Overview

Our mission is to break down geographical barriers and create meaningful career opportunities where talented individuals can thrive, grow, and make a genuine impact.

Responsibilities

• Build and evolve production AI agents on foundation models, currently AWS Bedrock.
• Develop and evolve orchestration for production AI agents.
• Apply context engineering to production LLM and agent systems.
• Build and maintain evaluation datasets and pipelines, including tool-selection, trajectory and LLM-as-judge evaluations.
• Build and maintain production observability and monitoring for LLM and agent systems.
• Implement and work with tracing and instrumentation for production LLM systems.
• Work directly alongside the engineer currently leading the AI-agenting function as the first dedicated hire in this area.
• Apply strong agent-architecture fundamentals to help inform whether the existing custom orchestration layer should be retained or a production framework adopted.
• Work as part of a new three-person product team alongside the AI function lead and a Full Stack Engineer.
• Operate as an individual contributor working alongside the AI function lead rather than managing others.
• Take ownership of measurable deliverables immediately upon onboarding.
• Deliver similar AI/agent engineering work against roadmap timelines.

Qualifications

• 2+ years of experience building production LLM agents, including tool-calling agent loops, streaming, context management, structured outputs and orchestration frameworks.
• Production experience with an agentic framework such as LangGraph, LangChain or custom orchestration. There is no fixed orchestration framework requirement; strong agent-architecture fundamentals and production experience with any agentic framework are in scope. - 1.5+ years of experience with evaluation-driven development, including building and maintaining evaluation datasets and pipelines covering tool selection, trajectory evaluation and LLM-as-judge.
• 1+ year of experience with LLM observability, tracing and instrumentation using Langfuse, OpenTelemetry or similar tooling.
• Genuine production agent-observability exposure. Direct, hands-on Langfuse experience is strongly preferred because this is a confirmed skill gap within the team; OpenTelemetry or other tracing tools are acceptable only as a secondary signal alongside real agent-observability exposure. - 1+ year of experience with LLM cost optimisation, including prompt caching, model selection and routing, and LLM FinOps.
• 5+ years of backend engineering proficiency, including TypeScript/Node, Postgres and serverless AWS.
• Proven experience delivering similar work on similar timelines.

Nice to have

• 1+ year of AWS Bedrock experience. Equivalent production experience with other foundation-model providers, including OpenAI, Anthropic API, Azure OpenAI or Vertex AI, is fully transferable.
• 1+ year of experience with AI safety and guardrails, including prompt-injection screening, output validation and handling untrusted input.
• 6+ months of familiarity with MCP and multi-agent patterns.
• Familiarity with geospatial data.

Benefits

• Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter)
• No Weekend Work: Real work-life balance, not just words
• Day 1 Benefits: Laptop and full medical insurance provided
• Support That Matters:Mentorship, community, and forums where ideas are shared
• True Belonging: A long-term career where your contributions are valued