AI Engineer

Work Location: Hyderabad (Hybrid Model)

Prestige Skytech, Financial District

Experience: 3 - 5 years

Mandatory Skills: AI, ML, RAG, LLM

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

• Bachelor’s degree in Computer Science, Engineering, AI/ML, or related field.
• Strong analytical skills, eagerness to experiment, and enthusiasm to learn cutting-edge AI tools.

Skills: ai,rag,llm