Agentic AI Developer

22 hours ago

Hyderabad, India Prajava Technologies Full time

Designation - Agentic AI Developer

Work Location - Hyderabad (Hybrid)

Experience - 0 to 2 years

Key Responsibilities

  • Agentic AI Development:

  • Build, customize, and deploy AI agents using frameworks like LangChain, AutoGen, CrewAI, and Haystack.

  • Enable agent reasoning, planning, and tool-use for complex tasks.

  • RAG Pipeline Design:

  • Implement and optimize RAG pipelines for enterprise-scale knowledge retrieval.

  • Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to manage embeddings and context injection.

  • Fine-tune retrieval strategies, chunking logic, and metadata tagging for high-quality responses.

  • Prompt Engineering & LLM Integration:

  • Develop structured prompts, context-aware query chains, and workflows for LLMs (OpenAI, Anthropic, Llama, Mistral, etc.).

  • Integrate RAG-enabled LLMs into APIs, chatbots, and enterprise applications.

  • Automation & Platform Development:

  • Create orchestration pipelines for AI agents and RAG workflows.

  • Contribute to building internal AI platforms, dashboards, and monitoring systems.

  • Experimentation & Research:

  • Stay current with new developments in RAG, multi-agent systems, and reasoning models.

  • Rapidly prototype AI solutions to demonstrate value to business teams.

Required Skills

  • Programming: Strong in Python; familiarity with JavaScript/TypeScript or Go is a plus.
  • LLM Frameworks: Experience or coursework in LangChain, LlamaIndex, Haystack, or AutoGen.
  • RAG Expertise: Understanding of RAG concepts, document indexing, embeddings, retrieval strategies, and vector DBs.
  • Databases: PostgreSQL/MySQL for structured data; Pinecone, Weaviate, Milvus, FAISS for vectors.
  • APIs & Cloud: Knowledge of REST/GraphQL APIs and cloud services (AWS/GCP/Azure).
  • Version Control: Git, GitHub/GitLab, and CI/CD pipelines.

Preferred Skills (Good-to-Have)

  • Familiarity with LangGraph and other agent orchestration libraries.
  • Exposure to multi-agent collaboration patterns and reasoning models (OpenAI o1, DeepSeek-R1).
  • Knowledge of document preprocessing, semantic search, and hybrid retrieval.
  • Understanding of MLOps for deploying and monitoring AI pipelines.
  • Experience with Docker, Kubernetes, and distributed systems.

Qualifications

  • Bachelors degree in Computer Science, Engineering, AI/ML, or related field.
  • 03 years of relevant experience (internships, hackathons, or open-source contributions preferred).
  • Strong analytical skills, eagerness to experiment, and enthusiasm to learn cutting-edge AI tools.

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