Top AWS Jobs in Pune

Lead incident response, threat hunting, and forensic investigations across corporate, cloud, and product environments. Conduct cloud and container forensics, malware analysis, build detections and automation, collaborate with engineering to remediate vulnerabilities, and improve security posture using frameworks like MITRE ATT&CK.

Partner with sales teams to win and expand enterprise customers by owning technical sales activities. Assess customer requirements, conduct product demonstrations and proofs of value, respond to RFPs and RFIs, build stakeholder relationships, and communicate Chainguard’s security benefits. The role also supports webinars, conferences, marketing initiatives, feature requests, and customer education while serving as a trusted technical advisor.

Lead design, deployment, migration, optimization, and troubleshooting of Cisco security solutions. Architect HLD/LLD, validate designs, build lab simulations, leverage AI/automation, support presales, mentor team members, and drive continuous improvement.

Lead MEA technical risk activities to ensure regulatory alignment (UAE PDPL, DIFC, SAMA CSF, NCA ECC, POPIA), integrate global frameworks (NIST CSF 2.0, ISO27001, COBIT), define KRIs/KPIs, run RCSA, drive remediation and audit readiness (PCI DSS, SOX 404), coordinate stakeholders and regulators, and provide decision-ready inputs to the Group CISO and Technology Risk Forum.

Develop, deploy, and maintain scalable AI/ML pipelines and production systems, including LLMs and generative AI models. Collaborate with data scientists, software engineers, architects, and clients to integrate AI capabilities into products. Optimize model performance, latency, and cost on AWS, GCP, and Azure, using Docker, Kubernetes, CI/CD, monitoring, versioning, and other MLOps practices.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Own the architecture and delivery of production-grade generative and agentic AI systems, including LLM agents, RAG pipelines, multi-agent workflows, APIs, and cloud-native services. Establish AI engineering, evaluation, observability, guardrail, and LLMOps practices while mentoring AI/ML and backend engineers. Collaborate with Product, Data, Platform, Security, and Compliance teams to deliver scalable, secure, and business-ready solutions, and provide technical direction on GenAI strategy and architecture.

Serve as a techno-functional business analyst: gather and translate requirements, design functional specifications, support integrations and data flows (APIs, databases, cloud), collaborate with architects and developers, support UAT and deployment, and drive process improvements and change management for digital transformation initiatives.

Design and build data pipelines and analytics to extract actionable insights, apply advanced analytics/ML, create dashboards, and drive platform performance, reliability, and DevSecOps for high-throughput payment systems. Collaborate with stakeholders, influence technical strategy, and ensure controls, scalability, and operational resilience.

Manage and support plant IT infrastructure, including Windows and Linux servers, Active Directory, networking, virtualization, backups, monitoring, security, and disaster recovery. Provide L2/L3 user support, maintain system availability, troubleshoot connectivity and performance issues, coordinate with vendors and ISPs, support onboarding and offboarding, and ensure documentation, compliance, audit readiness, and minimal operational downtime.

Designs, builds, and maintains ETL/ELT pipelines feeding Microsoft Fabric Lakehouse platforms. Responsibilities include data ingestion, bronze/silver/gold layer development, CDC, incremental loading, data quality, metadata governance, performance tuning, monitoring, automation, and low-level design documentation. The role collaborates with architects, data modelers, and business analysts to deliver reliable, reusable datasets and promote self-service analytics while applying security, resilience, compliance, and cost-optimization standards.

Leads customer-facing design and implementation of cloud, platform, infrastructure, data, and AI solutions. Responsibilities include cloud migration and modernization, Infrastructure as Code, CI/CD, Kubernetes, automation, GitOps, platform security, observability, and AI-assisted development. The consultant conducts workshops, creates reusable platform capabilities, enables responsible AI adoption, mentors engineers, supports proposals and pre-sales, and ensures secure, reliable, governed, and cost-effective production solutions.

Build and maintain production-grade full-stack web applications using Node.js, Express.js, React.js, Next.js, and AWS. Design payment, billing, invoicing, subscription, refund, and reconciliation workflows; develop secure APIs and transactional data models; improve repositories and Git workflows; support deployments, monitoring, debugging, refactoring, documentation, and architectural discussions. Collaborate with distributed product, design, QA, and business teams while using AI-powered development tools to accelerate delivery and resolve issues.

Develop and maintain production-grade full-stack web applications using Node.js, Express.js, React.js, Next.js, and AWS. Build payment, billing, invoicing, subscription, refund, and reconciliation workflows with secure APIs and transactional data models. Manage Git branching, code quality, documentation, deployments, monitoring, and issue resolution. Collaborate with product, design, QA, and business teams in a remote Agile environment while using AI development tools to accelerate coding, debugging, refactoring, and testing.

Design, develop, test, and deploy cloud-based SaaS applications; modernize and refactor existing systems; implement CI/CD, containerization, logging, and monitoring; support AWS deployments and SOC2-aligned secure coding; participate in on-call rotation, code reviews, documentation, and cross-functional collaboration to deliver scalable, maintainable features.

Lead design and support of analytical data infrastructure and real-time data pipelines on AWS. Build ETL, data modeling, warehousing, and BI solutions; collaborate on analytics and machine learning integrations; automate reporting and improve self-service access.

Lead design and implementation of scalable, low-latency equities trading systems. Hands-on Java development, provide technical guidance, enforce code quality, mentor engineers, collaborate with global stakeholders, and drive CI/CD, cloud, and DevOps practices to meet performance, reliability, and business requirements.

Senior technical leader responsible for engineering strategy, platform architecture, and delivery across multiple teams. Owns roadmap and standards for Java-based microservices, event-driven/streaming platforms (Kafka), cloud-native infrastructure (AWS, EKS), data stores, and CI/CD. Partners with senior business stakeholders, mentors senior engineers, and resolves complex cross-cutting platform challenges.

Senior engineering leader accountable for platform-scale architecture, technical strategy, and delivery across Java-based microservices and event-driven systems (Kafka). Owns org-wide architecture, tooling, standards, cloud/container platforms (AWS/EKS), data architecture, and alignment with senior business stakeholders while remaining hands-on for design reviews and incident response.

Senior technical leader responsible for engineering strategy, platform-scale architecture, and delivery across multiple teams. Owns technical roadmap for shared services, champions event-driven architectures (Kafka), provides hands-on guidance for Java microservices, ensures reliability, observability, and security, and partners with senior business and technology stakeholders to drive execution and scalability.

Design, build, and maintain production data pipelines and models using Python and SQL. Improve data architectures (Kafka, warehouses, ODS), optimize SQL performance, perform data cleaning and analysis, select data sources, and collaborate with partners to support cloud-based analytics (Snowflake, AWS SageMaker) and workflow tools like Airflow.

Develop, fine-tune, deploy, and optimize AI/ML models and LLM-based RAG solutions using Python and AWS Bedrock. Build REST APIs and microservices with FastAPI or Flask, deploy scalable cloud infrastructure, manage containerized workloads, and develop data pipelines and ETL processes. Work with relational and NoSQL databases, CI/CD, and AWS services while collaborating with technical and product teams and documenting AI workflows.

Develop and maintain ScienceLogic’s internal developer platform, including Kubernetes environments, CI/CD pipelines, container tooling, and infrastructure-as-code. Collaborate with development teams to understand workflows, enforce software engineering and container best practices, evaluate technologies, and contribute to architecture decisions. The role also involves documenting standards, supporting observability and logging, and implementing DevSecOps practices such as secure build pipelines and compliance automation.

Lead strategic design, architecture, and hands-on implementation of Elastic Stack and Search AI solutions for enterprise customers. Conduct workshops, gather requirements, develop proofs of concept, optimize queries and clusters, and deliver scalable search platforms. Manage project objectives, dependencies, timelines, and customer relationships. Collaborate with engineering, product, support, and sales teams, provide product feedback, assess technical risks, and mentor team members. Periodic client-site travel of up to 20% is required.

Design and implement scalable Elastic Stack observability and Search AI solutions for enterprise customers. Lead workshops, requirements gathering, architectural planning, proofs of concept, data modeling, query optimization, cluster tuning, and end-to-end project delivery. Advise customers, manage engagement timelines and dependencies, collaborate with engineering and product teams, support presales scoping, and mentor consultants. The role requires hands-on cloud, infrastructure, networking, security, containerization, automation, and programming experience, with periodic client-site travel up to 20%.