Generative AI Agent Engineer - Agent Design & Performance

Proof of Skill; Hyderabad; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Chryselys is seeking a Generative AI Agent Engineer to design, build, and optimize intelligent agents that can reliably reason, use tools, and complete complex workflows. This role focuses on agent behavior, tool design, orchestration, evaluation, and performance.

Responsibilities include designing architectures and tools, building multi-step task pipelines, and collaborating with platform engineers to deploy agents in production with robust best practices.

Qualifications

• 3+ years of experience in software engineering, machine learning, or GenAI application development.
• Hands-on experience designing and deploying LLM-powered agents or agentic workflows.
• Strong understanding of prompting, tool calling, structured outputs, planning, RAG, memory, and context management.
• Experience designing APIs and tools for agents, with attention to usability, reliability, permissions, and clear contracts.
• Proficiency in Python, TypeScript, or a comparable programming language.
• Experience with agent frameworks such as LangGraph, LangChain, or similar technologies.
• Familiarity with AWS and preferably AWS AgentCore.
• Experience with agent evaluation, observability, tracing, experimentation, and performance optimization.
• Strong understanding of distributed systems, APIs, asynchronous workflows, and production software practices.

Responsibilities

• Design agent architectures, workflows, instructions, decision logic, and collaboration patterns.
• Define and build high-quality tools, including tool schemas, inputs, outputs, permissions, error handling, and user feedback.
• Develop agents that can plan, reason, retrieve information, call APIs, and complete multi-step tasks reliably.
• Optimize agent performance across accuracy, task completion, latency, cost, consistency, and user experience.
• Design memory, context, retrieval, and summarization strategies that improve agent effectiveness.
• Create evaluation frameworks, test scenarios, benchmarks, and quality metrics for agent behavior.
• Analyze agent traces and failures to identify issues with prompts, tools, routing, context, or orchestration.
• Implement guardrails for safety, security, hallucination reduction, authorization, and human-in-the-loop escalation.
• Build multi-agent workflows and agent-to-agent interactions where appropriate.
• Collaborate with application and platform engineers to integrate agents into production systems.
• Establish reusable patterns and best practices for agent development and continuous improvement.

Skills

GenAI agent development

LLM-powered agents

Prompting and tool calling

API/tool design

Python

TypeScript

LangChain/LangGraph

AWS familiarity

Observability and tracing

Distributed systems

Tools

LangGraph

LangChain

AWS AgentCore

Job description

Chryselys is a Great Place to Work Certified Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations. We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights.

Role Summary

We are seeking a Generative AI Agent Engineer to design, build, and optimize intelligent agents that can reliably reason, use tools, and complete complex workflows. This role focuses on agent behavior, tool design, orchestration, evaluation, and performance.

Responsibilities

• Design agent architectures, workflows, instructions, decision logic, and collaboration patterns.
• Define and build high-quality tools, including tool schemas, inputs, outputs, permissions, error handling, and user feedback.
• Develop agents that can plan, reason, retrieve information, call APIs, and complete multi-step tasks reliably.
• Optimize agent performance across accuracy, task completion, latency, cost, consistency, and user experience.
• Design memory, context, retrieval, and summarization strategies that improve agent effectiveness.
• Create evaluation frameworks, test scenarios, benchmarks, and quality metrics for agent behavior.
• Analyze agent traces and failures to identify issues with prompts, tools, routing, context, or orchestration.
• Implement guardrails for safety, security, hallucination reduction, authorization, and human-in-the-loop escalation.
• Build multi-agent workflows and agent-to-agent interactions where appropriate.
• Collaborate with application and platform engineers to integrate agents into production systems.
• Establish reusable patterns and best practices for agent development and continuous improvement.

Qualifications

• 3+ years of experience in software engineering, machine learning, or GenAI application development.
• Hands-on experience designing and deploying LLM-powered agents or agentic workflows.
• Strong understanding of prompting, tool calling, structured outputs, planning, RAG, memory, and context management.
• Experience designing APIs and tools for agents, with attention to usability, reliability, permissions, and clear contracts.
• Proficiency in Python, TypeScript, or a comparable programming language.
• Experience with agent frameworks such as LangGraph, LangChain, or similar technologies.
• Familiarity with AWS and preferably AWS AgentCore.
• Experience with agent evaluation, observability, tracing, experimentation, and performance optimization.
• Strong understanding of distributed systems, APIs, asynchronous workflows, and production software practices.

Preferred Qualifications

• Experience with multi-agent systems and A2A or MCP protocols.
• Experience building agents for complex enterprise or regulated-industry workflows.
• Familiarity with model routing, prompt versioning, fine-tuning, guardrails, and human-in-the-loop patterns.
• Strong understanding of identity, authorization, data privacy, and secure tool execution.
• Experience translating business processes into reliable agent workflows and measurable outcomes.