I&P - GN - SONG - AI & Data - Platforms - Full Stack Engineering - Consultant

Job description

Entity: GN Song Practice: GN Song - Data & AI Title: Song Process Excellence | Full Stack Engineering Consultant - CL9 Job Location: Gurgaon/ Bangalore/ Mumbai/ Hyderabad/ Pune/ Kolkata/ Chennai About Song - Data & AI Accenture Song uses AI, proprietary customer data, and product platforms to help clients improve customer experience and drive measurable growth across marketing, sales, commerce, and service. From strategy through execution, Song Data & AI helps organizations build and operationalize advanced capabilities - covering customer data unification, predictive analytics, and Generative AI (including agentic use cases) - to enable smarter decisioning like personalization and "next best action," faster content and experience delivery, and more effective commerce and customer engagement. What's In It For You? Join a worldwide network of full stack, cloud, data, and AI engineers building secure digital products and AI-enabled enterprise applications. Access world-class training, mentorship, and certifications across modern front-end and back-end engineering, cloud-native development, DevSecOps, data platforms, and applied AI. Work on high-visibility engagements across Marketing, Sales, Commerce, Customer Service, and Digital Products - creating applications that make data, ML, Generative AI, and agentic capabilities usable at scale. Contribute to Accenture's reusable user-interface components, application services, integration patterns, reference implementations, testing assets, and engineering playbooks. What You Will Do As a Full Stack Engineering Consultant, you will own the hands-on design, build, testing, deployment, and support of assigned application modules and workstreams. You will create responsive user experiences and scalable services, integrate governed data and ML/AI capabilities, and guide junior team members within agreed architecture, security, and delivery standards. Analyze business, user, and technical requirements and translate them into user stories, acceptance criteria, API contracts, detailed designs, and executable engineering tasks. Build responsive, accessible, and reusable web interfaces using modern JavaScript or TypeScript frameworks such as React, Angular, Vue, or Next.js. Develop secure back-end services, microservices, and APIs using one or more enterprise stacks such as Java and Spring Boot, .NET, Node.js and NestJS, or Python and FastAPI. Implement application data models and persistence using relational and NoSQL databases, caching, search, object storage, and messaging services appropriate to the use case. Integrate applications with enterprise systems, identity services, APIs, files, event streams, and third-party platforms using synchronous and asynchronous integration patterns. Apply data engineering know-how to application delivery - including SQL, schema design, data contracts, app-specific ingestion or transformation, data quality checks, lineage awareness, and consumption of lakehouse or warehouse data products. Integrate ML and AI capabilities through model endpoints, Retrieval-Augmented Generation, embeddings and vector search, agent or tool APIs, structured outputs, feedback capture, and human-in-the-loop workflows in collaboration with ML/AI engineers. Implement engineering practices covering Git, code reviews, automated unit, integration and end-to-end testing, CI/CD, containerization, cloud deployment, configuration, and release management. Design and operate for security, privacy, accessibility, performance, resilience, observability, and cost; troubleshoot defects and production incidents across the application stack. Own an assigned module or workstream, coordinate day-to-day technical activities, review deliverables, and guide Analysts or Senior Analysts. Engage client product owners, designers, architects, data teams, and AI teams through requirement workshops, design walkthroughs, sprint reviews, demonstrations, and issue resolution. Contribute reusable code, components, technical documentation, reference implementations, and practice knowledge assets. Domain Focus Candidates should bring hands-on full stack application delivery experience in one or more of the following domains: Marketing - campaign and content workflows, customer data applications, audience activation, personalization, measurement, and next-best-action experiences Sales - sales productivity, recommendations, forecasting and revenue intelligence applications, customer or outlet prioritization, and route-to-market tools Commerce - product discovery, search and recommendations, catalog, pricing and promotions, order and inventory experiences, and digital commerce platforms Service - conversational interfaces, agent assist, knowledge and case management, contact center applications, and operations automation Design & Digital Products - responsive web or mobile products, AI copilots, workflow applications, experimentation, product analytics, and reusable digital services Who We Are Looking For Mandatory Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, Engineering, or a related discipline. 4-8 years of progressive experience in full stack application engineering, including ownership of production modules or technical workstreams. Strong hands-on expertise in at least one modern front-end stack - React, Angular, Vue, Next.js, JavaScript or TypeScript - together with HTML, CSS, responsive design, and component-based development. Strong hands-on expertise in at least one back-end stack - Java and Spring Boot, .NET and C#, Node.js and NestJS or Express, Python and FastAPI, or equivalent. Experience designing and consuming REST or GraphQL APIs, microservices, asynchronous workflows, and enterprise integration patterns. Experience with relational databases and SQL, plus working knowledge of NoSQL, caching, search, object storage, or messaging technologies. Strong software engineering foundations covering data structures, object-oriented or functional design, clean code, design patterns, version control, code reviews, and automated testing. Hands-on exposure to at least one major cloud platform - Azure, AWS, or GCP - and experience with containers, CI/CD pipelines, configuration, secrets, and environment promotion. Working knowledge of application security, including authentication and authorization, OAuth2 or OpenID Connect, IAM, secure coding, API protection, encryption, and OWASP risks. Experience implementing logging, metrics, tracing, error handling, performance optimization, resilience, and production support for distributed applications. Working knowledge of data engineering concepts - SQL and data modelling, ETL/ELT, batch or streaming integration, schema evolution, data contracts, quality, lineage, and lakehouse or warehouse consumption; Spark familiarity is valuable. Working knowledge of ML/AI application integration - model APIs, prompts and structured outputs, embeddings, vector search, RAG, agent or tool-calling patterns, feedback loops, and AI service monitoring. Awareness of AI evaluation, hallucination and failure handling, guardrails, privacy, Responsible AI, human oversight, and secure handling of enterprise data in AI-enabled applications. Ability to work from a solution architecture and produce detailed designs, API specifications, implementation plans, test evidence, and technical documentation. Experience working in Agile product delivery, estimating tasks, tracking dependencies and risks, reviewing work, and mentoring junior engineers. Strong problem-solving, collaboration, and communication skills, with the ability to explain technical choices to client and cross-functional stakeholders. What We Are NOT Looking For Front-end-only or back-end-only profiles without evidence of working across application layers and owning end-to-end integration. Low-code, CMS, portal configuration, or packaged-platform profiles without substantive software engineering, automated te