Top AWS Jobs in Hyderabad

Develop scalable and secure backend systems using Node.js, TypeScript, AWS serverless services, REST and GraphQL APIs. Responsibilities include database design, authentication and authorization, API optimization, CI/CD pipeline management, production monitoring, troubleshooting, testing, documentation, and collaboration with frontend and product teams.

Own the architecture, automation, security, scalability, and operation of hybrid infrastructure across on-premises datacenters and AWS. Lead hosting pipeline improvements, infrastructure design, observability, virtualization, deployment automation, and structured change management. Collaborate with engineering and product teams, communicate technical trade-offs, optimize platform reliability, and mentor hosting personnel.

Resolves critical technical issues for high-value customers through root cause analysis, advanced network troubleshooting, bug reproduction, testing, and engineering collaboration. Supports cloud networking environments, Linux systems, automation, QA, documentation, and customer communication. The role also contributes to feature feedback, support content, and off-hours escalation coverage.

Develop, test, and maintain high-performance web applications with Next.js and React. Build responsive interfaces from UI/UX designs, integrate RESTful or GraphQL services, and optimize applications for speed, scalability, SEO, and accessibility. Collaborate with designers, backend engineers, and product managers to deliver features, resolve technical issues, participate in code reviews, and improve development standards.

Develop, test, and maintain high-performance web applications using Next.js and React. Translate designs into responsive interfaces, integrate RESTful or GraphQL services, optimize SEO and performance, resolve technical issues, and write reusable code. Collaborate with designers, backend engineers, and product managers on feature delivery, participate in code reviews, and contribute to development standards. The role also involves testing, CI/CD, deployment, and staying current with frontend technologies.

Design, build, and operate AWS and Kubernetes infrastructure powering production AI systems. Own CI/CD, infrastructure as code, GitOps, observability, secrets management, GPU workloads, model serving, reliability, security, scalability, and cost optimization. Troubleshoot production incidents, perform root-cause analysis, and develop automation using Python and Bash while collaborating across Engineering, ML/AI, Security, and Product teams.

Develop and maintain scalable backend and full-stack systems using Node.js, MySQL, Redis, REST, and GraphQL. Responsibilities include system architecture, microservices, API development, testing, CI/CD, deployment, performance optimization, production troubleshooting, documentation, and code reviews. The role collaborates remotely with product and design teams and requires familiarity with cloud platforms, Docker, native mobile development, and database technologies.

Develop and maintain production-ready Flutter mobile applications for iOS and Android. Responsibilities include responsive UI development, algorithm and performance optimization, testing, debugging, app deployment, production monitoring, and collaboration with designers, product managers, and backend developers. The role requires Flutter and Dart expertise, API and state-management experience, Firebase, CI/CD, Git, cloud, database, native development, and Docker familiarity.

Design and implement enterprise data architectures spanning data lakes, warehouses, data fabric, and MDM. Build scalable pipelines and integration frameworks, establish governance and data quality standards, enable AI/ML initiatives, develop data strategies, and optimize platforms for performance, scalability, and reliability. Collaborate with business and technology stakeholders across the organization.

Build and maintain reliable, scalable cloud infrastructure for Kubernetes-based distributed database systems on AWS and Google Cloud. Develop Golang automation, optimize CI/CD pipelines, implement monitoring and observability, troubleshoot complex infrastructure issues, and design disaster recovery and high-availability strategies. Participate in on-call support, incident response, and cross-functional efforts to improve system reliability and resolve customer issues.

Develop and maintain Java applications on AWS, build REST and enterprise API integrations, and implement serverless workflows with Lambda and Step Functions. Configure messaging through SNS/SQS, manage DynamoDB and S3 resources, provision infrastructure using CloudFormation or CDK, and monitor systems with CloudWatch. Apply IAM security practices, troubleshoot cloud applications, collaborate with development, architecture, and client teams, and follow deployment and monitoring best practices.

Lead end-to-end SAP migration projects from on-premises environments to AWS, including planning, execution, cutover, validation, and technical delivery. Manage SAP Basis across ECC, S/4HANA, and BW landscapes; perform OS and database migrations using SUM DMO and SWPM; administer HANA and AnyDB environments; design AWS infrastructure; and oversee performance, capacity, HA/DR, replication, backup, recovery, and complex troubleshooting.

Develop and maintain scalable full-stack web applications using Python and modern frontend technologies. Build REST APIs, microservices, and serverless applications; manage relational and NoSQL databases; deploy applications to cloud platforms; and follow coding, testing, version control, and CI/CD best practices. Collaborate with cross-functional teams throughout the software development lifecycle.

Lead the design and delivery of AI/ML and Generative AI solutions, including RAG systems, LLM applications, prompt-driven agents, automation pipelines, and proof-of-concepts. Develop and fine-tune models, evaluate AI frameworks and cloud services, establish responsible AI practices, guide technical best practices, collaborate with stakeholders, and ensure enterprise security and compliance.

Leads the design, development, deployment, and optimization of scalable AI/ML solutions, including generative AI, LLM, NLP, and RAG applications. Drives architecture and solution design, develops production-ready models, collaborates with engineering and R&D teams on proofs of concept and deployments, ensures application scalability and reliability, and mentors engineers.

Develop AI applications using Python, generative AI, LLMs, RAG, vector databases, APIs, and agentic AI frameworks. Build and integrate solutions with models including GPT, Claude, Gemini, and Llama. Use LangChain, LangGraph, Docker, cloud platforms, and modern deployment tools. The role requires strong problem-solving, API development, prompt engineering, and immediate or short-notice availability for office-based work.

Develop modern generative AI applications using LLMs, retrieval-augmented generation, vector databases, prompt engineering, and agentic AI. Build APIs and production systems with Python, FastAPI, LangChain, LangGraph, Docker, and cloud platforms. Responsibilities may include integrating major LLM providers, implementing function calling, embeddings, evaluation frameworks, guardrails, monitoring, and fine-tuning. The role is full-time, office-based, and requires immediate or short-notice availability.

Develop enterprise applications using .NET and .NET Core 8.0, design microservices and REST APIs, integrate AWS cloud services, apply software design patterns, and implement AI integrations. The role involves working from the Hyderabad office five days per week during a 1:00 PM–10:00 PM shift. Lead or technical lead experience, cloud-based application architecture, and immediate availability are advantageous.

Design, develop, and optimize scalable applications using .NET Core 8.0, microservices, and AWS. Apply design patterns and coding best practices, build AI-enabled integrations, troubleshoot performance issues, and contribute to architecture and technical decisions while collaborating with cross-functional teams.

Lead end-to-end AI Data Assurance and Quality Engineering programs, managing scope, timelines, budgets, risks, resources, governance, testing frameworks, quality metrics, and release readiness. Collaborate with business, data engineering, architecture, and AI/ML teams while mentoring quality and assurance teams. Drive automation, AI-assisted testing, workforce planning, client pursuits, solutioning, capability development, innovation, and practice growth.

Lead the development of enterprise AI solutions using Generative AI, LLMs, RAG, and Agentic AI. Build AI applications, chatbots, and retrieval systems using embeddings and vector databases. Apply machine learning frameworks, deploy and monitor AI models, establish CI/CD pipelines, and design scalable enterprise AI architectures across cloud platforms.

Leads the development of scalable, production-ready AI solutions using machine learning, generative AI, NLP, deep learning, neural networks, and cloud AI platforms. The role requires Python, TensorFlow, PyTorch or Keras, prompt engineering, Hugging Face, spaCy or NLTK, and data visualization tools. It also involves applying statistical modeling, working with Agile/Scrum methodologies, and collaborating with stakeholders.

Lead development of scalable enterprise applications using Python, REST APIs, SQL/PostgreSQL, FastAPI or Flask, and microservices. The role involves guiding technical delivery and may use Django, PySpark, GraphQL, Elasticsearch, Hadoop, AWS, CI/CD, testing frameworks, and Git. This is a hybrid Hyderabad role requiring four office days weekly, with a 12 PM–9 PM shift and immediate-to-15-day availability.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Design, build, optimize, and operate scalable, low-latency backend services for an AI risk decisioning SaaS platform. Collaborate with product, frontend, and QA teams; implement testing and CI/CD practices; monitor service health; resolve performance bottlenecks; and mentor junior engineers.