AI Engineer (Agentic AI & LLM Systems) with AI Start Up

Contract| Immediate

Your tasks

AI Start Up is looking for an experienced AI Engineer to join their growing AI team. You’ll play a key role in developing intelligent, agentic AI systems using cutting-edge large language models (LLMs), multi-agent orchestration, and retrieval-augmented generation (RAG). This is a hands-on role combining software engineering and a passion for building next-gen autonomous agents.

You’ll collaborate closely with AI leads, backend engineers, data engineers, and product managers to bring scalable and intelligent systems to life—integrated into real-world procurement and business applications.

Key Responsibilities

· Design and implement agentic AI pipelines using LangGraph, LangChain, CrewAI, or custom frameworks

· Build robust retrieval-augmented generation (RAG) systems with vector databases (e.g., OpenSearch)

· Fine-tune, evaluate, and deploy LLMs for task-specific applications

· Integrate external tools and APIs into multi-agent workflows using dynamic tool/function calling (e.g., OpenAI JSON schema)

· Develop memory modules such as short-term context, episodic memory, and long-term vector stores

· Build scalable, cloud-native services using Python

· Collaborate in agile, cross-functional teams to rapidly prototype and ship Multiagent-based features

· Monitor and evaluate agent performance using tailored metrics (e.g., success rate, hallucination rate)

· Ensure secure, reliable, and maintainable deployment of AI systems in production environments

Desired Persona

· 7+ years of professional experience in machine learning, NLP, or software engineering

· Strong proficiency in Python and experience with ML libraries like PyTorch, TensorFlow, scikit-learn, and XGBoost

· Hands-on experience with LLMs (e.g., GPT, Claude, LLaMA, Mistral) and NLP tooling such as LangChain, HuggingFace, and Transformers

· Experience designing and implementing RAG pipelines with chunking, semantic search, and reranking

· Familiarity with agent frameworks and orchestration techniques (e.g., planning, memory, role assignment)

· Deep understanding of prompt engineering, embeddings, and LLM architecture basics

· Design systems with role-based communication, coordination loops, and hierarchical planning. Optimize agent collaboration strategies for real-world tasks.

· Experience integrating REST/GraphQL APIs into ML workflows

· Strong collaboration and communication skills, with a builder’s mindset and

· willingness to explore new approaches

Positive to Have

· Solid foundation in microservice architectures, CI/CD, and infrastructure-as-code (e.g., Terraform)

· Experience with RLHF, LoRA, or parameter-efficient LLM fine-tuning

· Familiarity with CrewAI, AutoGen, Swarm, or other multi-agent libraries

· Exposure to cognitive architectures like task trees, state machines, or episodic memory

· Prompt debugging and LLM evaluation practices

· Awareness of AI security risks (e.g., prompt injection, data exposure)

Screening Criteria

· 5+ years of professional experience in machine learning

· Experience of implementation of AI pipelines using langchain and langgraph

· Experience in RAG systems deployment

· Expertise in Strong coding using Python

· Understanding of Multi agent frameworks (CrewAI, AutoGen, etc.)

· Available to join within 2 weeks

Evaluation Process

In the interview process, there will be online coding test, including Python coding (test cases/debugging) and RAG application development

Considerations

· 6 Months Contract

· Remote Working

· Timings – 12 PM to 9 PM IST