Senior Software Engineer

Software Engineer
AI Agents | Full Stack | Customer Implementation
Location: Bangalore
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.
Working knowledge of TypeScript/JavaScript and frontend development.
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

Work arrangement
No