Senior Software Engineer

Questhiring; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Questhiring is seeking a Mid-Level Software Engineer in Bengaluru to build AI-powered customer implementations. You will translate workflows into AI agents and backend services, deploy APIs, integrations, and front-end features, and work across voice, chat, SMS, and email experiences.

You will design prompts, flows, tool calls, and agent state management, while ensuring secure, scalable production deployments using cloud, Docker, CI/CD, and observability tools.

Qualifications

• 3–5 years of software engineering experience.
• Hands-on in AI agents, LLM-powered applications, backend development, and integrations.
• Strong experience with REST APIs, webhooks, and authentication.

Responsibilities

• Translate customer workflows into AI-powered solutions.
• Build and deploy AI/LLM-powered agents for business processes.
• Develop prompts, flows, tool calling, and agent state management.
• Create backend services, APIs, integrations, and frontend features.
• Integrate enterprise apps via REST APIs, webhooks, and JSON.
• Support voice, chat, SMS, and email experiences as needed.
• Implement RAG, embeddings, vector search, and knowledge workflows.

Skills

AI agents

LLM-powered apps

Backend development

REST APIs

Prompts engineering

Python

Java

Go

Rust

LangChain

LangGraph

LlamaIndex

OpenAI Agents SDK

Docker

CI/CD

JSON

OAuth / Authentication

PostgreSQL

Redis

AWS/GCP/Azure

Tools

LangChain

LangGraph

LlamaIndex

OpenAI Agents SDK

Google ADK

PostgreSQL

Redis

AWS

Docker

CI/CD

Job description

AI Agents | Full Stack | Customer Implementation

Experience: 3–5 years

Role Overview

We are looking for a Mid-Level Software Engineer with hands-on experience in AI agents, LLM-based applications, backend development, and integrations.

You will work on customer-facing implementations, translating business workflows into AI-powered solutions. The role involves building AI agents, developing APIs and backend services, integrating enterprise systems, and taking solutions from development through production deployment.

Key Responsibilities

• Understand customer workflows and convert requirements into technical implementation plans.


• Build and deploy AI/LLM-powered agents for conversational and business workflows.


• Develop prompts, conversation flows, tool calling, decision logic, and agent state/memory.


• Build production-quality backend services, APIs, integrations, and frontend features.


• Integrate enterprise applications using REST APIs, webhooks, JSON, authentication, and event-driven services.


• Work across voice, chat, SMS, and email experiences where required.


• Implement RAG, retrieval, embeddings, vector search, and knowledge-based AI workflows.


• Test AI agents and integrations for failure scenarios, authentication issues, unexpected inputs, retries, and tool failures.


• Build and monitor evaluations for accuracy, task completion, response quality, latency, and reliability.


• Deploy and support solutions in production using cloud, Docker, CI/CD, and observability tools.


• Troubleshoot production issues and continuously improve agents, prompts, retrieval, and application code.


• Create technical documentation and conduct customer walkthroughs when required.

Required Skills

• 3–5 years of relevant software engineering experience.


• Strong backend development experience in Python, Java, Go, or Rust.


• Hands-on experience building AI agents, conversational AI, or LLM-powered applications.


• Experience with LangChain, LangGraph, LlamaIndex, OpenAI Agents SDK, Google ADK, or similar frameworks.


• Strong understanding of REST APIs, webhooks, JSON, authentication, databases, and system integrations.


• Experience with prompt engineering, tool calling, structured outputs, and agent workflows.


• Knowledge of RAG, embeddings, vector databases, or hybrid search.


• Experience with PostgreSQL/Redis or similar databases.


• Familiarity with AWS/GCP/Azure, Docker, CI/CD, and production monitoring.


• Good understanding of automated testing, security, secrets management, and sensitive-data handling.


• Strong communication skills and ability to work directly with customers to understand and solve technical problems.

Good to Have

• Experience with MCP (Model Context Protocol) and agent memory/state management.


• Experience with voice AI, WebSockets/WebRTC, streaming APIs, STT/TTS, or platforms such as LiveKit/Deepgram/ElevenLabs.


• Experience integrating Salesforce, HubSpot, CRM, contact-center, or enterprise workflow systems.


• Experience with AI evaluation/observability tools such as LangSmith, Arize Phoenix, Braintrust, or OpenTelemetry.


• Familiarity with AI coding tools such as Cursor, GitHub Copilot, Claude Code, or Codex.

What Success Looks Like

• Independently take assigned AI workflows from requirements → development → testing → production.


• Build reliable AI agents that can execute intended actions and handle failures appropriately.


• Deliver secure, scalable, tested, and maintainable solutions.


• Effectively communicate technical solutions to customers and internal stakeholders.


• Continuously improve AI solutions using production data, evaluations, and customer feedback.

Key Skills / Keywords

AI Agents | LLM | Generative AI | LangChain | LangGraph | LlamaIndex | OpenAI Agents SDK | Prompt Engineering | RAG | MCP | Python | Java | REST API | Webhooks | Backend Development | TypeScript | PostgreSQL | Redis | Vector Database | AI Evaluation | AWS | Docker | CI/CD