AI talent search and infrastructure advisory for scaling engineering teams
Impala Search operates as a three-pillar talent and infrastructure firm: securing engineering talent (software, AI, infrastructure specialists, and executives), brokering fundraising relationships, and advising on enterprise AI adoption. The tech stack—React, TypeScript, Python, TensorFlow, PyTorch, FastAPI, LangChain, CrewAI—reveals heavy AI/ML engineering capability underpinning their own tooling and advisory. Active hiring is concentrated in senior and lead-level engineers across Bulgaria and Germany, with 10 roles posted in the last 30 days; projects center on voice AI agents, real-time dialogue, and enterprise AI infrastructure, suggesting they're building internal platforms to support the talent and capital advisory process.
Impala Search helps mid-market and growth-stage companies scale engineering capacity, raise capital, and deploy AI effectively. The Talent Search division places software engineers, AI specialists, and infrastructure professionals; Capital Search connects founders with investors; and AI Search & Activate advises on AI strategy, hiring, and implementation. Founded in 2018 and based in London, the firm operates with 11–50 employees and is actively hiring senior engineers and technical leadership, primarily in Bulgaria and Germany. Their own product—voice AI agents, real-time dialogue systems, and enterprise AI platforms—mirrors the problems their customers face when scaling infrastructure and adopting AI.
Frontend: React, TypeScript, Next.js, GraphQL. Backend: Python, FastAPI, Node.js, Laravel. ML/AI: TensorFlow, PyTorch, LangChain, CrewAI, Hugging Face, Ray. Data/storage: MongoDB, Redis, SQL. Infrastructure: Docker, AWS (recently adopted). Workflow/no-code: Retool, n8n, Airtable. Development tools: Cursor, Claude, GitHub Copilot.
Voice AI agents, real-time AI dialogue systems, AI agent management platforms, performance optimization, core infrastructure for low-latency interaction, and enterprise AI infrastructure. Projects address scaling real-time voice AI and reducing processing costs in distributed systems.
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