AI Engineer - Mumbai City
22 hours ago
Job description
AI Engineer (Agentic AI & LLM Systems) with AI Start UpContract| 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
- 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
- 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)
- 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
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
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