Senior Data Engineer

SG Analytics; Mumbai; On-site; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Growth opportunities

Flexible work arrangements

Professional development

Collaborative culture

Job summary

SG Analytics in Mumbai is seeking an AI Engineer specializing in MLOps and AIOps to deploy, operate, and optimize enterprise-ready AI solutions built on Azure.

You will collaborate with AI Developers, Product Owners, Governance leaders, and Cloud Architects to ensure reliable, scalable deployments that are secure, observable, and governance-compliant across client-facing applications.

Qualifications

• Bachelor's degree in a related technical field.
• 3+ years in MLOps and/or AIOps, preferably in Azure.
• Hands-on experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry.

Responsibilities

• Model Deployment & Monitoring: Deploy and monitor AI models across Azure services with telemetry for performance, drift, and availability.
• Lifecycle & Rollout Management: Manage model upgrades including APIs and UIs with structured rollout, version control, and rollback support.
• Performance & Cost Optimization: Optimize performance and cost through testing, profiling, and tuning of inference infrastructure and pipelines.
• MLOps Pipeline Implementation: Implement MLOps pipelines for CI/CD and lifecycle management using Azure ML and GitHub Actions.
• Governance & Compliance: Ensure compliant change management for all AI deployments with auditability and security controls.

Skills

MLOps

AIOps

Azure

Telemetry & Monitoring

Model Deployment

CI/CD

Education

Bachelor's degree in Computer Science, Engineering, Data Science

Tools

Azure ML

Synapse

Data Lake

App Services

Cosmos DB

Azure AI Foundry

Job description

ABOUT US

SG Analytics (SGA), a Straive company, is a leading global data and AI consulting firm delivering solutions across AI, Data, Technology, and Research. With deep expertise in BFSI, Capital Markets, TMT (Technology, Media & Telecom), and other emerging industries, SGA empowers clients with Ins(AI)ghts for Business Success through data-driven transformation.

A Great Place to Work certified company, SGA has a team of over 1,600 professionals across the U.S.A, U.K, Switzerland, Poland, and India. Recognized by Gartner, Everest Group, ISG, and featured in the Deloitte Technology Fast 50 India 2024 and Financial Times & Statista APAC 2025 High Growth Companies, SGA delivers lasting impact at the intersection of data and innovation.

JOB DESCRIPTION

Join our fast-growing organization as we redefine how professional services harness the power of Artificial Intelligence. As an AI Engineer specializing in MLOps and AIOps, you will play a critical role in deploying, operating, and optimizing enterprise-grade AI solutions built on Azure.

You will collaborate closely with AI Developers, Product Owners, Governance leaders, and Cloud Architects to ensure these systems are reliable, scalable, and cost-effective across tax, audit, advisory, and client-facing applications. This role goes beyond traditional DevOpsit is about engineering AI into the fabric of enterprise operations, enabling secure, observable, and governed machine learning deployments that deliver real business impact.

ROLES & RESPONSIBILITIES

• Model Deployment & Monitoring: Deploy and monitor AI models across Azure services with robust telemetry for performance, drift, and availability.
• Lifecycle & Rollout Management: Manage model upgrades including APIs and UIs with structured rollout, version control, and rollback support.
• Performance & Cost Optimization: Optimize performance and cost through testing, profiling, and tuning of inference infrastructure and pipelines.
• MLOps Pipeline Implementation: Implement MLOps pipelines for continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions.
• Governance & Compliance: Ensure compliant change management for all AI-related deployments with auditability, security, and governance controls.

REQUIRED SKILLSET

• Education: Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• Experience: 3+ years in MLOps and/or AIOps, ideally within an Azure cloud environment.
• Cloud Platforms: Hands-on experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry.

PREFERRED QUALIFICATIONS (GOOD TO HAVE)

• Consulting & Execution: Consulting background with a strong bias for action.
• Workflow Design: Experience with Prompt flow, automation pipelines, and human-in-the-loop systems.
• Post-Training Techniques: Knowledge of fine-tuning, instruction tuning, RLHF, and domain adaptation.
• Azure Infrastructure & Security: Proficiency in Azure DevOps, App Insights, Log Analytics, Key Vault, and Managed Identity integration.
• Testing & Profiling: Familiarity with tools for inference performance testing and profiling (e.g., Locust, K6, or custom scripts).
• Model Evaluation: Knowledge of performance metrics, benchmark development, and A/B testing frameworks.
• Observability & Telemetry: Deep understanding of model observability, telemetry, and incident response for AI systems

WHAT WE OFFER?

About SG Analytics

SG Analytics (SGA) is a leading global insights and analytics company that provides data-centric research and contextual analytics services to companies worldwide. With a team of powerful analytics and industry experts, SGA helps businesses turn data into a competitive advantage by delivering data-driven insights across financial services, technology, media, and life sciences. Guided by a philosophy of growth and innovation, we offer an environment where technical expertise and creative problem-solving are valued and nurtured.

Perks & Culture

• Growth & Impact: Be part of a fast-growing industry leader where you can design a career you love and get the tools and autonomy you need to reach your goals.
• Work/Life Balance: Benefit from flexible day-to-day management that supports your personal and professional commitments.
• Award-Winning Culture: Join a collaborative team environment that celebrates diverse ideas, cultures, and experiences to create innovative solutions.
• Authenticity: Work in a supportive setting where showing up authentically inspires everyone to do their best work.