Senior AI Engineer
- Posted 25 days ago
- Be among the first 10 applicants
Job Description
Role Overview
We are seeking a Senior AI Engineer (5–7 years experience) to drive system architecture and execution within our lean AI engineering pods. You will build resilient, scalable backend infrastructure and construct complex agent topologies. You are expected to operate with high independence, lead technical design discussions, and maintain rigorous engineering standards across the entire delivery lifecycle.
Key Responsibilities
- System Architecture: Design and develop high-throughput, fault-tolerant Python services utilizing FastAPI, containerization, and EKS/Kubernetes orchestration.
- Advanced Agentic Engineering: Architect complex agent loops, state persistence strategies, tool integration layers, and multi-agent interaction systems.
- Evals & Observability Infrastructure: Establish robust evaluation frameworks, ground-truth benchmark datasets, logging pipelines, and real-time observability stacks.
- Trade-Off Analysis: Evaluate framework implementations (LangGraph, LangChain, Strands, ADK vs. custom components), documenting technical decisions and performance trade-offs.
- Independent Execution: Drive product delivery in a 2-person pod model without relying on large support teams, taking ownership from RFC/design to production deployment.
Required Qualifications & Experience
- Experience: 5–7 years in backend production engineering and systems development.
- Agentic AI Expertise: 2–3+ years of production experience shipping multi-tool agentic applications into production environments.
- Technical Mastery: Deep knowledge of Python, FastAPI, microservices architecture, Docker, AWS EKS/Kubernetes, and CI/CD pipelines.
- Hands-on Production Track Record: Ability to explain end-to-end architectures of real-world systems you personally built, deployed, and monitored in production.
- Domain Depth: Complete grasp of agent execution loops, state management, ground-truth evaluations, and system observability tools.
More Info
Key Skills
About Company
Skills:
Llama), LLMs (GPT, Weaviate), vector databases (FAISS, Orchestration, Docker, Python, AWS, React, Gcp, MLops, Kubernetes, Prompt engineering, multi-agent orchestration, tool-using AI agents, Azure OpenAI, RAG pipeline development, Plan-and-Execute, Multi-Agent Systems, Pinecone, LangChain, CrewAI, Generative AI, Agentic AI development, Claude, LLMOps, Semantic Kernel, AutoGen, CI/CD
Skills:
Apis, Docker, Cloud Infrastructure, Python, LLM tool calling, RAG embeddings, LLM-powered applications, vector search and retrieval strategies, scalable architectures
Skills:
cloud platform , Monitoring Tools, Prometheus, Grafana, Datadog, Microservices, Docker, Terraform, Authentication, full stack development, Sql, Application Security, Containers, Rest Apis, Kubernetes, vector databases, backend language, Relational Databases, AI products, modern frontend technology, model deployment, LLM apps, Caching, CI CD pipelines, AI agents
Skills:
Jenkins, Typescript, Python, Test Architecture, GitHub Actions, Playwright, AI coding tools, LLM experience, prompt engineering, context retrieval agents
Skills:
cloud security, Azure ML, Azure, Python, LLM evaluation guardrails, AI GenAI development, Azure OpenAI, Semantic Kernel, LangGraph, AutoGen, ML fundamentals, cost management, LlamaIndex