs, security policies, and regulatory frameworks (HIPAA, GDPR, SOC2). Ensure seamless integration of structured and unstructured data sources (SQL, NoSQL, vector databases) to improve AI model accuracy and retrieval efficiency. Mentorship & Knowledge Sharing Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions. Education & Experience Required 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions. Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles. Bachelors Degree or equivalent in Computer Science, Engineering, Data Science, or a related field. Proficiency in full-stack development with expertise in Python (preferred for AI), Java Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server) NoSQL (OpenSearch, Redis, Elasticsearch) Vector Databases (FAISS, Pinecone, ChromaDB) Cloud & AI Infrastructure: AWS: Lambda, SageMaker, ECS, S3 Azure: Azure OpenAI, ML Studio GenAI Frameworks & Tools: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI. Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization. Proficiency in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment. Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams. Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption.

The role of an Industrial and Auto Strategy Consultant at Accenture involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. You will be part of the Industry Strategy Practice in Accenture's Strategy & Consulting Global Network, focusing on the CEOs" most strategic priorities at the intersection of business and technology. The primary areas of work include strategy and business consulting in the Automotive and Industrials industry, covering Market Segmentation, Market Assessment & Sizing, Product strategy, Sales & distribution, Supply chain, Corporate Strategy, Growth Strategy, Digital Strategy, and more. As a part of this role, you will conduct market research & analysis, develop strategies to address challenges facing Automotive/Industrials companies, work with clients to identify strategic goals, shape operating models, identify cost take-out opportunities, and drive business transformation. Additionally, you will collaborate with ecosystem partners to assist clients in achieving sustainability objectives and support clients in their inorganic growth agenda. Your responsibilities will also involve leading practice workstreams, preparing and delivering presentations to clients, monitoring industry trends, and participating in the development of thought leadership content. The ideal candidate must possess a strong understanding of the Automotive/Industrials industry, proven experience in developing & executing successful strategies, and a track record of working with C-level executive clients. They should have expertise in Corporate Strategy, Growth Strategy, Market Entry Strategy, Operating Model Strategy, M&A, and other related areas. Additionally, the candidate should demonstrate a strategic mindset, issue-based problem-solving skills, business acumen, and a capability to generate strategy sales & demand with market unit leads. This role offers a great learning ground deeply rooted in Industry & Business Strategy, providing an opportunity to work with key Automotive/Industrials clients and driving transformative strategic value & business growth. If you are someone with a strategic mindset, proven consulting experience, and a passion for shaping innovative strategies in the Automotive/Industrials industry, we invite you to join our high-performing team at Accenture.,

3+ Years experience in Gen AI, AI Engineering, Solution Architecture Gen AI Specialist strong experience in LLM, AI engineering, AI project deployment & production, Gen AI innovation, Gen AI architecture, Gen AI based use case design, build, deploy & scale at clients. 2 years + Strong experience in AI, ML, Data Science. Solutioning, Architecture, Build, Deploy, ML Ops, Production, Managed Services Top Engineering Colleges Preferred Prefer is resource is from tech startup. Consulting and Tech Firms are also good. Cloud Firms too if we can afford Full Stack Tech Skills i.e. Front End, Middle End, Back End, Custom Apps, Automation will be a big bonus Experience in Solution Architecture for projects, AI Project Delivery hands on,

Key Responsibilities Technical Leadership Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for cost-performance optimization. Design GPU/TPU-optimized training pipelines (FSDP, DeepSpeed) for billion-parameter models. Cloud-Native AI Development Build multi-cloud GenAI platforms (Azure OpenAI + GCP Vertex AI + AWS Bedrock) with unified MLOps. Implement enterprise security: VPC peering, private model endpoints, and data residency compliance. Innovation & Strategy Pioneer GenAI use cases: Agentic workflows, AI-driven synthetic data generation, real-time fine-tuning. Establish AI governance frameworks: Model cards, drift monitoring, and red-teaming protocols. Cross-Functional Impact Partner with leadership to define AI roadmaps and ROI metrics (e.g., $ saved via AI-driven automation). Preferred candidate profile Education: Bachelors/Masters in CS/AI or equivalent industry experience (5+ years in ML, 2+ in GenAI). Technical Mastery: Languages: Python. Frameworks: Expert-level PyTorch, TensorFlow Extended (TFX), ONNX Runtime. Cloud: Certified in Azure AI Engineer Expert and/or GCP Professional ML Engineer. GenAI Expertise: Shipped production GenAI systems (e.g., 10k+ QPS chatbots, code autocomplete at GitHub Copilot scale). Advanced prompt/response engineering: Self-critique chains, LLM cascades, guardrail-driven generation. Must-Have Experience Cloud AI experience: Azure: Designed solutions with Azure OpenAI, MLOps Pipelines, and Cognitive Search. GCP: Scaled Vertex AI LLM Evaluation, Gemini Multimodal, and TPU v5 Pods. High-Impact Projects: Automation projects to reduce significant $$ costs. Built RAG systems with hybrid search (vector + lexical) and dynamic data hydration. Led AI compliance for regulated industries (healthcare, finance).

Role & responsibilities * Immediate Joiners Please Azure and Azure AI infrastructure Autogen 4 and 6 Semantic Kernel Millions of documents handling Agentic Tools experience Programming Languages & Tools: Python, PyTorch, TensorFlow, Hugging Face, PyPDF, PyOCR, OpenCV Generative AI & LLM Frameworks: LangChain, LangSmith, LlamaIndex, AutoGen, Semantic Kernel Cloud Services: MS Azure AI Services (Azure AI Studio, Azure AI Search, Azure Cosmos DB, Azure Machine Learning) Database & Search Technologies: Chroma DB, Azure, Cosmos DB, FAISS, Pinecone, Qdrant, Milvus Data Engineering & Workflow Automation: ETL Pipelines, data preprocessing, multimodal workflows, large document volume handling (1,0002,000 documents). AI Techniques: RAG systems, Embedding techniques, Agentic AI, Prompt engineering. Visualization Tools: Power BI, Tableau Document/Image Processing: PyPDF, PyOCR, OpenCV Preferred candidate profile

Greetings !!! Hiring GEN AI Engineers for Hyderabad Location. Skills Required - GEN AI , Python, Lang chain Experience - 3 to 5 years Location - Hyderabad Interested one can share resumes to anmol.bhatia@incedoinc.com

Design, develop, and maintain scalable and efficient test automation frameworks. Develop comprehensive test plans based on project requirements and specifications. Create automated test scripts to validate functionality performance and reliability Required Candidate profile Strong programming skills in Java. exp in developing/maintaining automation f/w like Selenium and Robot framework experience with CI/CD tools like Jenkins Gen AI basic exposure is mandatory

Location: Noida 1015 years in Oracle Cloud and AI, with 5+ years of proven experience in designing, architecting and deploying AI/ML & Gen AI Solution over OCI AI stack. Strong Python development experience, streamlit, XML, JSON etc. Deep hands-on knowledge of LLMs (e.g. Cohere, GPT etc.) &prompt engineering techniques (e.g. zero-shot, few-shot, CoT, and ReAct) especially for Cohere, & OpenAI Models. Strong knowledge of AI governance, security, guardrails, and responsible AI. Must have knowledge of data ingestion, feature engineering, model training, evaluation, deployment, and monitoring. Proficient in AI/ML/Gen AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face, LangChain)& Vector DBs (e.g., Pinecone, Milvus). Role & responsibilities Qualifications: Oracle Cloud certifications such as: OCI Architect Professional, OCI Generative AI Professional,OCI Data Science Professional B.Tech Computer Science / MCA or equivalent degrees Any degree or diploma in AI would be preferred.

About this role: Wells Fargo is seeking an individual contributor for the Strategy and Execution function for Global Operations Data, Analytics and Reporting. This role involves working on governance, driving initiatives and projects, working closely with senior management on key deliverables, and collaborating with business and technical stakeholders. In this role, you will: Act as a Business Execution advisor to leadership to drive performance and initiatives, and develop and implement information delivery or presentations to key stakeholders and senior management Work on multiple business functional areas with focus on implementing and delivering long-term strategies, policies, and process advancements. Lead business execution team for assigned initiatives ensuring solutions are designed, integrated, and controlled to improve effectiveness, limit risk exposure, and create efficiencies as appropriate. Provide support to senior leadership for implementing innovative and significant business solutions that are large scale and cross organizational Collaborate and influence functional management to obtain resources, influence outcomes and ensure alignment with policies and business line objectives. Manage team meetings or steering committee to facilitate decision making and support implementation of recommendations and plans Provide input into communication routines with stakeholders, business partners, and experienced leaders Engage with all levels of professionals and managers across organization and serve as an experienced advisor to the leadership Required Qualifications: 5+ years of Business Execution, Implementation, or Strategic Planning experience in Banking Industry with work exposure to senior leadership, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience & education Influencing large teams with multiple stakeholders, strategic thinking, framework driven roadmaps, knowledge about data driven decisioning. Good to have - Python, Power BI, Tableau. Excellent PowerPoint story boarding, MS Excel advanced levels Excellent verbal and written communication skills and the ability to communicate complex ideas in a concise and clear fashion Ability to effectively communicate information to a variety of audiences Desired Qualifications: MBA from Top Tier Institute Excel MS Office Product Suite - Advanced Skills Finance P&L Knowledge Data Products Experience in Artificial Intelligence, machine Learning, Gen AI.