ROLE
– Build intelligent chatbots, AI assistants, copilots, and workflow automation solutions
– Design and implement AI Agents and Multi-Agent Systems capable of reasoning, planning, and autonomous task execution
– Build agentic workflows integrating external APIs, databases, enterprise applications, and third-party services
– Develop scalable backend services and APIs for AI applications
– Evaluate, benchmark, monitor, and continuously improve AI system performance
– Collaborate with product, engineering, and business teams to deliver AI-driven solutions
– Stay up to date with the latest advancements in Generative AI, Agentic AI, LLMs, and emerging AI technologies

REQUIREMENTS
– Strong proficiency in Python with experience building scalable, production-grade applications
– Hands-on experience in Generative AI, LLMs, and AI-powered application development
– Experience working with foundation models such as GPT, Claude, Gemini, Llama, Mistral, DeepSeek, Qwen, or similar
– Strong understanding of Prompt Engineering, Function Calling, Tool Calling, Structured Outputs, Context Management, and LLM Evaluation
– Experience designing and building AI Agents, Agentic Workflows, and Multi-Agent Systems
– Hands-on experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, LlamaIndex, PydanticAI, or similar
– Experience designing and implementing RAG pipelines and enterprise knowledge retrieval systems
– Strong understanding of embeddings, semantic search, hybrid search, reranking, and vector retrieval techniques
– Experience with Vector Databases such as Pinecone, Qdrant, Weaviate, ChromaDB, FAISS, or Milvus
– Experience building and deploying REST APIs using FastAPI, Flask, or similar frameworks
– Familiarity with Git, Docker, CI/CD practices, and cloud platforms such as AWS, Azure, or GCP
– Strong problem-solving, analytical, and communication skills
– Self-driven mindset with ownership and accountability
– Exposure to Agentic RAG, GraphRAG, Knowledge Graphs, and advanced retrieval architectures
– Experience deploying open-source LLMs using Ollama, vLLM, Hugging Face, TensorRT-LLM, or similar tools
– Exposure to LLMOps and MLOps platforms such as MLflow, LangSmith, Phoenix, Weights & Biases, or Arize
– Experience with AI evaluation frameworks, observability platforms, monitoring, and guardrails
– Knowledge of Kubernetes, distributed systems, and scalable AI infrastructure
– Experience building enterprise chatbots, AI copilots, workflow automation solutions, and autonomous AI systems
– Familiarity with multimodal AI applications involving text, image, audio, and document understanding
– Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field
– 1–3 years of relevant experience in AI/ML, Generative AI, LLM Engineering, or AI Application Development
– Strong understanding of software engineering best practices and system design principles
– Passion for Generative AI, Agentic AI, and emerging AI technologies
– Ability to rapidly learn and adopt new AI frameworks, tools, and methodologies
– Experience taking AI solutions from proof-of-concept to production deployment
– Strong collaboration and communication skills
– Ownership-driven mindset with a focus on building impactful AI products

BENEFITS
– Work on cutting-edge Generative AI, Agentic AI, and Multi-Agent Systems
– Build production-grade AI products with real-world business impact
– Opportunity to work with the latest LLMs, MCP, RAG, Agentic AI, and AI infrastructure technologies
– Collaborative, innovation-driven environment with excellent learning and growth opportunities