Senior AI/ML Engineer

CWX is looking for a dynamic SENIOR AI/ML ENGINEER to become a vital part of our vibrant PROFESSIONAL SERVICES TEAM, working on-site in Hyderabad . Join the energy and be part of the momentum!

At CloudWerx, we're looking for a Senior AI/ML Engineer to lead the design, development, and deployment of tailored AI/ML solutions for our clients. In this role, you’ll work closely with clients to understand their business challenges and build innovative, scalable, and cost-effective solutions using tools like Google Cloud Platform (GCP), Vertex AI, Python, PyTorch, LangChain, and more.

You’ll play a key role in translating real-world problems into robust machine learning architectures, with a strong focus on Generative AI, multi-agent systems, and modern MLOps practices. From data preparation and ensuring data integrity to building and optimizing models, you’ll be hands-on across the entire ML lifecycle — all while ensuring seamless deployment and scaling using cloud-native infrastructure.

Clear communication will be essential as you engage with both technical teams and business stakeholders, making complex AI concepts understandable and actionable. Your deep expertise in model selection, optimization, and deployment will help deliver high-performing solutions tailored to client needs.

We’re also looking for someone who stays ahead of the curve — someone who’s constantly learning and experimenting with the latest developments in generative AI, LLMs, and cloud technologies. Your curiosity and drive will help push the boundaries of what's possible and fuel the success of the solutions we deliver.

This is a fantastic opportunity to join a fast-growing, engineering-led cloud consulting company that tackles some of the toughest challenges in the industry. At CloudWerx, every team member brings something unique to the table, and we foster a supportive environment that helps people do their best work. Our goal is simple: to be the best at what we do and help our clients accelerate their businesses through world-class cloud solutions.

This role is an immediate full time position.  

Insight on your impact

• Conceptualize, Prototype, and Implement AI Solutions: Design and deploy advanced AI solutions using large language models (LLMs), diffusion models, and multimodal AI systems by leveraging Google Cloud tools such as Vertex AI, AutoML, and AI Platform (Agent Builder). Implement Retrieval-Augmented Generation (RAG) pipelines for chatbots and assistants, and create domain-specific transformers for NLP, vision, and cross-modal applications. Utilize Document AI, Translation AI, and Vision AI to develop full-stack, multimodal enterprise applications.
• Technical Expertise: models via LoRA, QLoRA, RLHF, and Dreambooth. Build multi-agent systems using Agent Development Kit (ADK), Agent-to-Agent (A2A) Protocol, and Model Context Protocol (MCP). Provide thought leadership on best practices, architecture patterns, and technical decisions across LLMs, generative AI, and custom ML pipelines, tailored to each client’s unique business needs.
• Stakeholder Communication: Effectively communicate complex AI/ML concepts, architectures, and solutions to business leaders, technical teams, and non-technical stakeholders. Present project roadmaps, performance metrics, and model validation strategies to C-level executives and guide organizations through AI transformation initiatives.
• Understand client analytics & modeling needs:Collaborate with clients to extract, analyze, and interpret both internal and external data sources. Design and operationalize data pipelines that support exploratory analysis and model development, enabling business-aligned data insights and AI solutions.
• Database Management: Work with structured (SQL/BigQuery) and unstructured (NoSQL/Firestore, Cloud Storage) data. Apply best practices in data quality, versioning, and integrity across datasets used for training, evaluation, and deployment of AI/ML models.
• Cloud Expertise: Architect and deploy cloud-native AI/ML solutions using Google Cloud services including Vertex AI, BigQuery ML, Cloud Functions, Cloud Run, and GKE Autopilot. Provide consulting on GCP service selection, infrastructure scaling, and deployment strategies aligned with client requirements. 
• MLOps & DevOps: Lead the implementation of robust MLOps and LLMOps pipelines using TensorFlow Extended (TFX), Kubeflow, and Vertex AI Pipelines. Set up CI/CD workflows using Cloud Build and Artifact Registry, and deploy scalable inference endpoints through Cloud Run and Agent Engine. Establish automated retraining, drift detection, and monitoring strategies for production ML systems.
• Prompt Engineering and fine tuning: Apply advanced prompt engineering strategies (e.g., few-shot, in-context learning) to optimize LLM outputs. Fine-tune models using state-of-the-art techniques including LoRA, QLoRA, Dreambooth, ControlNet, and RLHF to enhance instruction-following and domain specificity of generative models.
• LLMs, Chatbots & Text Processing:Develop enterprise-grade chatbots and conversational agents using Retrieval-Augmented Generation (RAG), powered by both open-source and commercial LLMs. Build state-of-the-art generative solutions for tasks such as intelligent document understanding, summarization, and sentiment analysis. Implement LLMOps workflows for lifecycle management of large-scale language applications.
• Consistently Model and Promote Engineering Best Practices: Promote a culture of technical excellence by adhering to software engineering best practices including version control, reproducibility, structured documentation, Agile retrospectives, and continuous integration. Mentor junior engineers and establish guidelines for scalable, maintainable AI/ML development.