About the role
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.
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.
- Independently take assigned AI workflows from requirements development to testing to production.
Requirements:
- 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.
- 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.