**Urgent**Senior AI/ML Engineer| Machine Learning| Deep Learning| Generative AI| 5-10 Years| Hyderabad Location

About Senzcraft:

Senzcraft is an Enterprise AI Product & Services company. We are on a mission to engineer the touchless enterprise: organisations where routine work runs itself, decisions are faster, and people spend their time on what truly matters. We combine AI, automation and deep engineering to turn complex business processes into intelligent, self-running systems.

We are a team of builders who care about craft, clarity and real-world impact. If you want your code to run in production and move real numbers for real businesses, you will feel at home here.

What You’ll Be Doing

We are seeking a highly skilled Senior AI/ML Engineer to lead the design, development, deployment, and governance of enterprise-scale AI solutions. This role will be responsible for building scalable AI/ML platforms, Generative AI applications, Retrieval-Augmented Generation (RAG) solutions, agentic workflows, and real-time data pipelines that deliver measurable business value. The ideal candidate combines deep technical expertise with the ability to align AI initiatives to strategic business objectives. This role will report to the Global head of AI & Innovation and collaborate closely with the Data & Analytics, Enterprise architecture and Integrations, Information security, Legal & Data privacy teams.

How You’ll Succeed (Roles & Responsibilities)

Success in this role requires both strong execution and the ability to operate effectively in a global, evolving environment. You will:

AI Solution Engineering & Architecture

• Design, develop, and deploy end-to-end AI/ML solutions, including microservices, RAG architecture, and agentic AI workflows.

• Build scalable and reusable AI services that support enterprise-wide business use cases.

• Evaluate and integrate emerging AI technologies, frameworks, and foundation models.

MLOps, Data Science & Advanced Analytics

• Implement and maintain MLOps pipelines for model training, deployment, monitoring, versioning, and lifecycle management.

• Automate model deployment, performance monitoring, and drift detection processes.

• Optimize AI workloads for cost, scalability, and performance across Azure and AWS cloud platforms.

• Design, develop and deploy scalable, secured, predictive statistical ML models to continuously empower business functions.

Real-Time Data Engineering

• Build low-latency data ingestion, processing, and orchestration pipelines supporting AI applications.

• Design and maintain vector databases, knowledge repositories, and semantic search capabilities.

• Enable real-time analytics and AI-driven decision-making using large-scale operational and transactional data.

AI Governance, Security & Responsible AI

• Implement security-by-design principles across AI solutions and data platforms.

• Protect sensitive financial and operational data through robust access controls and governance frameworks.

• Mitigate risks related to prompt injection, hallucinations, data leakage, bias, and regulatory compliance.

• Ensure adherence to Responsible AI, privacy, and enterprise security policies.

Business Partnership & Value Realization

• Collaborate with business leaders, product teams, and solution architects to identify high-value AI opportunities.

• Translate business problems into scalable AI solutions that drive operational efficiency, growth, and innovation.

• Measure and communicate business outcomes, model performance, and ROI from AI initiatives.

Experience

• Bachelor's or master’s degree in computer science, Data Science, Engineering, Artificial Intelligence, or related field.

• 5+ years of experience in AI/ML engineering, software engineering, data engineering, or cloud-based solution development.

• Hands-on experience with Generative AI, LLMs, RAG frameworks, AI agents, and vector databases.

• Strong foundation in statistics, predictive modeling, and machine learning.

• Experience selecting and implementing appropriate algorithms based on business objectives, data characteristics, and performance requirements.

• Strong proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, LangChain, Semantic Kernel, etc.).

• Experience with Azure AI Services, AWS AI/ML services, and cloud-native architectures.

• Knowledge of MLOps, CI/CD, containerization (Docker/Kubernetes), and modern software engineering practices.

• Familiarity with supervised and unsupervised learning techniques, including: o Predictive: Regression, Classification o Tree-Based: Decision Trees, Random Forests, XGBoost, LightGBM • Forecasting & Recommendations • Deep Learning & Neural Networks • Reinforcement Learning o Unsupervised: Clustering, Segmentation

• Ability to interpret model results and translate insights into business recommendations.