Website:
yminds.ai
Job details:
About the Role
Our client is seeking an AI-focused Developer with strong hands-on experience in Generative AI, LLM-based application development, and Agentic AI solutions.
The ideal candidate will have strong expertise in Python or TypeScript, RESTful APIs, LLM orchestration frameworks, vector databases, prompt engineering, cloud AI platforms, and scalable microservices architecture.
Candidates should have practical experience building and deploying real-world Agentic AI solutions. Profiles with only theoretical knowledge, training, certifications, or proof-of-concept exposure in Agentic AI will not be considered.
Key Responsibilities
- Design, develop, implement, and deploy Agentic AI applications and autonomous AI workflows.
- Build production-ready Generative AI and LLM-powered applications.
- Develop scalable backend services using Python or TypeScript.
- Design and integrate RESTful APIs, GraphQL APIs, and microservices.
- Build LLM workflows using LangChain, LlamaIndex, LangGraph, or similar orchestration frameworks.
- Develop AI agents capable of tool calling, API integration, planning, memory, reasoning, retrieval, and multi-step task execution.
- Implement prompt-engineering techniques such as zero-shot prompting, few-shot prompting, structured outputs, and function/tool calling.
- Integrate vector databases such as Pinecone, ChromaDB, FAISS, or Weaviate.
- Work with embeddings, transformers, NLP pipelines, semantic search, retrieval mechanisms, and contextual data.
- Build and integrate RAG-based applications and enterprise knowledge assistants.
- Deploy AI applications using AWS Bedrock, SageMaker, Google Vertex AI, Azure OpenAI, or similar cloud platforms.
- Monitor, troubleshoot, and optimize Agentic AI and LLM applications for performance, accuracy, reliability, scalability, latency, and cost.
- Implement version control and deployment workflows using Git and CI/CD pipelines.
- Create clear technical documentation for application architecture, AI workflows, APIs, integrations, and deployment processes.
- Collaborate with engineering, product, data, and business stakeholders.
Required Skills
- 3+ years of overall relevant software development / AI application development experience.
- 2+ years of hands-on experience in Generative AI and LLM-based application development.
- 1+ year of hands-on Agentic AI experience involving real-world project implementation and deployment — mandatory.
- Proven experience building AI agents, multi-step agentic workflows, tool-calling solutions, or autonomous AI systems.
- Strong proficiency in Python or TypeScript for AI-driven backend development.
- Strong experience developing and integrating RESTful APIs.
- Hands-on experience with LangChain, LlamaIndex, LangGraph, or similar LLM orchestration frameworks.
- Strong understanding of prompt engineering, including zero-shot, few-shot, structured prompting, function calling, tool calling, and structured outputs.
- Experience with vector databases such as Pinecone, ChromaDB, FAISS, or Weaviate.
- Understanding of NLP, embeddings, transformers, semantic search, retrieval techniques, and RAG architectures.
- Experience with at least one cloud AI platform such as AWS Bedrock, SageMaker, Google Vertex AI, or Azure OpenAI.
- Knowledge of REST, GraphQL, microservices, and scalable application architecture.
- Experience using Git and CI/CD pipelines.
- Strong analytical, debugging, and problem-solving skills.
- Excellent technical documentation, collaboration, and communication skills.
Nice-to-Have Skills
- Experience developing multi-agent systems or agent orchestration workflows.
- Hands-on experience with RAG architectures and enterprise knowledge assistants.
- Experience with agent frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel.
- Knowledge of agent memory, planning, reasoning, tool usage, state management, and human-in-the-loop workflows.
- Experience implementing LLM evaluation, observability, monitoring, guardrails, and responsible AI controls.
- Familiarity with Docker, Kubernetes, serverless architecture, and cloud-native deployments.
- Experience optimizing LLM applications for latency, token usage, reliability, scalability, and cost.
- Exposure to fine-tuning, model selection, AI application security, and access controls.
About YMinds.AI
YMinds.AI is a technology-focused talent solutions company helping organizations hire exceptional professionals across Engineering, AI/ML, Data, Cloud, Product, and Business functions.
Through our AI-powered talent platform, EmployAbility.AI, we enable faster access to verified and high-quality candidates by combining intelligent matching, expert screening, and a continuously refreshed talent network.
Keywords
Agentic AI Developer, Generative AI Engineer, LLM Developer, AI Agents, Multi-Agent Systems, Python, TypeScript, LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, REST APIs, GraphQL, Microservices, Prompt Engineering, Function Calling, Tool Calling, RAG, Vector Databases, Pinecone, ChromaDB, FAISS, Weaviate, NLP, Embeddings, Transformers, AWS Bedrock, SageMaker, Vertex AI, Azure OpenAI, CI/CD
Hashtags
#AgenticAI #GenerativeAI #AIEngineer #LLMDeveloper #AIAgents #Python #TypeScript #LangChain #LangGraph #LlamaIndex #RAG #VectorDatabase #PromptEngineering #CloudAI #Hiring #TechJobs #YMindsAI
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