4 hours ago
Pune, IndiaMid Level
Responsibilities
- Understand business use cases, requirements, data sources, workflow steps, dependencies, risks, and technical approaches for GenAI and agentic AI solutions.
- Support low-level design for AI modules, including prompt flows, API flows, response flows, RAG designs, agent workflows, tools, fallback handling, and human review points.
- Develop LLM-based chat, search, summarization, classification, Q&A, RAG, structured-output, and agent workflow features.
- Integrate LLM APIs and AI solutions with enterprise systems, APIs, files, databases, knowledge sources, cloud services, and backend services.
- Configure vector databases, document retrieval pipelines, model settings, service connections, environment variables, and secure API-key handling.
- Test prompts, RAG responses, agent workflows, tool calls, APIs, fallback paths, accuracy, relevance, safety, and consistency, and resolve defects.
- Optimize prompts, retrieval, chunking, metadata filters, context usage, API calls, retries, timeouts, caching, response time, token usage, and execution cost.
- Follow secure coding, data handling, access control, audit logging, responsible AI, governance, guardrail, and validation requirements.
- Support deployment across development, test, UAT, and production environments, including releases, post-deployment validation, rollback, and hypercare.
- Troubleshoot production issues involving AI responses, APIs, retrieval, agents, latency, missing context, tool failures, and API errors, and provide RCA inputs.
- Prepare technical notes, test cases, validation results, support notes, runbooks, release documentation, and knowledge-transfer materials.
- Participate in Agile/Scrum delivery activities and collaborate with architects, senior developers, QA, business analysts, DevOps, support, and delivery teams.
Requirements
- At least 3 years of experience, with flexibility for candidates demonstrating strong hands-on AI project experience.
- Hands-on experience with GenAI application development, agentic AI implementation, prompt engineering, RAG, LLM API integration, Python, REST API development, SQL, vector databases, embeddings, and Git-based development.
- Experience or familiarity with chatbot, RAG, LLM, AI-agent, or automation use cases is preferred.
- Knowledge of LangChain, LangGraph, LlamaIndex, OpenAI, Azure OpenAI, Claude, Gemini, AWS Bedrock, agent tools, function calling, workflow orchestration, and Model Context Protocol is preferred.
- Knowledge of FastAPI, Flask, Node.js, Docker, CI/CD, Azure, AWS, GCP, LLM evaluation, observability, responsible AI, and AI governance is preferred.
- Qualification of BE, BTech, MCA, MSc, BSc, BCA, or equivalent practical experience.
- AI, GenAI, Cloud, or Python certification is preferred.
- Clear communication, problem-solving ability, ownership, collaboration, curiosity, learning mindset, documentation skills, and delivery focus.
Benefits
- India-based work arrangement may be remote, hybrid, or work-from-office according to project needs.
- Client shift work and collaboration with multi-region teams may be required.
- Inclusive recruitment process that values diverse backgrounds and experiences.
Tech Stack
AWSAzureDockerFastAPIFlaskGitGoogle Cloud PlatformJavaScriptMicrosoft SQL ServerMongoDBNode.jsPostgreSQLPythonSQLTypeScript
Categories
About Fujitsu
Fujitsu is a global leader in digital services that transform organizations and the world around us. We aim to make the world more sustainable by building trust in society through innovation.