The Role
Build and deploy AI-native, full-stack software using multi-agent orchestration, hybrid graph and vector retrieval, asynchronous Python backends, and React/TypeScript frontends. Develop agent memory, workflow compilation, real-time streaming interfaces, enterprise integrations, and secure authentication. Deploy containerized services with Azure infrastructure and CI/CD, while operating on-premises and cloud LLMs. The role requires production software engineering, LLM or agent-framework experience, graph database knowledge, and ownership across API, UI, and deployment.
Summary Generated by Built In
Project Role : AI Native Software Engineer
Project Role Description : Build and ship production-ready software using AI as a core part of the engineering lifecycle. Apply AI-native practices to develop and validate solutions, maintain quality and compliance, and continuously improve how software is built and operated.
Must have skills : Digital Full Stack Development
Good to have skills : TypeScript, Python (Programming Language), Software Development
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI Native Software Engineer, your day revolves around creating and delivering software solutions where artificial intelligence is deeply integrated into every stage of development. You will engage in designing, building, and deploying applications that leverage AI capabilities, ensuring that these solutions meet high standards of quality and compliance. Your role involves continuous refinement of software processes to enhance efficiency and reliability, collaborating with various teams to innovate and improve the overall software lifecycle. This position offers an opportunity to work at the forefront of technology, blending software engineering with AI-driven methodologies to produce impactful products.
Roles & Responsibilities:
-Design and implement multi-agent orchestration pipelines using LangGraph state machines with conditional routing, self-healing loops, and sub-agent
hierarchies
- Build and maintain a hybrid retrieval system combining Neo4j knowledge graphs (Cypher) with Qdrant vector search and sentence-transformer
embeddings
- Develop FastAPI backend services with async I/O (asyncpg, Motor), Pydantic v2 models, and JWT/RBAC security
- Build React 18 / TypeScript frontend features including visual graph editors (ReactFlow), real-time SSE streaming, and observability dashboards (Recharts)
- Integrate enterprise protocols: A2A (JSON-RPC), MCP (Model Context Protocol), AG-UI (Server-Sent Events)
- Connect to ALM/PLM tools via REST and GraphQL APIs with OAuth2/SSO authentication (SAML, OIDC)
- Implement dual-tier agent memory (Redis L1 + mem0 L2) with semantic recall and context consolidation - Build DAG-based workflow compilation with topological sorting, cycle detection, and Ray-based parallel execution - Deploy and operate containerized services using Docker, Azure Bicep IaC, and CI/CD pipelines (Azure Pipelines / Jenkins) - Serve and manage on-prem LLM models via vLLM alongside cloud-hosted models (OpenAI-compatible APIs)
Professional & Technical Skills:
Backend & AI
- Python 3.10+ — production-grade FastAPI, Pydantic v2, async/await patterns
- LangGraph / LangChain — state machines, tool calling, agent orchestration
- LLM engineering — prompt design, token budgeting, multi-model routing, self-healing retry loops
- PostgreSQL (JSONB, asyncpg) or MongoDB (Motor) — async data persistence
Knowledge & Retrieval
- Neo4j — Cypher queries, entity-relationship graph modeling, traversal algorithm
- Vector databases (Qdrant, Pinecone, or Weaviate) — embedding pipelines, semantic search, hybrid retrieval
- RAG architecture — chunking strategies, re-ranking, token budget management
- Sentence-transformers or equivalent embedding models
Frontend
- React 18 + TypeScript + Vite — component architecture, hooks, lazy loading
- Server-Sent Events (SSE) or WebSocket — real-time streaming UIs
- ReactFlow / XYFlow — interactive node-based graph editors
- State management (Zustand or Redux) + server-state (TanStack Query)
Additional Skills
- vLLM or TGI — on-prem LLM model serving and optimization
- mem0 or similar — persistent agent memory systems
- A2A / MCP / AG-UI — emerging agentic interoperability protocols
- GraphQL — schema design, client integration
- OAuth2 / SAML / OIDC — enterprise SSO integration
- Ontology modeling — entity taxonomies, relationship schemas for engineering domains
- Pytest — async test patterns, fixture-based testing
Qualifications
- 4+ years professional software engineering experience
- 2+ years working with LLMs, agent frameworks, or ML systems in production
- Strong async Python and modern React/TypeScript skills
- Experience with graph databases or knowledge graph systems
- Comfortable owning features across the full stack — API to UI to deployment
Additional Information:
- The candidate should have minimum 3 years of experience in Digital Full Stack Development.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.15 years full time education
Project Role Description : Build and ship production-ready software using AI as a core part of the engineering lifecycle. Apply AI-native practices to develop and validate solutions, maintain quality and compliance, and continuously improve how software is built and operated.
Must have skills : Digital Full Stack Development
Good to have skills : TypeScript, Python (Programming Language), Software Development
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI Native Software Engineer, your day revolves around creating and delivering software solutions where artificial intelligence is deeply integrated into every stage of development. You will engage in designing, building, and deploying applications that leverage AI capabilities, ensuring that these solutions meet high standards of quality and compliance. Your role involves continuous refinement of software processes to enhance efficiency and reliability, collaborating with various teams to innovate and improve the overall software lifecycle. This position offers an opportunity to work at the forefront of technology, blending software engineering with AI-driven methodologies to produce impactful products.
Roles & Responsibilities:
-Design and implement multi-agent orchestration pipelines using LangGraph state machines with conditional routing, self-healing loops, and sub-agent
hierarchies
- Build and maintain a hybrid retrieval system combining Neo4j knowledge graphs (Cypher) with Qdrant vector search and sentence-transformer
embeddings
- Develop FastAPI backend services with async I/O (asyncpg, Motor), Pydantic v2 models, and JWT/RBAC security
- Build React 18 / TypeScript frontend features including visual graph editors (ReactFlow), real-time SSE streaming, and observability dashboards (Recharts)
- Integrate enterprise protocols: A2A (JSON-RPC), MCP (Model Context Protocol), AG-UI (Server-Sent Events)
- Connect to ALM/PLM tools via REST and GraphQL APIs with OAuth2/SSO authentication (SAML, OIDC)
- Implement dual-tier agent memory (Redis L1 + mem0 L2) with semantic recall and context consolidation - Build DAG-based workflow compilation with topological sorting, cycle detection, and Ray-based parallel execution - Deploy and operate containerized services using Docker, Azure Bicep IaC, and CI/CD pipelines (Azure Pipelines / Jenkins) - Serve and manage on-prem LLM models via vLLM alongside cloud-hosted models (OpenAI-compatible APIs)
Professional & Technical Skills:
Backend & AI
- Python 3.10+ — production-grade FastAPI, Pydantic v2, async/await patterns
- LangGraph / LangChain — state machines, tool calling, agent orchestration
- LLM engineering — prompt design, token budgeting, multi-model routing, self-healing retry loops
- PostgreSQL (JSONB, asyncpg) or MongoDB (Motor) — async data persistence
Knowledge & Retrieval
- Neo4j — Cypher queries, entity-relationship graph modeling, traversal algorithm
- Vector databases (Qdrant, Pinecone, or Weaviate) — embedding pipelines, semantic search, hybrid retrieval
- RAG architecture — chunking strategies, re-ranking, token budget management
- Sentence-transformers or equivalent embedding models
Frontend
- React 18 + TypeScript + Vite — component architecture, hooks, lazy loading
- Server-Sent Events (SSE) or WebSocket — real-time streaming UIs
- ReactFlow / XYFlow — interactive node-based graph editors
- State management (Zustand or Redux) + server-state (TanStack Query)
Additional Skills
- vLLM or TGI — on-prem LLM model serving and optimization
- mem0 or similar — persistent agent memory systems
- A2A / MCP / AG-UI — emerging agentic interoperability protocols
- GraphQL — schema design, client integration
- OAuth2 / SAML / OIDC — enterprise SSO integration
- Ontology modeling — entity taxonomies, relationship schemas for engineering domains
- Pytest — async test patterns, fixture-based testing
Qualifications
- 4+ years professional software engineering experience
- 2+ years working with LLMs, agent frameworks, or ML systems in production
- Strong async Python and modern React/TypeScript skills
- Experience with graph databases or knowledge graph systems
- Comfortable owning features across the full stack — API to UI to deployment
Additional Information:
- The candidate should have minimum 3 years of experience in Digital Full Stack Development.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Skills Required
- Minimum 3 years of experience in Digital Full Stack Development
- 4+ years of professional software engineering experience
- 2+ years working with LLMs, agent frameworks, or ML systems in production
- Strong asynchronous Python skills
- Modern React and TypeScript skills
- Experience with graph databases or knowledge graph systems
- Ability to own features across the full stack, including API, UI, and deployment
- Digital full-stack development
- 15 years of full-time education
- Python programming
- TypeScript
- Software development experience
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
-
Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
-
Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
-
Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
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The Company
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
