Solutions Architect

EdgeVerve; Pune District; On-site; INR 5,000,000 - 8,000,000; Full time

Job summary

EdgeVerve Systems Limited is building AI Next, a unified platform to scale Applied AI across enterprises. The role leads scalable architecture for secure, compliant AI-enabled solutions and data platforms, partnering with stakeholders to deliver enterprise-grade results.

The candidate will drive DataOps/MLOps practices, mentor teams, and ensure governance, security, and performance across cloud-native microservices and API-led integrations.

Qualifications

• Strong expertise in cloud-native, microservices-based architectures.
• Hands-on knowledge of performance optimization, technical design reviews, DevOps, and CI/CD practices.
• Solid understanding of database design and management, data formats such as JSON, XML, and Avro.
• Experience with analytics and data platforms, query optimization, and designing data pipelines.
• Knowledge of security, compliance, data governance, privacy, explainability, and audit requirements.
• Proficiency in Java, Python, or C++, with integration patterns including APIs and events.
• Knowledge of ML, deep learning frameworks such as TensorFlow and PyTorch, LLMs, RAG, and vector stores.
• Experience with MLOps and AI operationalization, including deployment, monitoring, retraining, and production support.

Responsibilities

• Design and lead scalable, secure, and reliable technology architectures aligned with business goals and enterprise standards.
• Partner with stakeholders and cross-functional teams to translate requirements into technical solutions and act as the primary technical contact.
• Provide technical leadership through mentoring, governance, and enforcement of best practices and architectural guidelines.
• Drive solution quality through testing, performance tuning, monitoring, and collaboration with support teams to minimize downtime.
• Define AI/ML and data architecture patterns for product integration, including model integration and data pipelines.
• Ensure AI and data solutions meet governance, privacy, security, explainability, lineage, and cost-effective scalability.
• Guide DataOps and MLOps practices across the solution lifecycle, including deployment, retraining, validation, and release governance.

Skills

Cloud-native architecture

Microservices

DevOps

CI/CD

Data governance

MLOps

AI/ML architecture

TensorFlow

PyTorch

Large Language Models

RAG

vector stores

prompt orchestration

security and governance

Java

Python

C++

Tools

Docker

Kubernetes

CI/CD tooling

APIs

Event-driven design

Data streaming

Databases

JSON/XML/Avro

Job description

EdgeVerve Systems Limited (a wholly owned subsidiary of Infosys) builds AI-, automation-, and analytics-led digital platforms that help enterprises transform operations at scale, with security and scalability at the core

About AI Next

EdgeVerve AI Next is a unified platform designed to scale Applied AI across the enterprise, built from the ground up to leverage Generative AI and bridge silos across people, processes, data, and technology to drive transformation in business operations.

AI Next also includes platform capabilities that support flexible model choices and enterprise-ready foundations for secure, scalable deployments

Experience : 12-20 years

Notice Period - 60days to immediate joiner.

JOB Description:

Responsibilities

• Design and lead scalable, secure, and reliable technology architectures that align with business goals and enterprise standards.
• Partner with stakeholders, business leaders, and cross-functional teams to gather requirements, translate them into technical solutions, and serve as the primary technical point of contact.
• Provide technical leadership through mentoring, governance, and the enforcement of best practices, coding standards, and architectural guidelines.
• Drive solution quality and operational excellence through testing, performance tuning, monitoring, troubleshooting, and collaboration with support teams to minimize downtime.
• Define AI/ML and data architecture patterns for product integration, including model integration, inference workflows, data pipelines, API-led integration, event-driven components, and interoperability with enterprise platforms.
• Ensure AI and data solutions meet enterprise requirements for governance, privacy, security, explainability, traceability, lineage, auditability, resiliency, disaster recovery, and cost-effective scalability.
• Guide the adoption of DataOps and MLOps practices across the solution lifecycle, including deployment, monitoring, retraining, validation, versioning, release governance, and ongoing optimization.

Skill requirements

• Strong expertise in technical architecture design for cloud-native, microservices-based, and containerized enterprise systems.
• Hands-on knowledge of performance optimization, technical design reviews, DevOps, and CI/CD practices for scalable and reliable solution delivery.
• Solid understanding of database design and management, data formats such as JSON, XML, and Avro, and enterprise data architecture including modeling, integration, quality, metadata, and lineage.
• Experience with analytics and data platforms, query optimization, and designing streaming, batch, and enterprise-scale data pipelines.
• Good knowledge of security, compliance, data governance, privacy, explainability, and audit requirements for enterprise technology and AI-enabled solutions.
• Proficiency in programming languages such as Java, Python, or C++, along with knowledge of process automation and modern integration patterns including APIs and event flows.
• Knowledge of machine learning, deep learning frameworks such as TensorFlow and PyTorch, Large Language Models, RAG, vector stores, prompt orchestration, and responsible AI controls.
• Experience with MLOps and AI operationalization, including feature engineering workflows, model lifecycle management, deployment, evaluation, drift monitoring, retraining, and production support.