Jobs at Accenture

Designs and maintains data architecture for applications, including data requirements, models, storage, and system integration. Collaborates with cross-functional teams to align data strategies with business objectives, documents data models and integration processes, resolves architecture challenges, and mentors junior team members. Requires at least three years of Collibra Data Governance experience and strong knowledge of database design, data integration, storage solutions, and performance optimization.

Design and implement production-ready AI and machine learning applications using generative AI, LLMs, deep learning, neural networks, chatbots, and image processing. Deploy scalable solutions across cloud and on-premises infrastructure, optimize ML workflows, collaborate with stakeholders, make technical decisions, and mentor junior engineers.

Develop and enhance custom software components using Informatica PowerExchange, data integration techniques, real-time processing, and complex workflows. Collaborate across teams, make technical decisions, improve processes, troubleshoot data exchange systems, and mentor junior engineers while ensuring scalable, reliable, and high-performing solutions.

Design, build, test, and maintain Python-based web applications. Edit and update website content, document technical designs, troubleshoot performance issues, and implement enhancements. Collaborate with cross-functional teams to meet business and user requirements, follow secure coding practices, and support junior team members. The role requires proficiency in Python frameworks, familiarity with front-end technologies, version control, and web security principles.

Develop and enhance custom software solutions using Java and Spring Boot. Design scalable applications, build RESTful APIs, optimize database queries, troubleshoot software issues, and participate in agile development. Collaborate with cross-functional teams to gather requirements, document technical processes, contribute to solution design, and support junior team members through guidance and best practices.

Analyzes and improves business workflows using SAP S/4HANA for Product Compliance. Gathers requirements, develops use cases, designs monitoring and feedback mechanisms, and leads cross-functional process improvement efforts. Acts as a subject matter expert, supports team decisions, coordinates stakeholders, provides solutions, and mentors junior team members.

Develop and enhance custom software components using Spring Boot, RESTful APIs, agile practices, and scalable application design. Collaborate across teams, make technical decisions, troubleshoot performance issues, improve development processes, and mentor junior engineers. The role requires software development lifecycle knowledge, version control, continuous integration experience, and at least five years of Spring Boot experience.

Package, deploy, administer, and troubleshoot macOS applications and devices in an enterprise environment. Use Workspace ONE UEM and related tools to manage application lifecycles, deployment workflows, reporting, and device insights. Support Workspace ONE Access and Enterprise Connector issues, maintain documentation, collaborate with endpoint teams and vendors, and follow enterprise packaging, testing, security, compliance, and ITIL standards.

Develop, design, code, and enhance custom software components using modern frameworks and agile practices. Translate complex business requirements into scalable technical solutions, apply data modeling and database design techniques, optimize performance, and coordinate cross-functional delivery. Serve as a subject matter expert, make team-level decisions, establish development best practices, collaborate across teams, and mentor junior engineers.

Develop and enhance scalable full-stack enterprise applications using Java and modern frameworks. Build frontend and backend components, integrate AI services and APIs, implement RAG features, and use AI-assisted development tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while applying software engineering, SDLC, agile, quality, and CI/CD practices.

Designs, develops, and maintains data solutions, pipelines, and ETL processes using PySpark. Ensures data quality, reliability, and integrity across large datasets and systems. Troubleshoots distributed data-processing issues, documents workflows, collaborates with cross-functional teams, contributes to solution development, and guides junior team members. The role requires independent execution, subject-matter expertise, and at least three years of PySpark experience.

Develop full-stack enterprise applications using Java and modern frameworks, with front-end and back-end integration, AI-assisted development tools, and scalable engineering practices. Build and enhance software components, integrate AI services and APIs, implement RAG features, and collaborate with architects and AI specialists. The role requires strong SDLC and enterprise engineering knowledge, full-stack development experience, and the ability to use copilots and LLM-based coding assistants while maintaining quality.

Develop full-stack enterprise applications using Java and modern frameworks, including front-end and back-end components, APIs, databases, cloud-native technologies, and CI/CD pipelines. Use AI copilots and LLM tools for coding, debugging, testing, documentation, and RAG feature integration. Collaborate with architects and AI specialists to deliver scalable, high-quality software using agile and enterprise engineering practices.

Build agentic AI applications and production-ready software using LLM tooling, RAG pipelines, vector databases, API integrations, and modern development practices. Responsibilities include implementing agents, prompts, memory, evaluation loops, ingestion and embedding services, enterprise integrations, testing, observability, safety controls, CI/CD, rapid prototyping, and stakeholder communication. The role requires strong software engineering fundamentals, hands-on AI development experience, an AI project portfolio, and at least 7.5 years of Java full-stack development experience.

Develop full-stack enterprise applications using Java and modern frameworks, including front-end and back-end components, APIs, databases, cloud-native technologies, and CI/CD pipelines. Use AI copilots, LLM-based coding tools, and pre-built AI services to accelerate coding, testing, debugging, documentation, and integration. Collaborate with architects and AI specialists while delivering scalable, high-quality software solutions.

Develop, enhance, test, and maintain custom software components for multiple clients. Analyze requirements, design scalable solutions, write and review code, troubleshoot issues, and collaborate with cross-functional teams. The role requires expertise in payments fundamentals, software development lifecycle methodologies, APIs, integrations, and Git, along with independent ownership and contribution to technical discussions.

Build and productionize agentic AI applications using LLM tooling, RAG pipelines, vector search, AI APIs, and enterprise integrations. Develop agents, prompts, memory, evaluation loops, observability, guardrails, and CI/CD pipelines. Create prototypes, write automated tests, implement safety controls, and integrate APIs, event streams, and data sources. Communicate tradeoffs and iterate rapidly with stakeholders. The role requires Java full-stack experience alongside hands-on AI application development.

Develop and optimize enterprise Smartsheet solutions and Power BI analytics platforms. Build dashboards, semantic models, DAX measures, automated workflows, integrations, data pipelines, governance standards, and executive reporting. Collaborate with stakeholders, troubleshoot performance and refresh issues, provide training, and support solution adoption. The role requires mandatory five-day office attendance from designated Indian locations and support availability until 11 AM PST.

Build and integrate agentic AI applications using LLMs, RAG pipelines, vector databases, AI APIs, enterprise integrations, and evaluation frameworks. Develop clean, testable software, CI/CD pipelines, safety controls, observability, and robust error handling. Prototype rapidly, demonstrate solutions, communicate tradeoffs, and evolve experimental systems into production applications. The role requires strong Java full-stack experience, hands-on AI development, and a portfolio of AI projects.

Develop and enhance full-stack enterprise applications using Java and modern frontend frameworks. Build backend and frontend components, integrate AI services and APIs, implement RAG features, and use AI-assisted coding tools for development, debugging, testing, and documentation. Collaborate with architects and AI specialists while following enterprise engineering, SDLC, agile, scalability, quality, and CI/CD practices.