3 days ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- 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.
- Develop secure back-end services, microservices, and APIs using enterprise technology stacks.
- Implement data models and persistence across relational and NoSQL databases, caching, search, object storage, and messaging services.
- Integrate enterprise systems, identity services, APIs, files, event streams, and third-party platforms through synchronous and asynchronous patterns.
- Apply data engineering practices including SQL, schema design, data contracts, ingestion or transformation, data quality checks, lineage awareness, and lakehouse or warehouse consumption.
- Integrate ML and AI capabilities through model endpoints, RAG, embeddings, vector search, agent or tool APIs, structured outputs, feedback capture, and human-in-the-loop workflows.
- Implement Git-based development, code reviews, automated testing, CI/CD, containerization, cloud deployment, configuration, and release management.
- Design and operate applications for security, privacy, accessibility, performance, resilience, observability, and cost, while troubleshooting defects and production incidents.
- Own assigned modules or workstreams, coordinate technical activities, review deliverables, and guide Analysts or Senior Analysts.
- Engage client product owners, designers, architects, data teams, and AI teams through workshops, walkthroughs, reviews, demonstrations, and issue resolution.
- Contribute reusable code, components, technical documentation, reference implementations, and engineering knowledge assets.
Requirements
- Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, Engineering, or a related discipline.
- 4-8 years of progressive full stack application engineering experience, including ownership of production modules or technical workstreams.
- Hands-on expertise in at least one modern front-end stack, including React, Angular, Vue, Next.js, JavaScript, or TypeScript, along with HTML, CSS, responsive design, and component-based development.
- Hands-on expertise in at least one back-end stack, including Java and Spring Boot, .NET and C#, Node.js and NestJS or Express, or Python and FastAPI.
- 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 foundations in data structures, object-oriented or functional design, clean code, design patterns, version control, code reviews, and automated testing.
- Hands-on exposure to Azure, AWS, or GCP, together with containers, CI/CD pipelines, configuration, secrets, and environment promotion.
- Working knowledge of application security, authentication and authorization, OAuth2 or OpenID Connect, IAM, secure coding, API protection, encryption, and OWASP risks.
- Experience with logging, metrics, tracing, error handling, performance optimization, resilience, and production support for distributed applications.
- Working knowledge of data engineering, 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, including model APIs, prompts, structured outputs, embeddings, vector search, RAG, agents, feedback loops, and AI service monitoring.
- Awareness of AI evaluation, hallucination and failure handling, guardrails, privacy, Responsible AI, human oversight, and secure enterprise data handling.
- Ability to work from solution architecture and produce detailed designs, API specifications, implementation plans, test evidence, and technical documentation.
- Experience with Agile product delivery, task estimation, dependency and risk tracking, work review, and mentoring junior engineers.
- Strong problem-solving, collaboration, and communication skills, including the ability to explain technical choices to clients and cross-functional stakeholders.
- Preferred qualifications include a Master's degree, recognized cloud or application-development certifications, relevant consulting experience, Kubernetes, serverless platforms, infrastructure as code, API gateways, service mesh, platform engineering, progressive web applications, cross-platform mobile development, design systems, accessibility, front-end performance engineering, Kafka, Databricks, Snowflake, Azure AI Foundry, Amazon Bedrock, Vertex AI, MLOps, LLMOps, AgentOps, reusable accelerators, open-source or internal engineering communities, proofs of concept, and client-facing demonstrations.
Benefits
- Worldwide network of full stack, cloud, data, and AI engineers.
- World-class training, mentorship, and certifications across front-end and back-end engineering, cloud-native development, DevSecOps, data platforms, and applied AI.
- Opportunity to work on high-visibility engagements across marketing, sales, commerce, customer service, and digital products.
- Opportunity to contribute to reusable components, application services, integration patterns, reference implementations, testing assets, and engineering playbooks.
Tech Stack
AngularApache KafkaApache SparkAWSAzureC#CSSDatabricksExpressFastAPIGitGoogle Cloud PlatformGraphQLHTMLJavaJavaScriptKubernetesNestJS.NETNext.jsNode.jsPythonReactSnowflakeSpring BootSQLTypeScriptVue.js
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.