Gen AI - Senior Developer
Primary stack
Job description
About the Position
We’re looking for a GenAI Senior Developer to design, build, and deploy intelligent LLM-powered systems-from single-agent chatbots, copilots to complex multi-agent applications - at scale. We are particularly interested in candidates who have hands-on experience in taking GenAI applications from concept to production, especially within high-volume B2C environments. This role prioritizes individuals who understand the nuances of deploying, maintaining, and optimizing GenAI solutions for real-world users, beyond the scope of Proof-of-Concept (PoC) development. You will work across the full stack, integrating LLMs, microservices, vector databases, backend APIs, and modern cloud infrastructure.
Responsibilities
GenAI Application Development & Deployment
- Develop scalable, asynchronous microservices using Python (FastAPI) for chatbots, copilots, and agentic workflows;
- Design event-driven architectures to support high concurrency, rate limiting, and real-time responsiveness;
- Implement secure, versioned REST/gRPC APIs;
- Use Pydantic, dependency injection, and modular coding practices for maintainability;
- Proficient in working with databases using ORMs like SQLAlchemy;
- Ensure observability using logging, metrics, tracing, and health checks;
- Create responsive React.js frontends integrated via REST APIs or WebSockets;
- Deploy applications on Cloud Run, GKE, using Docker, Artifact registry, CI/CD pipelines.
LLM-Powered Conversational Interfaces
- Design and build LLM-powered chatbots, voicebots, copilots and other applications using LangChain or custom orchestration frameworks;
- Integrate enterprise-grade LLM APIs (Gemini, OpenAI, Claude) for multi-turn, intelligent interactions;
- Implement user session management and context/state tracking for personalized and continuous conversations;
- Build RAG pipelines with vector databases, knowledge graphs to ground responses with external knowledge and documents;
- Apply advanced prompt engineering (ReAct, Chain-of-Thought with tool calling) for precise and goal-oriented outputs;
- Ensure performance in low-latency, streaming environments using WebSockets, gRPC, and SIP media gateways;
- Perform fine-tuning of open-source LLMs (LLaMA variants) using techniques like SFT, LoRA, for cost-effective domain adaptation;
- Optimize high-speed inference pipelines leveraging multi-GPU clusters (up to 8x H100s) to reduce latency and improve throughput.
Multi-Agent Systems & Orchestration
- Create multi-agent systems & Implement orchestration patterns like supervisor-agent, hierarchical, and networked agents using frameworks like ADK, Pydantic AI and LangGraph;
- Use LangGraph for stateful workflows with memory, conditional branching, retries, and async execution;
- Enable persistent context and long-term memory;
- Monitor behavior, drift, and performance using observability tools;
- Skilled in developing agents with ADK and A2A protocols & experienced in configuring custom and remote MCP servers.
Requirements
- Languages/Frameworks: Python, FastAPI, HTML, CSS, React.js, LangChain, LangGraph, Pydantic AI, ADK (Agent DevelopmentKit)
- LLMs & Agents: OpenAI - (GPT-4), Claude, Gemini, Mistral, LLaMA 3.2/4
- Databases: BigQuery, Redis, FAISS, Pinecone, SQLAlchemy, Chroma, GCP Vector search
- Protocols/APIs: REST, gRPC, WebSockets, OAuth2, OpenAPI, MCP, A2A
Nice to Have
- DevOps: Docker, GitHub Actions, Jenkins, GKE, Cloud Run
- Infra & Tools: GCP, Azure, Pub/Sub, Artifact Registry, NGINX, Langfuse, Postman, Pytest
We Offer
- Location: Brasov, Remote
- Company size: 50-100
- Employment type: Full-time
About the Company
Join our innovative team in the Technology industry and contribute to cutting-edge projects that leverage the latest advancements in AI and machine learning.
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