AI Native Software Engineer

Accenture PLC; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Accenture PLC in Bengaluru is seeking an AI Native Software Engineer to design, build and deploy AI-integrated software across the full stack. You will craft multi-agent orchestration, hybrid retrieval systems, and secure backend services with FastAPI and JWT, while delivering responsive frontend features in React/TypeScript.

The role emphasizes production-grade AI workflows, scalability, and compliance, with opportunities to work at the frontier of AI-driven software engineering in an

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.
• Based at Bengaluru office; 15 years full-time education required.

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 with Qdrant vector search and sentence-transformer embeddings.
• Develop FastAPI backend services with async I/O, Pydantic models, and JWT/RBAC security.
• Build React 18 / TypeScript frontend features including visual graph editors, real-time SSE streaming, and observability dashboards.
• Integrate enterprise protocols: JSON-RPC, Model Context Protocol, Server-Sent Events.
• Connect to ALM/PLM tools via REST and GraphQL APIs with OAuth2/SSO authentication.
• Implement dual-tier agent memory with semantic recall and context consolidation.
• Deploy and operate containerized services using Docker, IaC, and CI/CD pipelines.

Skills

Digital Full Stack Development

Python

TypeScript

Software Development

Education

15 years full time education

Tools

Neo4j

Qdrant

FastAPI

React

Docker

Azure Pipelines

Jenkins

Job description

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
• Backend & AI - LangGraph / LangChain — state machines, tool calling, agent orchestration
• Backend & AI - LLM engineering — prompt design, token budgeting, multi-model routing, self-healing retry loops
• Backend & AI - 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

Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

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