Summary
✨ AI‑Generated
Build high-performance backend services that connect foundation models, retrieval systems, and internal services. You will design agentic workflows with tool use, routing, evaluation, and state management, integrate modern model APIs, optimize prompts and context usage, and maintain well-tested, documented production code.
Highlights
An advanced engineering opportunity focused on building low-latency AI integrations and autonomous agent systems, with substantial exposure to modern foundation models, orchestration, prompt optimization, and production-quality software engineering.
Description
Job Description
Backend & Systems Integration: Architect and build concurrent, low-latency microservices and middleware in Go (Golang) to interface with foundation model APIs, context retrieval systems, and internal services.
Agentic Orchestration: Design and implement autonomous and semi-autonomous multi-step agentic systems, including tool use/function calling, task routing, evaluation loops, and state management.
Model Integration & Claude SDK: Leverage the Anthropic Claude SDK (and related model APIs) to integrate advanced reasoning, multimodal features, structured JSON outputs, and large-context document processing.
Prompt Engineering & Optimization: Apply systematic prompt engineering techniques (chain-of-thought, few-shot prompting, system prompts, dynamic context windows) to maximize output reliability, reduce hallucinations, and control token usage.
Codebase & Version Control: Maintain high code quality, test coverage, and documentation within team repositories using Git across GitLab or GitHub.
Required Qualifications
Proficiency in Go (Golang): Strong experience writing idiomatic, concurrent, and high-performance backend microservices (goroutines, channels, REST/gRPC interfaces).
AI Model Integration & SDKs: Hands-on experience integrating with commercial LLM APIs, with direct experience using the Claude SDK / Anthropic API for structured data extraction and tool calling.
Prompt Engineering: Demonstrated expertise in designing, testing, and optimizing system prompts, dynamic templates, and evaluation strategies for reliable model responses.
Version Control & Collaboration: Proficient with Git and platform workflows in GitLab or GitHub(PRs/MRs, branch management, code review hygiene).
Preferred Qualifications
Experience building or integrating standard tool-use protocols (such as Model Context Protocol / MCP or custom tool schemas).
Familiarity with vector databases, semantic search, and hybrid Retrieval-Augmented Generation (RAG) pipelines.
Understanding of LLM evaluation frameworks, token optimization strategies, and latency/cost mitigation patterns (caching, streaming, batching).
