Senior AI Engineer – Agentic AI & Backend

Experience: 5+ Years

Location: Bangalore

Work Mode: Hybrid

Employment Type: Full-time

About the Role

We are looking for a Senior AI Engineer to design, develop, and operate production-ready AI systems powered by LLMs and intelligent agents.

You will be responsible for building the engineering foundation behind AI agents, MCP-based integrations, agentic workflows, and AI-powered connectors. The role involves taking solutions from architecture and development through deployment, monitoring, evaluation, and continuous improvement.

This is a hands-on engineering position, not a research or prompt-engineering role. You should enjoy solving complex engineering problems and building reliable AI applications that can operate at scale.

Key Responsibilities

• Design and develop MCP servers that allow AI agents to securely access data, APIs, and business capabilities.

• Build robust agentic workflows involving tool calling, orchestration, multi-step execution, and human approval when required.

• Develop integrations that connect AI agents with external applications, platforms, and enterprise systems.

• Own services throughout their lifecycle, including architecture, development, deployment, monitoring, and production support.

• Establish evaluation processes to measure agent accuracy, reliability, and behavioral consistency.

• Implement logging, tracing, and observability to understand and troubleshoot AI-agent behavior.

• Improve systems for performance, latency, cost efficiency, scalability, and reliability.

• Create reusable SDKs, frameworks, and engineering components for AI development.

• Work closely with Product, Design, Engineering, and customer-facing teams to convert requirements into production solutions.

• Evaluate emerging technologies across the rapidly evolving LLM and agent ecosystem.

Required Qualifications

• 5+ years of software engineering experience with experience delivering production systems.

• Strong hands-on expertise in Python backend development.

• Proven experience developing and deploying LLM-powered applications or AI agents.

• Practical knowledge of:

• Function/tool calling

• Structured outputs

• Prompt chaining

• Agent orchestration

• Multi-agent systems

• Human-in-the-loop workflows

• Experience developing MCP servers or equivalent AI integrations/tool interfaces.

• Understanding of LLM evaluation and testing methodologies.

• Experience deploying applications using AWS, GCP, or similar cloud platforms.

• Good knowledge of Docker and containerized applications.

• Experience with asynchronous programming in Python.

• Strong understanding of APIs, backend architecture, and distributed services.

• Ability to make sound technical decisions while keeping the end-user and business requirements in mind.

Preferred Skills

• Experience with LangGraph, LangChain, Anthropic SDK, Pydantic-AI, CrewAI, or similar agent frameworks.

• Familiarity with AI observability and tracing platforms such as Langfuse, LangSmith, or OpenTelemetry.

• Exposure to LLMOps, agent evaluation, and AI monitoring.

• Experience with digital analytics, application monitoring, APM, or observability platforms.

• Contributions to open-source AI/engineering projects, technical blogs, presentations, or community initiatives are a plus.