AI Native Software Engineer
Accenture
- Location
- Onsite (Bengaluru, Karnataka)
- Employment
- Full-time
- Level
- Mid Level
Posted 3 days ago
About the role
Accenture seeks an AI Native Software Engineer to build production-ready software integrating AI into the engineering lifecycle. The role focuses on designing multi-agent orchestration pipelines and hybrid retrieval systems to deliver impactful, high-quality software solutions.
Skills
Python
React
TypeScript
FastAPI
LangGraph
Neo4j
Qdrant
Vector databases
LLM engineering
PostgreSQL
Docker
Azure
GraphQL
RAG architecture
CI/CD
OAuth2
Full job details
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 : Python (Programming Language), TypeScript, 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 : Python (Programming Language), TypeScript, 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
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