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Agent Developer
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Chennai, Tamil Nadu, India
Work mode:
Hybrid
Published on:
27 August 2026
What they need
Position: Agent Developer
Location: Chennai Hybrid Mode
Experience: 6+ Years
Notice Period: Immediate
Job Description
Builds AI agents, prompts, skills, and reasoning pipelines that automate scoping, decomposition, planning, testing, and specification synthesis.
Responsibilities
- Develop AI agents, workflows, skills, prompts, and reasoning pipelines using agent-orchestration frameworks.
- Build agents for scoping, domain decomposition, planning, test generation, and specification synthesis.
- Integrate Retrieval-Augmented Generation (RAG) and context-retrieval layers to ground agent outputs.
- Design and implement guardrails based on approved technology standards, naming conventions, and pre-checks sourced from the knowledge base.
- Create reusable prompt libraries, agent skills, and evaluation datasets.
- Continuously evaluate model performance, grounding quality, hallucination rates, and reasoning accuracy.
- Collaborate with backend and platform teams to operationalize agent capabilities.
Qualifications
- Bachelor's or Master's degree in Computer Science, AI, or a related discipline.
- 6+ years of total experience and 2+ years of Agent development experience.
- Strong Python programming expertise.
- Hands-on experience with LLMs, agent-orchestration frameworks, prompt engineering, and vector databases.
- Experience with RAG patterns, context engineering, and knowledge retrieval.
- Experience developing autonomous, tool-using, planning, and multi-agent systems.
- Familiarity with evaluation frameworks, observability tooling, and AI guardrails.
- Understanding of enterprise integration patterns and cloud platforms.
Mandatory Tech Stack
- Language: Python
- Agent Frameworks: LangGraph / LangChain or equivalent agent-orchestration frameworks
- LLM APIs: OpenAI / Anthropic / Bedrock / Azure OpenAI or equivalent foundation-model APIs
- Agentic RAG & Retrieval: Vector databases such as Pinecone / FAISS, embeddings, and semantic search
- Prompting: Prompt engineering, context engineering, and structured outputs
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