Top AWS Jobs in Pune

Supports and improves enterprise infrastructure across managed services environments. Administers Zabbix monitoring, Linux and Windows servers, Active Directory, virtualization, containers, Microsoft 365, databases, networking, and endpoint platforms. Provides Tier 2/3 support, incident and root-cause analysis, automation, documentation, and continuous improvement while supporting multiple customer environments.

Monitor and support a multi-cloud infrastructure across Azure and AWS, including Windows, Linux, and SQL Server systems. Responsibilities include incident response, alert triage, patching, compliance tracking, network troubleshooting, reliability reporting, runbook improvement, and automation. The role participates in a follow-the-sun on-call rotation and supports VPNs, DNS, subnets, routing, monitoring tools, and infrastructure maintenance.

Leads cloud platform architecture, reliability, modernization, automation, cost optimization, and operational excellence across Azure-based SaaS infrastructure with some AWS. Manages and develops cloud and database engineers, establishes observability and incident-response practices, improves CI/CD, supports highly available systems, and partners with engineering, product, and security teams. The role remains hands-on with Infrastructure-as-Code while overseeing hiring, performance management, capacity planning, and technical strategy.

Own and mature the organization's governance, risk, and compliance program. Responsibilities include maintaining policies and risk registers, conducting risk and vendor assessments, managing control libraries, coordinating audits, testing controls, tracking remediation, administering GRC platforms, responding to security questionnaires, and supporting privacy and incident response compliance. The role advises leadership and cross-functional teams while monitoring regulatory and framework changes.

Owns and modernizes Litmos’s Microsoft Azure environment, including infrastructure, networking, governance, security, cost optimization, and cloud-native migrations. Administers SQL Server and supports PostgreSQL, Synapse, and Azure AI Foundry platforms. Builds Infrastructure as Code with Bicep, automates operations using PowerShell and Python, improves CI/CD, strengthens observability and disaster recovery, and supports GDPR compliance across a distributed US/Australia team.

Own end-to-end security incident response during non-US hours, including alert triage, investigation, containment, remediation, root cause analysis, documentation, and escalation. Maintain SOC playbooks and runbooks, produce incident reports and metrics, improve tooling and automation, and coordinate handoffs with US-based security staff. Investigate events across SIEM, EDR, email, network, identity, and cloud platforms while serving as the primary security operations contact for India-based stakeholders.

Identify, triage, and remediate vulnerabilities in web applications and proprietary software. Refactor .NET/C# code, implement secure coding standards, conduct code reviews, support secure SDLC practices, and assess SAST, DAST, penetration testing, and bug bounty findings. Monitor emerging threats and OWASP Top 10 updates while supporting compliance with FERPA, COPPA, GDPR, UK GDPR, and other data protection standards. The role is fully remote but requires permanent residency in India and specified IST working hours.

Supports design, implementation, operation, and maintenance of multi-cloud platforms across GCP, AWS, and Azure. Responsibilities include cloud infrastructure automation, monitoring, incident management, security and compliance, backup and disaster recovery, system administration, outage analysis, and operational process improvement. The role also partners with application and product teams, supports CI/CD and configuration management, and provides 24/7 cloud hosting operations.

Own the reliability, scalability, security, observability, and operational readiness of production AI/ML, GenAI, RAG, and agentic AI platforms. Define SLOs, monitor services, lead incident response, automate infrastructure and deployment workflows, implement CI/CD, observability, evaluation, governance, security, and cost controls, and support resilient cloud-native AI operations. Mentor engineers and collaborate with AI, platform, security, product, and business stakeholders.

Own, audit, validate, optimize, and modernize statistical models written in R. Build and deploy new predictive models and analytical features, improve production code quality, collaborate with data engineering, communicate technical findings to stakeholders, and mentor junior data scientists. The role requires advanced statistical modeling expertise, strong R proficiency, and experience improving complex algorithms.

Lead ML engineering for Operational Intelligence: design and productionize multimodal transformer and agentic systems, build scalable RAG/Graph-RAG and LLMOps/MLOps pipelines, implement inference services and memory/state subsystems, apply traditional and deep learning methods, enforce Responsible AI, and drive research-to-production innovation.

The Enterprise Architect will design R&D IT solutions, enhance analytics platforms, ensure regulatory compliance, and mentor teams while collaborating with multiple stakeholders.

Develop, train, deploy, and maintain machine learning and generative AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Design scalable ETL pipelines, optimize databases, process large datasets with Spark and Snowflake, and create business visualizations. The role requires expertise across Python, SQL, cloud AI platforms, machine learning frameworks, databases, and data engineering.

Architects and develops scalable generative and agentic AI solutions for enterprise clients. Responsibilities include translating business requirements into technical designs, defining architecture and non-functional requirements, evaluating technologies through proofs of concept, reviewing designs and code, and ensuring scalable, secure, maintainable production deployments on Azure or AWS. The role requires deep LLM, RAG, prompt engineering, model tuning, evaluation, anomaly detection, API development, and cross-functional collaboration experience.

Architects and develops scalable generative AI and agentic AI solutions for enterprise clients. Responsibilities include translating business requirements into technical designs, selecting architectures and technologies, defining non-functional requirements, reviewing code and architecture, conducting proofs of concept, and resolving technical issues. The role requires production-grade Python development, RAG and prompt engineering expertise, model fine-tuning and evaluation, cloud deployment on Azure or AWS, API development, and cross-functional collaboration.

Designs and evolves highly scalable backend systems, APIs, distributed workflows, databases, messaging infrastructure, and observability solutions. Leads cross-team architecture initiatives, resolves complex production issues, optimizes performance and data access, establishes reliability and engineering standards, modernizes technical debt, mentors engineers, and remains hands-on with critical systems.

Design, develop, and maintain cloud-native microservices in Java; deploy containerized applications on AWS EKS; work with Aurora/PostgreSQL, Redis; troubleshoot production issues; contribute to architecture and CI/CD.

Build and support scalable healthcare data platforms, unified data models, datasets, and ad hoc data access solutions. Extract and integrate heterogeneous healthcare data, improve data quality, support acquisitions, and model data for BI, software applications, machine learning, and AI. Collaborate with product, engineering, business, and clinical stakeholders while following software development lifecycle best practices.

Leads systems engineering for middleware and distributed platforms, including OpenShift and Kubernetes deployments, CI/CD automation, cloud infrastructure, application onboarding, SSL certificate lifecycle management, security patching, performance monitoring, troubleshooting, and platform integration. Collaborates across teams to resolve technical issues, improve system reliability, and ensure applications meet performance and security standards.

Design and lead enterprise cloud data architecture using Snowflake, including data models, ingestion, transformation, governance, security, performance, and cost optimization. Guide data engineers, select and integrate tools such as dbt, Airflow, and Kafka, establish architecture standards, and collaborate with engineering, analytics, business, and leadership teams. The role also oversees AWS cloud architecture, documentation, data quality, and scalable analytics platforms.

Lead the architecture and hands-on development of AI agents that execute end-to-end payment transactions across multiple markets. Design agent orchestration, transaction workflows, integrations, security controls, exception handling, and deterministic payment logic. Build primarily with Python and LLMs, integrate payment platforms and enterprise services, lead testing and transaction validation, and mentor engineers. Requires deep software architecture, payments, distributed systems, cloud, and AI agent engineering expertise.

Provides L1/L2 desktop and endpoint support, including device setup, onboarding, troubleshooting, remote assistance, imaging, asset tracking, and access provisioning. Maintains endpoint security, patching, encryption, and compliance controls while monitoring SIEM/EDR alerts. Supports incident response, vulnerability remediation, phishing and malware investigations, cloud security reviews, documentation, and coordination with infrastructure and security teams. This hybrid role is based in New Delhi and requires office attendance two days weekly.

Leads change and release engineering across CI/CD, traditional, and vendor-led environments. The role automates deployments, establishes risk-based governance, improves production-change visibility, analyzes change failures and DORA metrics, and reduces major incidents. It also owns CAB processes, compliance reporting, rollback and testing controls, AI-enabled workflows, process documentation, and leadership reporting while coaching a small team of Change Managers.

Senior Java Engineer responsible for designing, developing, and maintaining scalable Treasury Technology applications. The role includes backend development, high-volume data processing, ETL, real-time reporting, batch processing, performance tuning, architectural problem-solving, testing, and cloud integration. The engineer will establish technical standards, guide developers, support Agile delivery, and ensure solutions meet functional, non-functional, architectural, quality, and maintainability requirements. Experience with Java, Spring, Oracle, PL/SQL, Spark, Hadoop, and cloud platforms is required.

Develop NLP and generative AI models for text classification, sentiment analysis, entity recognition, translation, and semantic analysis. Responsibilities include text preprocessing, feature engineering, model training and evaluation, exploratory data analysis, algorithm optimization, and large-scale data processing. Collaborate with engineering and domain teams to integrate solutions, document methodologies, and apply emerging NLP and machine learning techniques.