12 Llm Ops Jobs

As a Subject Matter Expert in ML or LLM Ops at CitiusTech, you will play a crucial role in guiding the organization's MLOps and LLMOps strategy. Your responsibilities will involve providing strategic direction, technical leadership, and overseeing the development of scalable infrastructure and processes aligned with business objectives. You will be at the forefront of innovation by designing and implementing robust pipelines for ML and LLM models, ensuring efficient deployment and continuous optimization. Collaboration with cross-functional teams such as engineering, data science, and product will be essential to seamlessly integrate ML and LLM models into production workflows. Your experience of 10-15 years in MLOps or LLM Ops, along with expertise in CSPs like AWS, Azure, and GCP, will be beneficial. You must have a proven track record of successful deployments and possess in-depth knowledge of MLOps tools and platforms such as Kubernetes, Docker, Jenkins, Git, MLflow, and LLM-specific tooling. Familiarity with Cloud platforms, infrastructure as code principles, DevOps methodologies, and CI/CD pipelines is required. Your communication skills will be crucial as you will be required to translate complex technical concepts clearly to both technical and non-technical audiences. A passion for innovation and optimization of ML and LLM workflows is highly desired. Life at CitiusTech is centered on core values like Passion, Respect, Openness, Unity, and Depth (PROUD) of knowledge. The work culture is fun, transparent, non-hierarchical, diverse, and focused on continuous learning and work-life balance. CitiusTech has been rated as a Great Place to Work and offers comprehensive benefits to support a rewarding career. CitiusTech's EVP, "Be You Be Awesome," reflects the company's commitment to creating a great workplace where employees can thrive personally and professionally. Through continuous learning and growth opportunities, CitiusTech aims to positively impact human lives by solving healthcare challenges. If you are someone who is passionate about technology, innovation, and making a real-world impact in healthcare, CitiusTech welcomes you to join their team and be part of a culture that values Faster Growth, Higher Learning, and Stronger Impact. To explore more about CitiusTech, please visit www.citiustech.com. Happy Applying!,

As the AI Ops, ML Ops, and LLM Ops Manager, your primary responsibility is to oversee the efficient and scalable operations of AI and machine learning models. You will be in charge of managing the entire model lifecycle, covering development, deployment, monitoring, and maintenance. It is crucial to ensure strict adherence to predefined Service Level Agreements (SLAs) for AI and ML operations. To streamline the integration and deployment of models, you will be required to develop and maintain CI/CD Ops pipelines. Additionally, implementing and managing model registries for version control and governance is essential. You will establish coding checklists and best practices while also developing and automating testing frameworks to maintain model quality and reliability. Designing and managing inference pipelines for both real-time and batch predictions will be under your purview. Innovation plays a key role in this role, as you will be expected to adopt emerging technologies such as GenAI, AI, and NLP. Accelerating product/service development through rapid prototyping and iterative methods will be necessary to drive innovation effectively. Furthermore, aligning analytics innovation efforts with business strategy, IT strategy, and legal/regulatory requirements is imperative. You will also be tasked with identifying and developing advanced analytics capabilities and ecosystem partnerships in alignment with the DnA strategy. Key Responsibilities: - Lead AI Ops, ML Ops, and LLM Ops to ensure efficient and scalable operation of AI and machine learning models. - Develop and manage the model lifecycle, including development, deployment, monitoring, and maintenance. - Ensure adherence to predefined SLAs for AI and ML operations. - Create and manage analytics product/services roadmaps from concept to launch. - Develop and maintain CI/CD Ops pipelines for seamless integration and deployment of models. - Implement and manage model registries for version control and governance. - Establish and enforce coding checklists and best practices. - Develop and automate testing frameworks to ensure model quality and reliability. - Design and manage inference pipelines for real-time and batch predictions. - Incubate and adopt emerging technologies (GenAI, AI, NLP) to accelerate product/service development through rapid prototyping and iterative methods. - Align analytics innovation efforts with business strategy, IT strategy, and legal/regulatory requirements. - Establish and update strategies, implementation plans, and value cases for emerging technologies. - Drive innovation using appropriate people, processes, partners, and tools. - Identify and develop advanced analytics capabilities and ecosystem partnerships in alignment with DnA strategy. - Oversee end-to-end delivery of analytics services and products across cross-functional business areas. - Serve as the point of escalation, review, and approval for key issues and decisions. - Manage resource and capacity planning in line with business priorities and strategies. - Foster continuous improvement within the team. - Decide on program timelines, governance, and deployment strategies. Key Performance Indicators: - Achieved targets in Enterprise business case contribution, KPIs, customer satisfaction, and innovation measures. - Delivery on agreed KPIs including business impact - Launch of innovative technology solutions across Novartis at scale. - Business impact and value generated from DDIT solutions. - Adoption and development of Agile Productization and DevOps practices. - Operations stability and effective risk management. - Feedback on customer experience. - Applications adherence to ISC requirements and are audit ready. - Business capability, vision & strategy clearly defined, communicated, and executed, well aligned to business strategy and Enterprise IT strategy, providing a competitive advantage to Novartis. - Role model with the highest standards of professional conduct in leading the business capability area in line with the new IT operating model. - Deployment of digital platforms and services at scale to deliver the digital strategy. Skills And Experience: - Demonstrated experience in Budget Management, Business Acumen, Performance Management, Planning, Project Management, Risk Management, Service Delivery Management, and stakeholder management. - Strong understanding of AI Ops, ML Ops, and LLM Ops. - Experience in developing and managing the model lifecycle, including deployment and maintenance. - Proficiency in managing operations with predefined SLAs. - Expertise in CI/CD Ops pipelines development. - Experience with model registry and management. - Knowledge of coding checklists and best practices. - Proficiency in developing and automating testing frameworks. - Experience in designing and managing inference pipelines. - Production experience with commercial and open-source ML platforms. - Strong knowledge of AWS, Databricks, and Snowflake service offerings. - Ability to collaborate with business teams to gather requirements, groom product backlogs, and drive delivery. - Agile delivery experience managing multiple concurrent delivery cycles. - Solid foundation in CRISP analytical life cycle management. - Strong leadership skills with the ability to build high-performing teams. - Excellent vendor management and IT governance skills. - Innovative and analytical mindset with a focus on continuous improvement. - Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT governance, Building High Performing Teams, Vendor Management, Innovative & Analytical Technologies. - Strong understanding of descriptive vs. prescriptive Analytical frameworks. - Strong knowledge of visualization platforms and project life cycle management, including Power BI, Qlik, and MicroStrategy. - Significant production experience addressing visualization platform and data pipeline performance constraints. - Strong analytical and problem-solving skills, effective communication, and the ability to influence and collaborate with cross-functional teams.,

As a Manager, ML Ops Engineer at Genpact, you will be an integral part of the team responsible for building and maintaining the infrastructure and pipelines for cutting-edge Generative AI applications. Your role will involve collaborating closely with the Generative AI Full Stack Architect to ensure the efficiency, scalability, and reliability of Generative AI models in production. Your responsibilities will include designing, developing, and implementing ML/LLM pipelines for generative AI models, conducting research to explore new techniques, integrating GenAI APIs and microservices into existing systems, and automating ML tasks across the model lifecycle using tools like GitOps, CI/CD pipelines, and containerization technologies. Furthermore, you will be involved in MLOps support and maintenance on ML platforms Dataiku/Sagemaker, implementing version control, CI/CD pipelines, and containerization techniques, designing monitoring and alerting systems, and collaborating with infrastructure and DevOps teams for resource management. To qualify for this role, you should have a Bachelor's degree in computer science, Data Science, Engineering, or a related field, along with a deep understanding of generative AI concepts and experience in MLOps or related areas. Strong expertise in cloud platforms, CI/CD principles, containerization technologies, and monitoring tools is essential. Excellent communication, collaboration, and problem-solving skills are also required, along with a passion for Generative AI and its potential to transform industries. If you are looking to join a dynamic team at Genpact and contribute to the advancement of Generative AI technologies, we encourage you to apply for the Manager, ML Ops Engineer position in India-Bangalore. This is a full-time role with the opportunity to work on cutting-edge projects and make a significant impact in the field of AI. Join us on this exciting journey to shape the future with your expertise in ML Ops and Generative AI!,

Are you ready to power the world's connections Kong's API Management suite consists of various products like the Kong Enterprise Gateway, the Kong AI Gateway, and the Konnect SaaS platform. These products assist organizations in managing and operating their APIs securely, with high throughput and reliability. We are seeking an engineering leader to oversee the teams responsible for API Ops, LLM Ops, and the UI requirements of our product portfolio. The API Ops team manages the deck Open Source command line interface (CLI) for all Kong runtimes and provides Terraform support for the Kong Gateway, essential tools for operating Kong's products in production. The newly formed LLM Ops team will support other engineering teams in working with Large Language Models (LLMs) and introducing new features to our product lineup. The UI team is responsible for developing core features in Kong's SaaS platform. This role will be based in our office in Bangalore, India, with a hybrid work model involving three days in the office and two days working from home. As a leader, you are expected to optimize your time with the team and drive efficient outcomes. Your responsibilities will include building and leading high-performing engineering teams, attracting and retaining top talent, ensuring technical success, maintaining software systems for high reliability, shaping technical direction, collaborating with product leadership, managing agile workstreams, engaging with customers, and contributing to business growth. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science or a related field, along with experience in engineering management and SaaS development. Strong expertise in networking concepts, experience with public cloud platforms, and exceptional communication skills are also required. Kong Inc. is a prominent developer of cloud API technologies, dedicated to helping companies worldwide adopt an API-first approach and accelerate AI adoption securely. Kong empowers organizations of all sizes to enhance developer productivity, build securely, and expedite time to market. For more information about Kong, please visit www.konghq.com or follow us on X @thekonginc.,

As a Senior Data Scientist, you will play a crucial role in supporting the design, development, and implementation of generative AI models and systems. Your responsibilities will include assisting in model development, algorithm optimization, data preprocessing, feature engineering, model evaluation, and collaboration with cross-functional teams. You will focus on learning and developing your skills in generative AI while ensuring ethical considerations are adhered to under the guidance of senior team members. Your technical skills should include in-depth knowledge of ML, Deep Learning, NLP algorithms, and experience with ML platforms like GCP Vertex AI, Azure AI Foundry, or AWS SageMaker. Proficiency in Python, Java, or C++, along with machine learning frameworks such as TensorFlow or PyTorch, is essential for developing and optimizing generative AI models. Cloud computing experience, particularly with Google or Azure Cloud Platform, is crucial, as well as an understanding of Data Analytics Services offered by these platforms. Preferred technical skills may include knowledge of Azure Cognitive Search, Google Cloud Search, AWS Kendra, and experience in large-scale deployment of ML projects with a good understanding of DevOps/MLOps/LLM Ops. Strong communication skills, the ability to work independently, mentor junior developers, and understand business objectives to support data needs are key behavioral attributes required for this role. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science and possess 6 to 8 years of relevant work experience. If you are looking to contribute to cutting-edge generative AI projects, collaborate with diverse teams, and stay updated with the latest AI trends, this role is ideal for you.,

Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 1000 companies. With a presence in more than 45 countries across five continents, Evalueserve excels in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate clients" business impact and strategic decision-making. The team at Evalueserve consists of 4,500+ talented professionals operating across 45 countries, spanning India, China, Chile, Romania, the US, Canada, as well as emerging markets like Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work in multiple countries, Evalueserve offers a dynamic, growth-oriented, and open culture that prioritizes flexible work-life balance, diverse and inclusive teams, and equal opportunities for all. Evalueserve University has been established to design and deliver a Global Learning Strategy integral to business success. From new graduate onboarding to leadership skill development workshops and domain-specific knowledge programs, the university strengthens structured learning opportunities. As a member of the Evalueserve team, you will partner with business leaders and subject matter experts to design and deliver learning programs focused on developing key competencies in Data Science. You will manage, enhance, and deliver signature boot-camp training programs for new hires globally and collaborate with Operations to identify training needs for on-role analysts. Additionally, you will create new learning content, monitor training quality and effectiveness, and ensure alignment with business needs. To excel in this role, you should have 5-10 years of experience in Data Science, along with proficiency in Cloud Fundamentals (Azure/AWS/GCP), Python, Machine Learning, LLM Ops, MLOps, Project Management, and NLP. Advanced skills in Computer Vision, Deep Learning, and other frameworks are desirable. Experience in Data Warehousing/Data Engineering/Big Data is an added advantage. A graduation degree is a prerequisite, along with excellent communication and interpersonal skills, and proficiency in Excel and PowerPoint. If you are ready to elevate your impact through innovation and learning, Evalueserve welcomes you to join its dynamic team and contribute to its mission of delivering cutting-edge solutions to clients worldwide.,

Publicis Sapient is seeking a Principal Data Scientist to join its Data Science practice. In this role, you will act as a trusted advisor to clients, driving innovation in applied machine learning and statistical analysis. You will also lead efforts to enhance the group's capabilities for the future. Your responsibilities will include leading teams to develop data-driven solutions driven by learning algorithms, educating teams on problem-solving models in machine learning, and translating objectives into data-driven solutions. You will work with diverse data sets, cutting-edge technology, and witness your insights translating into tangible business results regularly. Your role will play a crucial part in integrating machine learning into core market offerings such as eCommerce, advertising, AdTech, and business transformation. You will also direct analyses to enhance the effectiveness of marketing tactics and collaborate with leaders in various Publicis Sapient divisions to ensure data-driven solutions are brought to the market. Key areas of focus will be customer segmentations, media and advertising optimization, recommender systems, fraud analytics, personalization, and forecasting. Your Impact: - Design and implement analytical models to support product and project objectives. - Research and innovate to develop next-generation solutions in digital marketing and customer experience. - Provide technical leadership and mentorship in data science. - Enhance machine learning operations platform for Generative AI in various industries. - Drive the application of machine learning in existing project disciplines. - Design experiments to measure changes in user experience. - Segment customers and markets for targeted messaging. - Direct research on analytics platforms to guide solutions. - Ensure solution and code quality through design and code reviews. - Establish standards in machine learning and statistical analysis for consistency and efficiency. - Assess client needs to adopt appropriate approaches for solving challenges. Qualifications: Your Skills & Experience: - Ph.D. in Computer Science, Math, Physics, Engineering, Statistics, or related field. - 15+ years of experience applying statistical learning methods in eCommerce and AdTech. - Proficiency in Gen AI tools and frameworks, LLM finetuning, and LLM ops. - Strong understanding of regression, classification, and cluster analysis approaches. - Proficiency in statistical programming with R, SAS, SPSS, MATLAB, or Python. - Expertise in Python, R, Scala, and SQL programming languages. Benefits of Working Here: - Access to regional benefits. - Gender-Neutral Policy. - 18 paid holidays per year. - Generous parental leave and new parent transition program. - Flexible work arrangements. - Employee Assistance Programs for wellness. Publicis Sapient is a digital transformation partner that helps organizations transition to a digitally enabled state. With a focus on strategy, consulting, customer experience, and agile engineering, the company aims to accelerate clients" businesses by designing products and services that customers truly value. Join a team of over 20,000 people worldwide who are united by core values and a purpose of helping people thrive in the pursuit of the next. Ideal candidates for this role will have experience in traditional AI and recent experience in Gen AI and Agentic AI. Organization, adaptability to change, and hands-on coding skills are highly valued.,

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.,

As an AI Research Scientist, your role will involve developing the overarching technical vision for AI systems that cater to both current and future business needs. You will be responsible for architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Working in partnership with product management, you will design agile project roadmaps that align technical strategy with market needs. Additionally, you will coordinate with data engineering teams to guarantee smooth data flows, quality, and governance across various data sources. Your responsibilities will also include leading the design of reference architectures, roadmaps, and best practices for AI applications. You will evaluate emerging technologies and methodologies, recommending innovations that can be integrated into the organizational strategy. Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems will be crucial aspects of your role. Leveraging containerization (Docker, Kubernetes) and cloud services, you will streamline the deployment and scaling of AI systems. Implementing robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will also be part of your duties. Project management will be a key component of your role, overseeing the planning, execution, and delivery of AI and ML applications within budget and timeline constraints. You will be responsible for the entire lifecycle of AI application development, from conceptualization and design to development, testing, deployment, and post-production optimization. Enforcing security best practices throughout each phase of development, with a focus on data privacy, user security, and risk mitigation, will be essential. Furthermore, providing mentorship to engineering teams and fostering a culture of continuous learning will play a significant role in your responsibilities. In terms of mandatory technical and functional skills, you should possess a strong background in working with or developing agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with robust knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras, is required. You should also have proven experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building and deploying scalable AI solutions. Hands-on skills with containerization (Docker), orchestration frameworks (Kubernetes), and related DevOps tools like Jenkins and GitLab CI/CD are necessary. Experience using Infrastructure as Code (IaC) tools such as Terraform or CloudFormation to automate cloud deployments is essential. Additionally, proficiency in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture are vital for this role. Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) is also required to support robust inter-system communications. Preferred technical and functional skills include experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) to ensure system reliability and operational performance. Familiarity with cutting-edge libraries such as Hugging Face Transformers, OpenAI's API integrations, and other domain-specific tools is advantageous. Experience in large-scale deployment of ML projects, along with a good understanding of DevOps/MLOps/LLM Ops and training and fine-tuning of Large Language Models (SLMs) like PALM2, GPT4, LLAMA, etc., is beneficial. Key behavioral attributes for this role include the ability to mentor junior developers, take ownership of project deliverables, contribute to risk mitigation, and understand business objectives and functions to support data needs. If you have a Bachelor's or Master's degree in Computer Science, certifications in cloud technologies (AWS, Azure, GCP), and TOGAF certification (good to have), along with 11 to 14 years of relevant work experience, this role might be the perfect fit for you.,

As an AI Azure Architect, your primary responsibility will be to develop the technical vision for AI systems that cater to the existing and future business requirements. This involves architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Additionally, you will partner with product management to design agile project roadmaps aligning technical strategies with market needs. Coordinating with data engineering teams is essential to ensure smooth data flows, quality, and governance across different data sources. Your role will also involve leading the design of reference architectures, roadmaps, and best practices for AI applications. Evaluating emerging technologies and methodologies to recommend suitable innovations for integration into the organizational strategy is a crucial aspect of your responsibilities. You will be required to identify and define system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems. Leveraging containerization (Docker, Kubernetes) and cloud services will streamline the deployment and scaling of AI systems. Implementation of robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will be part of your duties. Moreover, you will oversee the planning, execution, and delivery of AI and ML applications, ensuring they are completed within budget and timeline constraints. Managing project goals, allocating resources, and mitigating risks will fall under your project management responsibilities. You will be responsible for overseeing the complete lifecycle of AI application developmentfrom conceptualization and design to development, testing, deployment, and post-production optimization. Emphasizing security best practices during each development phase, focusing on data privacy, user security, and risk mitigation, is crucial. In addition to technical skills, the ideal candidate for this role should possess key behavioral attributes such as the ability to mentor junior developers, take ownership of project deliverables, and contribute towards risk mitigation. Understanding business objectives and functions to support data needs is also essential. Mandatory technical skills for this position include a strong background in working with agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with knowledge of machine learning libraries like TensorFlow, PyTorch, and Keras, is required. Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform), containerization tools (Docker), orchestration frameworks (Kubernetes), and DevOps tools (Jenkins, GitLab CI/CD) is essential. Proficiency in SQL and NoSQL databases, designing distributed systems, RESTful APIs, GraphQL integrations, and event-driven architectures are also necessary. Preferred technical skills include experience with monitoring and logging tools, cutting-edge libraries like Hugging Face Transformers, and large-scale deployment of ML projects. Training and fine-tuning of Large Language Models (LLMs) is an added advantage. Educational qualifications for this role include a Bachelor's/Master's degree in Computer Science, along with certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification. The ideal candidate should have 11 to 14 years of relevant work experience in this field.,

Required Qualifications 8+ years of experience in DevOps, SRE, or similar roles, with at least 1 year specifically working with LLMs or AI systems in production Strong hands-on experience with AWS cloud services, particularly Bedrock, Lambda, SQS, API Gateway, OpenSearch, and CloudWatch Experience with infrastructure-as-code using Terraform, CloudFormation, or similar tools Proficiency in Python and experience building automation tooling and pipelines Familiarity with LangOps platforms such as Langfuse for LLM observability and evaluation Experience with CI/CD pipelines Knowledge of logging, monitoring, and alerting systems Understanding of security best practices for AI systems, including prompt injection mitigation techniques Excellent troubleshooting and problem-solving skills Strong communication skills and ability to work effectively with cross-functional teams Must be legally entitled to work in the country where the role is located Preferred Qualifications Experience with prompt engineering and testing tools like Promptfoo Familiarity with vector databases and retrieval-augmented generation (RAG) systems Knowledge of serverless architectures and event-driven systems Experience with AWS Guardrails for LLM security Background in data engineering or machine learning operations Understanding of financial systems and data security requirements in the finance industry Familiarity with implementing technical solutions to meet compliance requirements outlined in SOC2, ISAE 3402, and ISO 27001

About Idolize Idolize is a fast-growing AI tech company at the forefront of HyperAutomation. For over 6 years, weve helped enterprises transform operations by combining RPA, workflow tools, computer vision, NLP, and GenAI into powerful, scalable automation solutions. Were now expanding our capabilities through a dedicated Center of Excellence focused on Agentic AI and LLM Opsenabling the next generation of intelligent, autonomous enterprise systems. If you're passionate about AI, automation, and building whats next, Idolize offers an exciting, innovation-driven environment where your work creates real impact. Educational Background Degree: B.Tech/B.E. in Computer Science or Information Technology; M.Tech (CS/IT) or MCA. Experience Level: 1+ years of hands-on experience in AI/ML system deployment, LLM integration or software automation. Overall experience shall be more than 1 year and less than 5 years out of which 1 year is mandatorily in AI driven development and innovations Technical Skills Build a Basic Chatbot: Architect and implement a maintainable chatbot skeleton, routing user inputs through your LLM pipeline. Add Tools: Integrate external APIs, databases, and microservices so agents can fetch data and execute actions. Add Memory: Design contextmanagement layers that persist and recall past interactions for coherent multiturn dialogues. Add Human-in-the-Loop: Embed review checkpointsalerts or UI prompts—allowing human operators to supervise and correct outputs. Customize State: Maintain a central session “state” store (TypedDict or custom class) to control parameters, flags, and intermediate results across workflows. LLM Integration: Proficiency with OpenAI/Azure OpenAI APIs or Hugging Face; fine-tuning and versioning transformer models. Containerization & Orchestration: Docker, Kubernetes Vector Search & RAG: Hands-on experience with FAISS, Qdrant or similar for retrieval-augmented generation. API Development: Building and securing scalable inference endpoints (FastAPI, AWS Lambda + API Gateway). Keywords which shall be part of your profile and work: ‘Python’, ‘Docker’, ‘Kubernetes’, ‘Terraform’, ‘DVC’, ‘LangChain’, ‘LangGraph’, ‘FAISS/Qdrant’, ‘Prompt Engineering’, ‘CI/CD’, ‘FastAPI’, ‘Cloud (AWS/Azure/GCP)’. Desired Traits Problem Solving: Strong analytical mindset with an ability to decompose complex automation challenges. Communication: Clear, concise articulation of technical designs and findings to both technical and non-technical stakeholders. Learning Attitude: Proactive in researching new GenAI/LLM techniques and integrating them into existing pipelines. Team Player: Mentoring junior engineers and fostering a collaborative, solutions-driven environment. Additional Qualifications for the role (Candidate with these skills will be preferred) Prompt Engineering: Hands-on work crafting, evaluating and refining prompts for diverse LLM tasks. RPA & Grid Automation: Experience with Selenium Grid or enterprise RPA platforms (Automation Anywhere, PowerAutomate). Cloud Native & Serverless: Deploying GenAI workloads on AWS SageMaker, Azure ML or GCP Vertex AI. Open Source Contributions: Public projects or research publications in NLP, LLMs or related tools. What is in it for you Live Use-Cases from Day 1: Drive production AI and automation projects across Banking, NBFC, Manufacturing and Insurance. High-Performing Culture: Work alongside passionate, subject-matter experts who thrive on innovation and excellence. Attractive Rewards: Competitive salary, performance-linked bonuses, and equity grants to recognize your impact. Modern, Central Office: AWFIS workspace in Thane Wagle Estate, with all amenities so you can focus on building solutions. Please send your resume to talent@idolizesolutions.com. We would like to schedule your interview at the earliest in person (mandatory). Office Address: Idolize Business Solutions AWFIS Office Space, 2nd Floor, Kalpataru Prime, Road Number 16, Wagle Industrial Estate, Thane West, 400604. Website: www.idolizesolutions.com | Email: talent@idolizesolutions.com