AI Developer - Agentic AI

Role: AI Developer Agentic AI

Exp: 23 Years

Work Mode: 12 10 pm Onsite( Mohali Punjab)

Job Role & Responsibilities

• Design develop and deploy Agentic AI systems capable of autonomous task by integrating reasoning memory and tool use to enable intelligent behavior across complex multistep workflows.
• Architect intelligent agents that can dynamically interact with APIs data sources and thirdparty tools to accomplish diverse objectives with minimal human intervention.
• Optimize performance of agentic frameworks by enhancing model accuracy minimizing response latency and ensuring scalability and reliability in realworld applications.
• Develop reusable testable and productiongrade code adhering to best practices in software engineering and modern AI development workflows.
• Collaborate with crossfunctional teams including product managers designers and backend engineers to convert business requirements into modular agent behaviors.
• Integrate RetrievalAugmented Generation (RAG) advanced NLP techniques and knowledge graph structures to improve decisionmaking and contextual awareness of agents.
• Conduct rigorous profiling debugging and performance testing of agent workflows to identify bottlenecks and improve runtime efficiency.
• Write and maintain comprehensive unit integration and regression tests to validate agent functionality and ensure robust system performance.
• Continuously enhance codebases refactor existing modules and adopt new design patterns to accommodate evolving agentic capabilities and improve maintainability.
• Implement secure faulttolerant and privacycompliant designs to ensure that deployed agentic systems meet enterprisegrade reliability and data protection standards.

Qualification Required:

Bachelors degree in computer science or related field.

Specialization or Certification in AI or ML is a plus.

Technical Expertise:

• 2 years of handson experience in AI/ML/DL projects with a strong emphasis on Natural Language Processing (NLP) Named Entity Recognition (NER) and Text Analytics.
• Proven ability to design and deploy Agentic AI systemsautonomous goaloriented agents that exhibit reasoning memory retention tool use and of multistep tasks.
• Practical expertise in agent architecture task decomposition and seamless integration with external APIs databases and tools to enhance agent capabilities.
• Skilled in agent prompting strategies including dynamic prompt chaining and context management to guide language models through intelligent decisionmaking workflows.
• Experience with RetrievalAugmented Generation (RAG) pipelines and generative AI with a strong focus on optimizing NLP models for lowlatency highaccuracy production use.
• Solid foundation in deep learning methods recommendation engines and AI applications within HR or similar domains.
• Exposure to Reinforcement Learning (RL) frameworks and holds relevant certifications or specializations in Artificial Intelligence showcasing continuous learning and depth in the field.

Minimum skills we look for:

Skills & Expertise (with Agentic AI focus)

• Proven experience in building Agentic AI systems including autonomous agents capable of multistep reasoning memory management and tool use.
• Expertise in agent design patterns task decomposition dynamic planning and decisionmaking logic using LLMs.
• Skilled in integrating multiagent coordination goalsetting and feedback loops to create adaptive evolving agent behavior.
• Strong command over prompt engineering contextual memory structuring and tool calling mechanisms within LLMpowered agent workflows.
• Proficiency in managing agent memory (shortterm longterm episodic) using vector databases and custom memory stores.
• Ability to build autonomous task pipelines with minimal human input combining language models APIs and thirdparty tools.
• Experience with frameworks and orchestration for agent behavior tracing logging and failure recovery.

Tools & Technologies Agentic AI

• Agentic Frameworks: LangChain CrewAI AutoGen AutoGPT BabyAGI for building managing and orchestrating intelligent agents.
• LLM APIs: OpenAI (GPT4/3.5 Anthropic (Claude) Cohere Hugging Face Transformers.
• Memory & Vector Databases: FAISS Weaviate Pinecone Chroma for embeddingbased agent memory and contextual retrieval.
• Prompt Management Tools: PromptLayer LangSmith for testing evaluating and refining agent prompts and traces.
• RAG & Context Enrichment: LangChain RAG pipelines Haystack Milvus.
• Autonomy Infrastructure: Docker FastAPI Redis Celery for building scalable agent runtimes.
• Observability: OpenTelemetry Langfuse (or similar) for tracing agent decisions failures and success metrics.
• Testing Agentic Behavior: Integration with PyTest mock APIs/tools to validate autonomous decision logic and fallback strategies.

Agentic AI systems,Restfull APIs,Retrieval-Augmented Generation (RAG),NLP models,Text Analytics,NLP,Name Entity,agent prompting,Generative AI, Large Language Models (LLM), Embeddings, Vectors, RAG (Retrieval-Augmented Generation) and Prompting