Software Engineer

Capgemini; Dadri; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Capgemini in India seeks a Gen AI engineer to build prototypes, pipelines and reusable AI components across the knowledge-base, design, testing and deployment stages.

You will develop RAG solutions, document-processing workflows and prompts, while collaborating with SMEs and deployment teams to ensure high-quality outputs and scalable AI solutions.

Qualifications

• Bachelors or Masters in Engineering with 1-4 years Gen AI experience.
• Strong prompt engineering with Claude/GPT-4/5 exposure.
• Hands-on RAG implementation including ingestion, embeddings, vector search, retrieval evaluation.
• Claude Code experience for code generation, explanation, refactoring, test generation, and docs.
• Experience building n8n workflows with API integrations, LLM calls, approvals and logging.
• Proficiency in Python, TypeScript/JS, REST APIs, JSON, Git, CI/CD, Docker, Kubernetes, LangChain, LlamaIndex, Semantic Kernel and vector DBs.
• Knowledge of software engineering lifecycle; Spec-driven Development beneficial.
• Telecom domain knowledge is a plus.

Responsibilities

• Build hands-on Gen AI prototypes, pilots and reusable components for AI roadmap.
• Implement AI solutions for knowledge-base queries, requirements generation, design support, trace/RCA, test strategy and test case generation.
• Develop RAG pipelines over docs and logs with retrieval quality evaluation.
• Create document-processing pipelines: parsing, metadata extraction, embedding generation, vector indexing and retrieval.
• Develop prompts, structured outputs, and reusable skill files for various AI tasks.
• Build n8n workflows for AI automation including ingestion, summarisation and approvals.
• Utilize Claude Code for code understanding, generation, refactoring, and test generation.
• Implement evaluation mechanisms to track output quality, accuracy and adoption rate.
• Collaborate with SMEs, developers, testers, and deployment teams to validate outputs.
• Document reusable assets and patterns in AI KM repository and Playbook.

Skills

Prompt engineering

LLMs

RAG implementation

Claude Code

n8n workflows

AI solutions development

Software lifecycle

Spec-driven Development

Telecom domain knowledge

Education

Bachelor's or Master's in Engineering

Tools

Python

TypeScript/JavaScript

REST APIs

JSON

Git

CI/CD

Docker

Kubernetes

LangChain

LlamaIndex

Semantic Kernel

vector databases

Job description

Roles & Responsibilities

• Build hands-on Gen AI prototypes, pilots and reusable components for AI roadmap.
• Implement AI solutions for knowledge-base query, requirements generation, design support, trace/RCA, test strategy, test case generation, test execution support, deployment/MOP and stakeholder interaction analysis.
• Develop RAG pipelines over requirements specifications and design documents, test plans, tickets, KB articles, deployment records, application and system logs and traces.
• Build document-processing pipelines including parsing, metadata extraction, chunking, embedding generation, vector indexing and retrieval logic.
• Create prompts, structured outputs and reusable skill files for requirements, acceptance criteria, design summaries, test cases, RCA summaries and stakeholder summaries.
• Build n8n workflows for AI automation, including document ingestion, knowledge refresh, ticket summarisation, requirement extraction, trace processing, test generation, approvals and metrics capture.
• Use Claude Code to support code understanding, code generation, refactoring, unit-test generation, documentation and engineering productivity within the OSP delivery context.
• Implement evaluation mechanisms to track output quality, retrieval accuracy, hallucination risk, human review effort, time saved, adoption and AI output acceptance rate.
• Work closely with SMEs, developers, testers, deployment teams and use-case owners to validate AI outputs and improve solution quality.
• Document reusable assets, demos, workflows, lessons learned and implementation patterns in the AI KM repository and AI Engineering Playbook.

Qualifications & Skills

• Bachelors or Master’s degree in Engineering, with 1-4 years of experience developing Gen AI solutions
• Strong hold on prompt engineering coupled with experience using LLMs including but not limited to Claude Sonnet, Claude Opus, Claude Haiku, GPT-4 and GPT-5. atleast 2
• Hands-on RAG implementation experience including document ingestion, embeddings, vector search, metadata filtering, retrieval evaluation and source-grounded responses.
• Experience with Claude Code for code generation, code explanation, refactoring, test generation, documentation and review support.
• Experience building n8n workflows with API integrations, conditional logic, LLM calls, approval flows, logging, retries and error handling.
• Experience with Python, TypeScript/JavaScript, REST APIs, JSON, Git, CI/CD, Docker, Kubernetes, LangChain, LlamaIndex, Semantic Kernel and vector databases.
• Good understanding of software engineering lifecycle activities including requirements, design, development, testing, deployment and support.
• Knowledge of Spec-driven Development will be beneficial.
• Background in Telecom sector and network platforms will be a plus.