Builds the 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 (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.





Solid 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: Lang Graph / Lang Chain 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.

📌 Gen AI + Python (India)
🏢 GK HR Consulting India Private
📍 India