AI Engineer
Posted Updated 30
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Summary
Hands-on AI Engineer at an engineering services firm, building AI agents, LLM-powered workflows and automations from prototype to production, along with the backend services, APIs and integrations that connect them to real client business processes. Core stack: Python, LLMs, prompt engineering, RAG and agentic frameworks.
Shuru is an AI, Product and Technology Engineering company helping startups and enterprises build, scale and modernise digital products. Our teams work with high ownership, first-principles thinking and an AI-native approach to solve meaningful business problems and ship production-grade technology.
We are looking for a hands-on AI Engineer who enjoys turning ambiguous problems into working products. You will build AI agents, intelligent systems, AI-powered workflows, automations, and integrations, taking ideas from prototype to production. This role is ideal for a strong builder who can work across AI, backend systems, APIs, and real-world business workflows. You will work closely with product, engineering, and business stakeholders to understand problems, experiment with solutions, and ship reliable AI systems into production.
What You’ll Build
- Develop memory, context, state management, and retrieval layers.
- Build frameworks for prompts, tools, guardrails, retries, and workflow testing.
- Create agent evaluation and regression testing frameworks.
- Implement observability for traces, latency, errors, token usage, and quality.
- Build secure APIs using Python and FastAPI.
- Integrate agents with APIs, event streams, vector databases, and enterprise systems.
Requirements
- The ideal candidate should have 5+ years of experience in Python and backend development, with strong hands-on experience in FastAPI, REST APIs, and microservices.
- They should have at least 2+ years of experience building agentic or LLM applications using LangGraph, LangChain, or similar frameworks.
- Strong experience in memory and context engineering, agent evaluation, workflow testing, and AI observability is required.
- The candidate should also have experience working with MongoDB or other document databases, along with AWS or other cloud-native environments.
- Experience with Docker, Kubernetes, Kafka, AWS Bedrock, vector databases, MCP, knowledge graphs, and human-in-the-loop workflows will be preferred.
- Experience building AI applications in healthcare or another regulated domain.
Benefits
- Work on international projects: Be part of a global team working with clients from across the world.
- Regular team outings: Even with remote work, we believe in building strong team bonds through regular social and team-building events.
- Collaborative & growth-oriented: Learn from senior engineers, work in a collaborative environment, and grow professionally with opportunities for career development.
- Competitive Salary and Benefits